RBI unclaimed deposits directives 2025

RBI’s Directive On Unclaimed Deposits 2025 & The Role Of Digital Address Verification

Introduction

In September 2025, the Reserve Bank of India (RBI) issued a clear and time-bound directive to scheduled commercial banks across the country: return over ₹67,000 crore in unclaimed deposits within three months. These funds, which have been lying dormant in banks for over a decade, reflect savings and investments that depositors or their heirs have not claimed.

According to official data presented in Parliament, ₹67,270 crore in unclaimed deposits had accumulated by June 2025, with nearly 87 per cent of these funds held by public sector banks. The State Bank of India alone accounts for close to ₹19,330 crore, followed by Punjab National Bank and Canara Bank, each with over ₹6,000 crore. Among private banks, ICICI Bank leads with over ₹2,000 crore in unclaimed deposits.

The central bank has set a strict three-month window—from October to December 2025—for institutions to intensify their efforts to trace account holders or their heirs. 

What Are Unclaimed Deposits?

Unclaimed deposits are amounts parked in bank accounts or term deposits that remain untouched for ten years or more. If there are no customer-initiated transactions, such as withdrawals, deposits, or instructions, over this period, the account is treated as inoperative.

By regulation, once these deposits cross the dormancy threshold, they are transferred by banks to the Depositor Education and Awareness (DEA) Fund maintained by the RBI. The intent behind this framework is to protect idle money from misuse and to ensure that rightful owners or their heirs can claim it at any point through a structured process.

Despite these measures, the scale of the problem is enormous. The funds in question represent both financial assets forgotten by individuals and systemic gaps in outreach. Many heirs are unaware of accounts held by deceased relatives, and in other cases, documentation gaps make it difficult for claimants to establish ownership.

The Scale Of Unclaimed Deposits

The RBI’s disclosure puts the size of unclaimed deposits at ₹67,270 crore as of June 2025. Public sector banks dominate this pool, reflecting their large customer base and legacy operations. Here are a few of the banks with their unclaimed deposits:

Bank

Unclaimed Deposits (₹ crore)

State Bank of India (SBI)

19,329.29

Punjab National Bank (PNB)

6,910.67

Canara Bank

6,278.14

Bank of Baroda

5,277.36

Union Bank of India

5,104.50

ICICI Bank

2,063.45

Other Private Banks (combined)

8,673.72

Total (All Banks)

67,270

RBI’s Instructions To Banks

The Reserve Bank of India has issued time-bound instructions to banks, directing them to intensify efforts between October and December 2025 to return unclaimed deposits.

Key Directives From The RBI

  • Special Outreach Drive (Oct–Dec 2025):
    Banks have been asked to run a targeted campaign over three months to trace account holders or their heirs. The focus will be on proactive engagement rather than passive compliance.

  • Role Of State Level Bank Committees (SLBCs):
    SLBCs are required to review progress at a granular level, breaking down data by region and age of deposit, and ensuring that lagging banks step up their efforts.

  • Public Awareness Measures:
    Banks must reach out to customers through various media, including print, electronic, and digital channels, with a special focus on rural and semi-urban areas where awareness levels are often lower.

  • Grievance Redressal:
    Institutions must strengthen grievance redressal mechanisms to ensure that claimants face fewer procedural hurdles when retrieving funds.

  • UDGAM Portal:
    A central plank of this drive is the UDGAM (Unclaimed Deposits – Gateway to Access Information) portal maintained by the RBI. This digital platform allows individuals to search for unclaimed deposits across multiple banks using simple identifiers such as their name, PAN, or address.

UDGAM Portal Homepage

As of July 2025, nearly 8.6 lakh users had registered, and the portal now covers banks that account for around 90% of unclaimed deposit value.

Challenges In Returning Dormant Deposits

While the RBI’s directive is clear and time-bound, executing it on the ground poses significant challenges. The sheer magnitude of ₹67,270 crore in dormant funds means banks must overcome structural, operational, and human barriers to reunite depositors with their money.

  • Tracing The Rightful Owners

One of the greatest hurdles lies in locating the original depositors or their heirs. Over time, customers may have moved houses, migrated abroad, or passed away, leaving no clear trail for banks to follow. Inheritance complexities add another layer of difficulty, especially in the absence of updated nominee information.

  • Documentation And Proof

Even when claimants are identified, retrieving deposits often hinges on producing valid documents such as identity proofs, succession certificates, or death certificates of deceased account holders. In many cases, these documents are either missing or difficult to obtain, delaying the process.

  • Awareness And Financial Literacy Gaps

A large proportion of dormant deposits belong to individuals in rural and semi-urban regions. Limited awareness of banking rules, lack of digital access, and low financial literacy mean that many potential claimants are unaware of their rights or the steps required to reclaim funds.

  • Operational Inefficiencies

Banks themselves face operational bottlenecks. Branch-level staff may not always have updated contact information, and in some cases, the processes for claim settlement remain manual, cumbersome, and time-consuming.

  • Risk Of Fraudulent Claims

Efforts to return unclaimed deposits must also be safeguarded against fraudulent attempts, where impostors may try to exploit gaps in verification mechanisms. This necessitates robust verification tools that can balance customer convenience with security.

The Scale of the Challenge

As per RBI’s directive, banks must return ₹67,000 crore lying in dormant accounts within 3 month

These deposits, untouched for over a decade, often belong to individuals who:

  • Have changed residences or migrated abroad.

  • Passed away without clear nominee details.

  • Remain unaware of their dormant accounts, especially in rural or semi-urban areas.

Traditional outreach methods — phone calls or emails — often fail. Contact numbers are outdated, email addresses bounce, and in many cases, families are unaware of the accounts at all. Simply shutting the account isn’t enough; banks must first trace and credit the rightful customer or heir.

AuthBridge’s Role: From Tracing To Compliance

When banks are pressed to act fast and at scale, mere promises don’t suffice. What matters is whether a solution can deliver across jurisdictions, risk tiers, connectivity constraints, and fraud vectors. AuthBridge’s address and contact point verification stack is built to meet exactly those demands. Below is a close look at the services.

At AuthBridge, we specialise in bridging the gap between compliance requirements and customer realities:

1. Skip Tracing For Account Closure
We leverage alternate data sources — credit bureau, utility, and telecom records — to trace rightful owners or heirs when contact details are missing.

2. Mobile-To-Address API (Powered by Shiprocket)
Our mobile-to-address API helps confirm and enrich contact data, scoring addresses against 12–13 trusted sources including national ID repositories. This accelerates discovery when customers cannot be reached directly.

3. Address Augmentation & Verification
Using mobile numbers, we link multiple data points to verify and augment addresses, reducing false positives and ensuring accurate outreach.

4. Re-KYC & Claimant Verification
Through video KYC, name screening, and account verification, we help banks securely re-onboard dormant customers or verify claimants before settlement.

5. Hybrid Approach: Digital + On-Ground
Where needed, our field verification teams complement digital workflows, ensuring even rural or hard-to-reach customers are traced effectivel

Conclusion

The RBI’s call to return ₹67,270 crore in unclaimed deposits within three months is both a challenge and an opportunity for banks. Success will depend on how effectively institutions can trace rightful claimants while safeguarding against fraud and delay. Digital tools such as AuthBridge’s Digital Address Verification (DAV) and GroundCheck.ai provide a practical answer—enabling banks to verify addresses in minutes, escalate seamlessly to on-ground checks when required, and build a transparent audit trail at every step. By adopting these solutions, banks not only stand to meet the RBI’s directive on time but also send a clear message of trust, accountability, and customer commitment.

RBI Master Direction September 2025 PA

RBI’s Updated Guidelines For Payment Aggregators 2025: Key Details

Introduction

On 15 September 2025, the Reserve Bank of India (RBI) issued the Master Direction on Regulation of Payment Aggregators (PAs). This consolidated framework supersedes earlier circulars — the 2020 and 2021 guidelines on Payment Aggregators and Gateways, and the 2023 directions on Cross-Border Payment Aggregators.

The new Direction has been issued under the powers conferred by Section 18, read with Section 10(2) of the Payment and Settlement Systems Act, 2007, together with Section 10(4) and Section 11(1) of the Foreign Exchange Management Act, 1999. It harmonises regulations for online, physical and cross-border aggregation of payments, introducing a common compliance regime for banks, non-banks, authorised dealer (AD) banks and scheduled commercial banks.

Key Definitions Under The RBI’s New Payment Aggregator Guidelines 2025

To understand the scope of the 2025 Master Direction, it is essential to first look at the definitions provided by the Reserve Bank of India. These definitions set the base for regulating Payment Aggregators (PAs) and Payment Gateways (PGs).

  1. A cash-on-delivery transaction is a merchant transaction in which banknotes or currency notes, being legal tender in India, are offered or tendered at the time of delivery of goods and services.
  2. Contact Point Verification (CPV) refers to the physical verification of the merchant’s address or place of business.
  3. E-commerce refers to the buying and selling of goods and services, including digital products, conducted over digital and electronic networks. For this definition, the term ‘digital and electronic network’ includes networks of computers, television channels, and other internet applications used in an automated manner, such as web pages, extranets and mobile platforms.
  4. An inward transaction refers to any transaction involving the inflow of foreign exchange, while an Outward transaction consists of the outflow of foreign exchange.
  5. A Marketplace is an e-commerce entity that provides an information technology platform on a digital or electronic network to facilitate transactions between buyers and sellers.
  6. A Merchant means an entity or marketplace that sells goods, provides services, or offers investment products. This also includes exporters and overseas sellers.
  7. Payment channel refers to the method or manner through which a payment instruction is initiated and processed in a payment system.
  8. A Payment Aggregator (PA) is an entity that facilitates the aggregation of payments made by customers to merchants through one or more payment channels, using the merchant’s interface (physical or virtual), to purchase goods, services, or investment instruments. Subsequently, it settles the collected funds to the merchant. The Directions categorise PAs into three types:
  • PA–Physical (PA–P): Facilitates transactions where the acceptance device and payment instrument are physically present in proximity.
  • PA–Cross Border (PA–CB): Facilitates aggregation of cross-border payments for current account transactions permissible under FEMA, through the e-commerce route. Two sub-categories exist under PA–CB: inward transactions and outward transactions.
    • It is clarified that non-bank entities authorised as AD Category-II, and facilitating current account transactions not prohibited under FEMA (other than purchase or sale of goods or services), do not fall within the purview of PA–CB business.
    • Similarly, a card transaction where the foreign exchange settlement is facilitated by a card network and the aggregator receives payment in local currency is not treated as PA–CB activity.
  • PA–Online (PA–O): Facilitates transactions where the acceptance device and payment instrument are not present in proximity at the time of payment.
  1. A Payment Gateway (PG) is defined as an entity that provides the technology infrastructure to route and facilitate the payment transaction processing without handling funds.

Finally, terms such as Central KYC Records Registry (CKYCR), Officially Valid Document (OVD), equivalent e-document, digital KYC, and Video-based Customer Identification Procedure (V-CIP) carry the same meanings as set out in the RBI’s Master Direction on Know Your Customer (2016), as amended from time to time.

Authorisation For Payment Aggregator Business

The Master Direction distinguishes between banks and non-bank entities operating as a Payment Aggregator. Here are the differences between banks and non-banks operating as PAs:

  • Banks do not require a separate authorisation from the RBI to provide PA services. Their existing powers and supervisory framework govern their activities.
  • Non-bank entities, however, must seek explicit authorisation from the RBI under the Payment and Settlement Systems Act, 2007. Only companies incorporated under the Companies Act, 2013, are eligible to apply.

To operationalise this requirement, the RBI has mandated that all non-bank Payment Aggregators submit their applications through the designated portal. Those who fail to apply by 31 December 2025 must wind down their PA business operations by 28 February 2026.

Capital Requirements For Payment Aggregators

To ensure that only entities with sufficient monetary capacity operate as PAs, the RBI has imposed a phased capital requirement:

  • At the time of application, a non-bank Payment Aggregator must demonstrate a minimum net worth of ₹15 crore.
  • By the end of the third financial year from the date of authorisation, this net worth must rise to ₹25 crore.

For this purpose, net worth is calculated in line with the Companies Act and relevant accounting standards. Compulsorily convertible preference shares may be included, but deferred tax assets are specifically excluded.

Governance And Management

The RBI has raised governance standards for Payment Aggregators in line with their growing role in handling public funds. Every PA is expected to be professionally managed, with its promoters and directors meeting the central bank’s fit and proper criteria. This entails solid financial integrity, a reputation for honesty, and freedom from disqualifications such as insolvency or conviction.

RBI has also closed the door on ownership changes slipping through unnoticed. Any takeover or acquisition of control, whether direct or indirect, requires prior approval from the RBI. This ensures that entities entrusted with merchant and customer funds remain under the regulator’s watch even when corporate structures shift.

To embed accountability, Boards of Payment Aggregators must frame policies on risk management, information security, and customer protection. These policies must not be a one-time exercise but must be subject to periodic review.

Dispute Resolution Framework

The RBI has mandated a time-bound framework for dispute resolution and refunds, aligned with its earlier Turn Around Time (TAT) prescriptions for failed transactions.

Payment Aggregators must enter into legally enforceable agreements with merchants and acquiring banks. These contracts must clearly allocate responsibility for settlement, refunds, and handling of disputes, reducing ambiguity in the payments chain.

Equally important is transparency for customers. Refund policies must be disclosed upfront, so payers know how their funds will be handled in the event of a reversal. Each PA must also appoint a grievance redressal officer and provide an escalation matrix to track and resolve complaints efficiently.

Security, Fraud Prevention And Risk Management

Every Payment Aggregator must implement a comprehensive risk management framework, including fraud prevention, suspicious activity monitoring, and controls safeguarding customer information.

Compliance with internationally recognised standards is compulsory. Aggregators must adhere to Payment Card Industry – Data Security Standards (PCI-DSS) and Payment Application – Data Security Standards (PA-DSS) where relevant. 

To verify adherence, Payment Aggregators must undergo an annual audit by a CERT-In empanelled auditor. This ensures independent validation of cybersecurity and system integrity. In addition, the Directions mandate compliance with RBI’s Cyber Resilience and Digital Payment Security Directions, 2024.

Data handling is another area where obligations are explicit. All payment system data must be stored in India, per the RBI’s 2018 data localisation circular. 

General Directions For Payment Aggregators

RBI has laid down a series of general directions that shape day-to-day business conduct for Payment Aggregators:

  • Contractual exclusivity: Aggregators may only facilitate payments for merchants with valid contracts. This ensures accountability and prevents misuse of aggregator platforms for unauthorised transactions.

  • Marketplace restriction: PAs are prohibited from running their own marketplaces. This prevents conflicts of interest between operating as a payments intermediary and competing as a merchant platform.

  • Merchant Discount Rate (MDR): PAs must comply fully with RBI’s prescriptions on MDR. Importantly, they are required to ensure that charges are transparently disclosed to merchants.

  • Refund rules: Refunds must, by default, be processed back to the original payment method. The only exception is when the customer opts for an alternative account under the same ownership.

  • Authentication norms: Using ATM PINs as an authentication factor is explicitly disallowed for card-not-present transactions.

Special Directions For Cross-Border Payment Aggregators

Entities facilitating payments for imports or exports via the e-commerce route must comply with additional safeguards to prevent misuse of outward remittances and to ensure alignment with FEMA.

Key provisions include:

  • Segregation of funds: Aggregators must maintain separate accounts for inward and outward flows. Inward and outward remittances cannot be commingled.

  • Transaction limits: Outward transactions are capped at ₹25 lakh per transaction. This ceiling prevents the misuse of aggregator channels for large-scale capital transfers.

  • Banking arrangements: Only Authorised Dealer (AD) Category-I–banks can be used to maintain collection accounts for inward (InCA) and outward (OCA) flows. This ensures settlement happens only through banks with full foreign exchange authorisation.

  • Settlement currency: Non-INR settlement is permitted only in cases where the merchant is an Indian exporter directly onboarded by the aggregator. For other cases, settlement must be in Indian Rupees.

  • Regulatory reporting: Cross-border PAs must provide sufficient data to their AD banks for reporting into RBI’s Export Data Processing and Monitoring System (EDPMS) and Import Data Processing and Monitoring System (IDPMS).

KYC And Due Diligence

Merchant onboarding lies at the heart of the Directions. RBI has imposed obligations that are closely aligned with its broader KYC Master Directions:

  • Complete due diligence: Aggregators must conduct comprehensive Customer Due Diligence (CDD) of all merchants, using officially valid documents, PAN, and other identifiers.

  • Simplified process for small merchants: A streamlined onboarding process may be applied when a merchant’s annual domestic turnover does not exceed ₹40 lakh, or where export turnover does not exceed ₹5 lakh. This involves verifying PAN, conducting Contact Point Verification (CPV), and collecting an officially valid document (OVD).

  • Background Verification and categorisation: Aggregators must validate the background of merchants, classify them under appropriate Merchant Category Codes (MCCs), and ensure that their names are accurately reflected in customer-facing transactions.

  • Monitoring: Onboarding is not a one-time exercise. PAs are responsible for continuous monitoring of merchants, including watchlist screening, tracking changes in legal status, and observing for adverse media.

  • Registration with FIU-IND: Non-bank aggregators must register with the Financial Intelligence Unit – India (FIU-IND) and adhere to reporting standards under the Prevention of Money Laundering Act.

  • Legacy merchants: All existing merchants must comply with these requirements by 31 December 2025. Merchants not verified by then must be re-onboarded from 1 January 2026.

Escrow Accounts And Settlement Requirements

The Directions mandate that all non-bank Payment Aggregators maintain merchant funds in escrow accounts with Scheduled Commercial Banks. For cross-border activity, separate accounts are required: an Inward Collection Account (InCA) for receipts from overseas customers and an Outward Collection Account (OCA) for payments made by Indian customers to overseas merchants. Funds relating to inward and outward transactions must be kept segregated.

Settlement Framework

  • Existing non-bank PAs must migrate to the escrow arrangement within two months of receiving RBI authorisation.

  • Credits and debits to the escrow account are restricted to transactions permitted explicitly under the Directions, ensuring that merchant funds are not diverted for unrelated purposes.

  • Interest may be earned only on the core portion of the escrow balance, calculated as the average of the lowest daily balances in each fortnight over the preceding 26 fortnights. This provision allows recognition of a stable minimum balance without enabling misuse of settlement float.

  • Following separate arrangements, escrow accounts must not be used for cash-on-delivery (COD) transactions.

Certification And Reporting

  • Quarterly: Payment Aggregators must obtain auditor certification confirming compliance with escrow guidelines.

  • Annually, the auditor and the escrow bank must certify adherence to RBI requirements.

Compliance And Reporting Obligations

Payment Aggregators are subject to extensive compliance and reporting requirements under the Directions.

  • Monthly: Aggregators must report transaction statistics to the Reserve Bank, covering volumes and values across different payment channels.

  • Quarterly: They must obtain an auditor’s certificate confirming compliance with escrow account operations and a certificate from the bank maintaining the escrow account on credits and debits.

  • Annual: Every aggregator must submit a net worth certificate, an information systems and cyber security audit report, and confirmation of compliance with the governance and operational provisions of the Directions.

  • Event-based: Any change in promoters, directors, or key managerial personnel must be communicated to the Reserve Bank, supported by a declaration confirming compliance with the fit-and-proper criteria.

How Can AuthBridge Streamline Your Compliance Under RBI’s New Directions?

Meeting RBI’s new master directions requires both robust governance structures and scalable verification infrastructure. AuthBridge’s solutions are aligned to support entities in implementing these requirements:

  • Merchant Onboarding And KYC/CDD
    RBI requires full customer due diligence, including PAN, CKYCR, OVD checks, and Contact Point Verification for merchants. AuthBridge enables this through automated identity verification APIs, digital address verification, and V-CIP for high-risk profiles.
  • Ongoing Monitoring And Due Diligence
    The Directions emphasise continuous monitoring of merchants, including adverse news screening and changes in legal status. AuthBridge provides automated monitoring tools and dynamic risk scoring, allowing compliance teams to act on early warning signals.
  • Duplicate and Mule Account Detection
    With Address Augmentation across 12–13 independent datasets (including NIDs and logistics service providers), AuthBridge helps identify inconsistencies, link identities across data points, and flag suspicious mule and duplicate accounts early.
  • AML And FIU-IND Reporting
    Non-bank aggregators must register with FIU-IND and comply with SAR/STR reporting. AuthBridge offers workflows that automate case detection and reporting, reducing the operational burden on compliance teams.
  • Skip Tracing for Dormant Accounts
    Dormant accounts present severe issues, particularly when registered email or phone contacts are unresponsive. AuthBridge’s Mobile-to-Address API with address scoring enables banks to trace customers through fresh, activity-based address signals, ensuring balances are credited to the rightful owner before closure.
  • Governance And Fit-And-Proper Checks
    RBI mandates promoters and directors to meet fit-and-proper criteria and requires risk management and customer protection policies. AuthBridge supports this with director background checks, conflict-of-interest screening, and governance-focused due diligence services.
Increased 2025 UPI Limits

New Increased UPI Transaction Limits 2025: Everything You Need To Know

Introduction

The National Payments Corporation of India (NPCI) has recently announced an update to the Unified Payments Interface (UPI) limits, which has a significant impact on how high-value digital payments are processed in India. Effective now, users can make Person-to-Merchant (P2M) transactions of up to ₹5 lakh per transaction, and a maximum of ₹10 lakh in total within 24 hours for specified categories. This update changes how UPI will handle large payments and has been designed to make digital transactions more efficient, secure, and accessible for users across various sectors.

Key Changes To UPI Transaction Limits

1. Per-Transaction Limit for P2M Transactions Increased to ₹5 Lakh

The single transaction limit for Person-to-Merchant (P2M) transactions has now been raised to ₹5 lakh in specified categories. Previously, the limit for such transactions was much lower, but this change enables businesses in specific industries to accept higher-value payments without relying on multiple smaller transactions. 

2. Daily Aggregate Limit Raised to ₹10 Lakh in Select Categories

In addition to the raised per-transaction limit, the daily aggregate limit for P2M transactions has been increased to ₹10 lakh within 24 hours for specific categories, including:

  • Insurance premiums
  • Capital markets
  • Travel
  • Collections
  • Government e-Marketplace (GeM)

This revision allows users to conduct more extensive daily transactions, supporting businesses that need to process large payments over a day. For instance, in the insurance sector, where large premium payments are common, companies can process these payments in a single day without requiring multiple smaller transactions.

3. P2P Transfer Limit Remains at ₹1 Lakh per Day

Despite the increase in transaction limits for P2M payments, the limit for Person-to-Person (P2P) transfers remains unchanged at ₹1 lakh per day. This helps maintain a clear distinction between personal transfers and commercial transactions, ensuring that high-value commercial transactions are subject to stricter conditions. On the contrary, personal transfers stay within a manageable limit.

4. Investment Payments in Capital Markets and Insurance Increased

For capital market investments and insurance premiums, the per-transaction limit has been raised from ₹2 lakh to ₹5 lakh, with a daily aggregate limit of ₹10 lakh. This will benefit investors, particularly those looking to make significant investments, by offering more room for digital transactions, eliminating the need to break down payments into multiple smaller ones.

5. GeM and Government Transactions Raise Transaction Limits

The Government e-Marketplace (GeM), which facilitates procurement by government departments, now has an increased transaction limit for payments such as tax payments, earnest money deposits, and other government-related transactions. Previously capped at ₹1 lakh, the per-transaction limit has now been increased to ₹5 lakh, simplifying and streamlining government transactions that often involve substantial sums.

6. Credit Card Bill Payments Now Higher

The transaction limit for credit card bill payments has also been raised to ₹5 lakh per transaction, with a daily cap of ₹6 lakh. This change offers more flexibility for consumers who need to make large credit card payments, whether for personal use or business expenses.

Increased UPI Limits 2025
Source: NPCI

Increased UPI Limit Benefits On Businesses And Consumers

A. Impact on Businesses

  1. Increased Flexibility for High-Value Transactions
    This update brings significant flexibility for businesses, especially those in the capital markets, insurance, travel, and e-commerce sectors. Businesses can now process higher-value transactions more easily without splitting payments into smaller amounts. This is particularly helpful for industries like insurance, where premiums can often exceed the previous limits.
  2. Faster and Smoother Payment Flow
    With the ability to accept higher-value transactions, businesses can offer smoother payment experiences to their customers. This reduces friction in the payment process, allowing businesses to close deals faster and improve cash flow.
  3. Simplified Compliance and Reporting
    The new limits provide an opportunity for businesses to streamline their compliance processes. With the ability to conduct more substantial transactions within a single window, companies can focus on fewer transactions, reducing the need for complex reporting and reconciliation tasks.

B. Impact on Consumers

  1. Increased Convenience for High-Value Transactions
    Consumers will find it easier to complete large payments in sectors like insurance and capital markets, where high-value transactions are the norm. With the higher limits, they no longer have to split payments into multiple parts, making the process more efficient and less time-consuming.
  2. Improved Payment Security
    The revised transaction limits are designed to accommodate large payments without compromising security. With verified merchants required for specified categories, the risk of fraud or error in high-value transactions is reduced.

How Authbridge Can Support Businesses With The New UPI Updates

As businesses adapt to these changes to UPI transaction limits, AuthBridge can help ensure that compliance, fraud prevention, and merchant verification processes are streamlined. 

1. Merchant Verification and KYC Services

For businesses handling larger payments, merchant verification becomes even more critical. AuthBridge’s merchant verification services, including Know Your Business (KYB) and KYC checks, help businesses deal with verified and trustworthy merchants. This is especially important as the scale of transactions increases in the insurance, capital markets, and e-commerce sectors.

2. Compliance with Regulatory Requirements

AuthBridge’s AML (Anti-Money Laundering) and KYC services ensure businesses comply with regulations while conducting large transactions. As transaction limits rise, the need for comprehensive background checks to verify the identity of merchants and customers becomes even more critical.

3. Fraud Prevention Tools

With higher-value transactions, the potential for fraud also increases. AuthBridge’s fraud prevention tools, such as UPI verification, address verification, and contact point verification (CPV) powered by DIGIPIN, ensure that merchants and consumers are thoroughly verified before engaging in large-value transactions. This helps businesses protect themselves from fraudulent transactions and reduce the risk of financial loss.

Conclusion

With verified merchants now eligible for larger transaction amounts, businesses in sectors such as insurance, capital markets, travel, and GeM will find it easier to process large payments without compromising security or efficiency. For businesses looking to take advantage of these changes, AuthBridge’s services can play a major role in ensuring that all necessary verification, compliance, and fraud prevention measures are in place.

Top-7-Customer-Onboarding-Solutions-In-India-blog-image

Top 7 Customer Onboarding Solutions In India

What Is Customer Onboarding?

Customer onboarding guides a new customer from the point of sign-up to the moment they see value in your product or service. Effective onboarding is critical in regulated sectors like banking, insurance, and fintech, including identity checks, document verification, and compliance with KYC and AML regulations.

Done well, onboarding builds trust, shortens time to value, and reduces drop-offs. Done poorly, it can cause frustration and churn before the relationship begins.

Key Points To Remember In Customer Onboarding

  • Compliance comes first – In India, customer onboarding must meet regulatory requirements like e-KYC, Video KYC, CKYC registry checks, AML, and sanctions screening.
  • Frictionless experience – Customers expect fast, digital-first experiences: pre-filled forms, mobile-friendly design, and minimal document re-submission.
  • Trust and securityLiveness detection, consent capture, and secure storage are essential to protect the business and the customer.
  • Time to value (TTV) – The sooner a customer experiences value, the more likely they are to stay. Automated workflows and guided onboarding reduce delays.
  • Analytics and tracking – Drop-off rates, completion times, and error rates must be measured to improve continually.

How To Choose Customer Onboarding Software In India

When evaluating platforms, businesses should consider the following:

  • Regulatory coverage
    Seek support for Aadhaar-based e-KYC (where applicable), PAN verification, GSTIN checks, Video KYC, and AML/sanctions screening.
  • Workflow flexibility
    Ensure the software can handle straight-through processing as well as exception handling. Project-style templates and client portals are often required.
  • Integration ecosystem
    A strong onboarding platform integrates with CRMs, core banking or insurance systems, payment gateways, and e-signing tools.
  • Scalability and security
    Cloud-native solutions with ISO or SOC certifications, data residency compliance, and strong encryption practices are critical.
  • Customer experience features
    Guided flows, multilingual support, mobile responsiveness, and automated reminders enhance adoption.
  • Commercial clarity
    Understand whether pricing is per API call, per user, or per project, and check for add-on costs like storage or premium connectors.

7 Best Customer Onboarding Solutions In India

Customer onboarding is no longer just a box-ticking exercise. It has become a critical differentiator for businesses in India, especially in regulated industries like banking, insurance, and fintech. Choosing the right onboarding platform can mean the difference between a seamless, compliant journey and one riddled with delays, drop-offs, and risks.

Below are seven of the best customer onboarding solutions available in India today, in no particular order:

1. AuthBridge

AuthBridge offers one of India’s most comprehensive onboarding platforms, designed to balance regulatory compliance with a smooth customer experience. The company combines digital identity verification, document management, due diligence, and automation at scale.

Key Capabilities:

  • Digital KYC & Video KYC (V-CIP):
    Real-time facial recognition, liveness detection, OCR, and geo-tagging. Video-based KYC is designed to cut turnaround times by up to 90% and reduce costs by as much as 70%.

  • AML & Risk Screening:
    Anti-Money Laundering checks, adverse media monitoring, and reputation screening through proprietary databases like Vault and Negative Image Search.

  • Third-Party Onboarding (OnboardX):
    A dedicated platform for onboarding vendors, distributors, gig workers, and other third parties with multi-channel initiation, progress monitoring, and due diligence powered by over a billion proprietary records.

  • Document Execution (SignDrive):
    Digital signing workflows that eliminate the friction of physical paperwork, with secure, auditable e-signatures.

  • Financial Data Intelligence:
    Bank Statement Analyser for automated classification of income, expenses, and potential fraud indicators, helping insurers and lenders speed up underwriting.

  • Insurance-Specific Accelerators:
    Tailored solutions for insurers, including real-time policyholder verification and Pre-Issuance Verification Calls (PIVC), with AI-led calls reducing PIVC turnaround times by up to 80%.

  • Integration & APIs:
    Plug-and-play APIs for PAN, Aadhaar DigiLocker, GSTIN and other verifications, plus integrations with HRMS, CRMs, and ERPs.

2. TrackWizz

TrackWizz focuses heavily on regulated financial sectors, offering an integrated suite for client lifecycle management.

Services Offered:

  • Central KYC (CKYC) submission and management.

  • AML and sanctions screening with transaction monitoring.

  • Automated onboarding workflows for high-net-worth and institutional clients.

  • Insider trading compliance and regulatory reporting (FATCA, CRS).

3. KYC Hub

KYC Hub is a global onboarding platform with solutions built for compliance-heavy markets, including India.

Services Offered:

  • Automated Digital KYC and Video KYC.

  • Perpetual KYC with ongoing risk assessment.

  • AML screening, fraud prevention, and dynamic risk scoring.

  • Document verification powered by AI and APIs.

  • Customisable workflows to adapt to business requirements.

4. Salesforce Financial Services Cloud

Salesforce provides a powerful onboarding module within its Financial Services Cloud, which is trusted globally and adapted for Indian institutions.

Services Offered:

  • Digital client onboarding with guided journeys.

  • Automated document collection and e-signatures.

  • CRM integration to unify customer data during onboarding.

  • Workflow automation for account origination and compliance checks.

5. Newgen Software

Newgen delivers AI-driven customer onboarding solutions designed for banks and financial institutions.

Services Offered:

  • End-to-end digital account opening (deposits and loans).

  • Video KYC for remote onboarding.

  • AI and ML-driven risk assessment for faster approvals.

  • Account maintenance automation, including re-KYC and updates.

6. OnRamp

OnRamp is built for businesses looking to provide structured and transparent onboarding experiences.

Services Offered:

  • A customer-facing portal for clear visibility of steps.

  • Internal project dashboards for teams to manage tasks and timelines.

  • Ready-to-use templates and playbooks to accelerate onboarding.

7. FlowForma

FlowForma is a no-code workflow automation tool that helps enterprises digitise their onboarding journeys.

Services Offered:

  • Customisable onboarding workflows with dynamic forms.

  • Deep integration with Microsoft 365 applications.

  • AI Copilot supports building and managing workflows.

  • Mobile-ready experiences for distributed teams.

Conclusion

For enterprises that value both compliance and customer experience, AuthBridge offers a proven, future-ready solution. Other platforms such as TrackWizz, KYC Hub, Salesforce, Newgen, OnRamp, and FlowForma also deliver strong capabilities, each excelling in specific domains. The choice ultimately depends on your industry, scale, and integration needs.

Businesses that adopt the proper solution now will win customer trust faster and build long-term resilience in an increasingly regulated market.

RBI FREE-AI Guidelines

RBI’s FREE-AI Framework: Key Highlights Summarised

RBI’s Push For Responsible AI In Financial Services

The Reserve Bank of India has released its Framework for Responsible and Ethical Enablement of AI (FREE-AI) at a time when the financial sector is moving rapidly from experimental deployments to mainstream adoption of artificial intelligence. For banks, insurers and non-banking financial companies, they now know that AI can no longer remain an ancillary tool. It is now central to the way institutions assess credit, monitor risks, and engage with customers, and it must be governed accordingly.

The framework lays down guiding principles and operational expectations that marry innovation with prudence. It acknowledges the efficiency and inclusion gains AI can unlock, while making clear that opacity, bias, and weak oversight could destabilise financial markets and corrode public trust. The RBI’s emphasis on board-level responsibility, structured model governance, and mandatory transparency obligations signals a regulatory shift, from permitting fragmented experimentation to demanding institution-wide accountability.

For the BFSI leadership, this is not merely a compliance update. It is a strategic inflexion point. Institutions that can integrate AI responsibly, embedding explainability, fairness and resilience into their models, stand to capture competitive advantage. Those who cannot may find themselves facing heightened supervisory scrutiny, reputational damage, and an erosion of customer confidence.

Opportunities Of AI In BFSI

For India’s financial sector, the RBI report is less about unveiling new possibilities and more about lending institutional weight to changes already underway. Artificial intelligence is no longer a speculative tool; it is shaping the way balance sheets are built, risks are priced, and customers are retained. The numbers are eye-catching; global estimates place potential banking productivity gains in the range of $200–340 billion a year, but the more telling developments are visible on the ground.

Take credit underwriting. Traditional scorecards that relied on income proofs and bureau history are being supplemented with data trails from GST filings, telecom usage, and even e-commerce behaviour. This is not simply innovation for its own sake. For lenders battling high acquisition costs and thin margins, alternate credit models mean access to new segments without compromising prudence. The inclusion dividend, bringing thin-file borrowers into the fold, is a by-product, though one with profound consequences for financial deepening.

Fraud detection is another front where AI is moving the needle. Global banks that have invested in AI-led validation tools report material reductions in false positives and payment rejections. In India, where digital transactions run into billions each month, even a modest improvement in accuracy translates into meaningful savings and, more importantly, sustained trust in digital channels.

Customer engagement is evolving as well. Multilingual voice bots, embedded in UPI or account aggregator frameworks, are starting to blur the lines between technology and financial literacy. The promise here is not just cost reduction through automation, but the creation of service models that feel accessible to a farmer in Vidarbha or a shopkeeper in Guwahati, clients who have historically been underserved by the formal system.

The report also nods to a larger structural opportunity: the alignment of AI with India’s digital public infrastructure. If Aadhaar and UPI represented the pipes of a new financial order, AI could well become the pressure valve, enabling real-time risk scoring, personalised nudges, and context-aware service delivery. For institutions, this is not a question of whether AI will matter, but how quickly they can adapt it to their existing frameworks without eroding safeguards.

Risks And Challenges Of AI Highlighted By RBI

If the opportunity side of AI feels expansive, the risks outlined by the RBI are equally sobering. The report makes it clear that unchecked adoption could destabilise both firms and markets. This is not rhetorical caution; the vulnerabilities are real and already visible.

The first is model risk. AI systems often behave like black boxes, powerful in prediction, opaque in logic. A credit model that misclassifies a borrower, or a fraud system that repeatedly flags genuine payments, is not merely a technical glitch. It can mean reputational damage, regulatory penalties, and erosion of customer confidence. The RBI rightly notes that bias in training data or poorly calibrated algorithms can hard-wire discrimination into financial processes.

Operational risks follow close behind. AI reduces human error in many processes, but it also amplifies the cost of mistakes when they occur at scale. A single point of failure in a real-time payments environment could cascade through millions of transactions. Market stability itself is not immune: history remembers the “flash crash” of 2010, and algorithmic misfires in a more AI-saturated environment could prove even more destabilising.

Third-party dependency adds another layer. Most Indian banks and NBFCs lean heavily on external vendors for AI models, cloud services, and integration layers. That concentration risk leaves institutions exposed to interruptions, contractual blind spots, and even geopolitical vulnerabilities. The report is blunt on this: outsourcing AI without iron-clad governance is an open invitation to risk.

Cybersecurity risks are no less pressing. AI is a double-edged sword here: it strengthens defence, but it also lowers the cost and sophistication threshold for attackers. Deepfake fraud, AI-engineered phishing, and data-poisoning attacks are already hitting financial institutions globally. For a sector built on trust, the reputational consequences of one high-profile breach could be devastating.

And then there is the risk of inertia. The RBI points out that institutions which resist AI adoption may find themselves doubly vulnerable, unable to counter AI-driven fraud and left behind by more agile competitors. In a sector where margins are tightening, standing still is itself a risk strategy.

The FREE-AI Framework Explained

The RBI’s Committee has attempted something unusual in Indian regulatory practice: to codify a philosophy for AI adoption rather than issue narrow compliance checklists. The FREE-AI framework — short for Framework for Responsible and Ethical Enablement of AI — is built around seven “Sutras” and six strategic pillars. Taken together, they are intended to guide how regulated entities design, deploy and govern artificial intelligence.

At the heart of the framework lie the Seven Sutras — principles that set the moral and operational compass:

  • Trust is the foundation. AI systems must inspire confidence not only in their outcomes but also in their process.

  • People first. Human oversight and consumer interest cannot be sacrificed at the altar of efficiency.

  • Innovation over restraint. The regulator signals it does not want to stifle progress, provided safeguards are in place.

  • Fairness and equity. Models must avoid systemic bias that could exclude vulnerable groups.

  • Accountability. Responsibility must sit with identifiable decision-makers, not be diffused into algorithms.

  • Understandable by design. Black-box systems that cannot be explained will not withstand scrutiny.

  • Safety, resilience and sustainability. AI must be stress-tested for shocks, cyber threats and long-term viability.

To move these ideals into practice, the report maps them against six strategic pillars. Three are enablers of innovation, infrastructure, policy, and capacity, and three are risk mitigators, governance, protection, and assurance. Under these sit 26 specific recommendations: from the creation of shared infrastructure and financial-sector sandboxes to board-approved AI policies, mandatory audits, and consumer disclosure requirements.

What is notable is the tone of the framework. It does not treat risk controls as an afterthought but places them on equal footing with innovation. A tolerant approach is suggested for low-risk AI use cases, particularly those that advance financial inclusion, but higher-stakes deployments will be subject to tighter scrutiny. 

AI Adoption And Use Cases: What RBI’s Surveys Show

The RBI conducted two surveys in 2025 — one by the Department of Supervision covering 612 regulated entities and another by the FinTech Department covering 76 institutions with 55 CTO/CDO follow-ups. Together, they capture nearly 90% of the sector’s assets, making them a credible reflection of the state of play.

Adoption Levels

  • Overall adoption is thin: only 20.80% (127 of 612) entities reported using or building AI solutions.

  • Banks: larger commercial banks are more active, but adoption still centres on limited functions.

  • NBFCs: 27% of 171 surveyed have live or developing use cases.

  • Urban Co-operative Banks (UCBs): Tier-1 UCBs — none; Tier-2 and Tier-3 report usage in single digits.

  • ARCs: none reported adoption.

This confirms that AI penetration is still largely confined to bigger balance sheets with stronger tech capabilities.

Complexity Of Models

Most reported applications use rule-based systems or moderate machine learning models. More advanced architectures, deep learning, neural networks, or generative stacks, are rare in production. The comfort zone remains models that can be explained and slotted into legacy IT frameworks without destabilising compliance.

Infrastructure Choices

  • 35% of entities using AI host models on public cloud.

  • The balance prefers private cloud, hybrid, or on-premise deployments, reflecting ongoing caution around data control, privacy, and outsourcing risks.

Use Cases (583 Applications Reported)

The RBI categorised 583 distinct applications across the surveyed entities:

  • Customer support15.60%

  • Credit underwriting13.70%

  • Sales and marketing11.80%

  • Cybersecurity and fraud detection10.60%

  • Other emerging use cases – internal administration, coding assistants, HR workflows, and compliance automation are rising but not yet mainstream.

This distribution illustrates a preference for low-to-medium risk operational functions rather than core balance-sheet exposures.

Generative AI

Interest in generative AI is widespread but tentative. In the FinTech Department’s sample of 76, 67% of institutions said they were exploring at least one generative use case. Yet these were overwhelmingly internal pilots: knowledge assistants, report drafting, code generation. Customer-facing deployments remain scarce due to unease about data sensitivity, unpredictable outputs, and the absence of clear explainability mechanisms.

Governance And Control Mechanisms

Perhaps the most telling findings relate to safeguards. Adoption often happens without adequate governance:

  • Interpretability tools (e.g., SHAP, LIME): only 15% reported use.

  • Audit logs: 18%.

  • Bias and fairness validation: 35%, and mostly pre-deployment rather than continuous.

  • Human-in-the-loop oversight: 28%.

  • Bias mitigation protocols: 10%.

  • Periodic audits: 14%.

  • Model retraining: 37%, but ad hoc in many cases.

  • Drift monitoring: 21%.

  • Real-time performance monitoring: 14%.

Reading The Numbers

The survey findings point to a sector that is experimenting but not yet institutionalising AI. Adoption is selective, shallow, and uneven across segments. The concentration of activity in larger banks and NBFCs highlights both the opportunity and the risk: systemic players are experimenting at scale without consistent controls, while smaller institutions risk being left behind entirely.

Inclusion, Digital Public Infrastructure And Sector-Specific Models

The report is unequivocal about AI’s role in widening formal finance without diluting prudence. It points to alternate data—utility payments, mobile usage patterns, GST filings and e-commerce behaviour—as credible signals for underwriting thin-file or new-to-credit borrowers, particularly MSMEs and first-time users. This is not an argument for laxity; it is an argument for better signals, especially where bureau history is sparse.

Inclusion, however, is not only about scorecards. The report emphasises multilingual access and low-friction channels that meet users where they are. AI-powered chatbots for guidance and grievance redress, and voice-enabled banking in regional languages for the illiterate or semi-literate, are explicitly flagged as near-term, high-impact levers. The intent is straightforward: reduce the cognitive and linguistic barriers that keep millions from using formal services confidently.

A second plank is the convergence with Digital Public Infrastructure (DPI). India’s rails—Aadhaar, UPI and the Account Aggregator framework—are treated as the substrate on which AI can enable personalisation and real-time decisioning at a population scale. The report is explicit: conversational AI embedded into UPI, KYC strengthened through AI in tandem with Aadhaar, and context-aware service via Account Aggregator are practical upgrades, not distant aspirations. To avoid concentration advantages, the report also moots AI models offered as public goods so that smaller and regional players can participate meaningfully.

On the modelling side, the committee pushes beyond generic LLM enthusiasm and asks a pointed question: Should India develop indigenous, sector-specific foundation models for finance? The rationale is not industrial policy for its own sake; it is risk and fit. A model that does not reflect India’s linguistic and operational diversity risks urban-centric bias and poor performance in real-world Indian contexts. General-purpose models, trained largely on English and Western corpora, will not reliably handle India’s multilingual and domain-specific needs.

Accordingly, the report outlines two practical directions. First, Small Language Models (SLMs): narrow, task-bound models that are faster to train, cheaper to run, and easier to govern, particularly when fine-tuned from open-weight bases for specific financial tasks. Second, “Trinity” models built on Language-Task-Domain combinations—e.g., Marathi + Credit-risk FAQs + MSME finance, or Hindi + Regulatory summarisation + Rural microcredit—to ensure regulatory alignment, multilingual inclusion, and operational relevance while keeping compute budgets realistic. The report notes these systems can be built quickly with moderate resources—a pragmatic route for Indian institutions.

Finally, the report widens the lens to the near-horizon. Autonomous agent patterns (using protocols like MCP and agent-to-agent messaging) could shift finance from task automation to decision automation—for instance, an SME’s agent negotiating with multiple lender-agents for real-time offers and execution. The paper also flags privacy-enhancing technologies and federated learning for collaborative training without raw-data exchange—important for inclusion use cases where data fragmentation and privacy risks otherwise stall progress. 

Barriers And Governance Gaps

The surveys surface a consistent set of impediments that explain why adoption is shallow outside a handful of large institutions. Chief among them are the talent gap, high implementation costs, patchy access to quality training data, limited computing capacity, and legal uncertainty. Smaller players, already stretched on capex and compliance, asked for low-cost, secure environments to experiment before committing to production.

Beyond economics, the risk picture is clear. Institutions flagged data privacy, cybersecurity, governance shortcomings, and reputational exposure as the principal concerns. Many remain wary of pushing advanced models into live workflows because of opacity and unpredictability—and the governance demands that follow. The implication is obvious: the more consequential the decision (credit, fraud, claims), the higher the bar for control and audit.

On internal readiness, the gap is structural. Only about one-third of respondents—mostly large public-sector and private banks—reported any Board-level framework for AI oversight. Only about one-fourth said they have formal processes to mitigate AI-related incidents. In many institutions, AI risks are loosely folded into generic product approval routines rather than being managed through a dedicated risk vertical. Training and staff awareness are thin, limiting the organisation’s ability to handle evolving risks.

Data governance is fragmented. Most entities lack a dedicated policy for training AI models. Key lifecycle functions—data sourcing, preprocessing, bias detection and mitigation, privacy, storage and security—are scattered across IT and cybersecurity policies. Data lineage and traceability systems, essential for accountability and reliable models, are missing in many legacy estates. Access to domain-specific, high-quality structured data remains a persistent pain point.

Even where AI is in use, safeguards are uneven. Of the 127 adopters, only 15% reported using interpretability tools; 18% maintain audit logs; 35% perform bias/fairness validation, mostly at build-time rather than in production. Human-in-the-loop is present in 28%, but bias-mitigation protocols sit at 10%, and regular audits at 14%. Periodic retraining is reported by 37%, drift monitoring by 21%, and real-time performance monitoring by just 14%—figures that underscore why supervisors are pressing for stronger model lifecycle controls.

Capacity building is patchy. A few institutions have launched training programmes, industry partnerships and centres of excellence, but talent remains scarce and efforts are fragmented. Respondents also emphasised the need to raise customer awareness so that AI-enabled services are better understood and trusted at the front line.

Finally, the demand from the industry is explicit: 85% of deep-dive respondents asked for a formal regulatory framework, with guidance on privacy, algorithmic transparency, bias mitigation, use of external LLMs, cross-border data flows, and a proportional, risk-based approach that allows safe innovation while tightening controls where stakes are high. 

Regulatory Trajectory: Proportionality, Outsourcing, Consumer Disclosures

RBI’s stance remains technology-agnostic but expects AI to be governed within the existing lattice of IT, cyber, digital lending and outsourcing rules, with incremental AI-specific clarifications layered on top where needed.

Proportionality (what to expect): the Committee signals a consolidated issuance to stitch AI-specific expectations—disclosures, vendor due diligence on AI risks, and cyber safeguards—into current regulations, rather than creating a separate AI rulebook.

Outsourcing (clarity on scope):

  • If an RE embeds a third-party AI model inside its own process, treat it as internal use—the RE’s standard governance and risk controls apply.

  • If the RE outsources a service and the vendor uses AI to deliver it, that is outsourcing; contracts should explicitly cover AI-specific governance, risk mitigation, accountability and data confidentiality, including subcontractors.

Consumer protection (minimums): customers should know when they are dealing with AI, have a means to challenge AI-led outcomes, and access robust grievance redress. These expectations flow from existing consumer circulars and are to be read as applicable to AI.

Digital lending (auditability): AI-based credit assessments must be auditable, not black boxes; data collection must be minimal and consent-bound, including for DLAs/LSPs.

Cyber/IT (extend controls to AI): apply access control, audit trails, vulnerability assessment and monitoring to AI stacks, mindful of data poisoning and adversarial attacks.

In short: expect a risk-based consolidation of AI expectations across the existing rule set, explicit outsourcing language for vendor-delivered AI services, plain-English disclosures to customers, and auditable model decisions for high-stakes use cases.

Operational Safeguards: Policy, Monitoring, And Incident Reporting

RBI’s framework expects AI to be governed as a first-class risk. That means formal policy, live monitoring, clear fallbacks, and an incident regime that can withstand supervisory scrutiny.

Board-Approved AI Policy. Institutions should maintain a single, actionable policy that: inventories AI use cases and risk-tiers them; fixes roles and accountability up to Board/committee level; codifies the model lifecycle (design, data sourcing, validation, approval, change control, retirement); sets minimum documentation standards; and defines training for senior management through to frontline teams. The policy should also spell out third-party controls (due diligence, SLAs, subcontractor visibility, right to audit) and the cadence for periodic review.

Data And Documentation. Keep an auditable trail of what went into and came out of each model: data sources and legal basis (consent/minimisation), preprocessing steps, versioned training sets, feature lineage, hyperparameters, and inference-time logs where feasible. Retention should align with existing data and consumer regulations.

Pre-Deployment Testing. High-impact models should face structured validation: representativeness checks on datasets; back-testing and challenger comparisons; fairness/bias testing on protected cohorts; stability tests across segments and time; and adverse scenario tests (including attacks such as prompt injection, data poisoning, adversarial inputs, inversion/distillation where relevant). Approval gates and sign-offs should be recorded.

Production Monitoring. Treat AI as “always in observation”:

  • Performance and error-rate tracking with thresholds for alerts and human review.

  • Drift detection on data and outcomes; defined triggers for retraining or rollback.

  • Continuous fairness checks where decisions affect customer access, pricing, or claims.

  • Access controls, audit trails and tamper-evident logs for models and data.

  • Change management for any update to data, code, thresholds, or prompts—including roll-back plans.

Human-In-The-Loop And Explainability. For high-stakes calls (credit, claims, fraud flags, adverse onboarding outcomes), ensure a human override path and an explanation that can be shown to customers and auditors. Record when and why overrides occur.

Business Continuity For AI. Define safe-fail modes: a kill-switch, degraded service (e.g., revert to prior approved model or rules), and manual operations where required. Map these to specific processes (payments, lending, onboarding) so continuity steps are executable under time pressure.

Vendor Oversight (When AI Is In The Service Chain). Contracts should name AI-specific obligations: model governance standards, data segregation and confidentiality, geo/sovereignty constraints, transparency on sub-processors, audit rights, security posture, and incident notification timelines with evidence packs. Where a third-party model is embedded inside your own process, apply your internal controls as if it were built in-house.

Customer Safeguards. Provide plain-English disclosure when an interaction or decision is AI-enabled, outline how customers can contest outcomes, and route challenges to trained staff. Keep redress timelines and decision records auditable.

Incident Reporting (Annexure Lens). Prepare to log and report AI incidents using a consistent template. At minimum capture: use case and model details; trigger and time of detection; impacted customers/systems/financials; severity; root cause; immediate containment; longer-term remediation and prevention; and named contacts. Link incident thresholds to your monitoring triggers and BCP so escalation is automatic rather than ad hoc.

Enablers: Innovation Sandbox And Sector Collaboration

The report does not view responsible AI as a compliance burden alone; it proposes concrete enablers to help institutions adopt safely and at speed.

AI Innovation Sandbox. A supervised, time-bound environment where banks, NBFCs and fintech partners can test AI use cases with real-world constraints and clear guardrails. The intent is to de-risk early pilots, surface model and data issues before scale, and document learnings in a format that can be audited and reused.

Shared Infrastructure And Public Goods. Sector access to curated datasets, evaluation suites, and compute on fair terms—especially for smaller and regional players. The emphasis is on domain-relevant benchmarks (credit, fraud, AML, KYC) and lightweight, explainable models that can run economically and be governed by existing risk functions.

Sector-Specific Models And Tooling. Practical focus on small language models and narrow task models tuned to Indian finance (languages, products, processes). Tooling includes bias and drift tests, red-team playbooks for adversarial inputs, and out-of-the-box explainers suitable for customer-facing decisions.

Standard Templates And Policy Kits. Model cards, data lineage registers, change-control logs, and incident report formats that align with supervisory expectations. These reduce time to compliance and create comparable evidence across institutions.

Capacity And Knowledge-Sharing. Board and senior management briefings, communities of practice for CRO/CTO teams, and joint exercises on model failures and recovery. The goal is consistent judgement across firms on when to escalate, when to roll back, and how to evidence decisions.

Vendor And Outsourcing Hygiene. Clearer procurement language for AI components—governance standards, transparency on sub-processors, audit rights, geo/sovereignty constraints, and incident-notification obligations—so external capabilities can be used without importing opaque risks.

Alignment With National AI Safety Efforts. Testing, assurance, and benchmarking to be interoperable with the emerging national safety and standards ecosystem, so results from one setting can inform supervisory reviews across the sector.

How AuthBridge Helps BFSI Align With FREE-AI

RBI’s framework sets clear expectations: evidence, accountability, explainability, and recoverability. AuthBridge’s stack lines up well against that bar, helping institutions shift from pilots to governed production without losing speed.

What The Framework Expects vs What You Can Operationalise With AuthBridge

FREE-AI Expectation

What BFSI Needs In Practice

How AuthBridge Helps

Clear governance and auditability

A single source of truth for AI/KYC decisions; model/use-case inventory; change logs; evidence on tap for internal audit and supervisory review

Board-ready policy and register templates; decision records with time-stamped artefacts; exportable audit packs across KYC, onboarding and screening flows

Explainable outcomes for high-stakes calls

Human-review paths, reasons you can show a customer or examiner, and an override trail

Decision explainers for onboarding flags, AML hits and risk scores; maker-checker workflows; override capture with rationale

Data minimisation and consent

Verifiable consent, least-data processing, and traceable lineage from source to decision

Consent capture embedded in Video-KYC and digital forms; field-level lineage and retention controls aligned to your policy

Continuous monitoring and bias/drift checks

Live quality gates, alerting, retraining triggers, and back-testing

Performance dashboards, drift alerts, threshold tuning; challenger vs champion comparisons where applicable

Resilience and safe-fail

Fallbacks when models or sources misbehave; continuity during outages

Kill-switch to revert to approved rulesets; degraded modes and manual paths for onboarding and verification

Outsourcing hygiene

Contracts that name AI obligations; visibility into sub-processors; audit rights

Standard clauses, evidence packs, and vendor reporting formats that match RBI’s emphasis on accountability

Consumer safeguards

Disclosure when AI is in play; channels to contest outcomes; fast redress

Plain-English notices in flows; case escalation to trained reviewers; decision journals to support responses

Conclusion

The RBI’s FREE-AI framework marks a decisive shift in how artificial intelligence will be viewed in Indian finance: not as an optional add-on but as a regulated capability that demands the same rigour as credit, capital or liquidity management. For BFSI institutions, the task is twofold—embrace the efficiency and reach AI enables, while embedding the safeguards that preserve trust and systemic stability. Those that move early will not only stay compliant but will also earn the confidence of customers and regulators alike. With AuthBridge’s AI-driven verification, diligence and compliance solutions, the sector can operationalise these expectations today—turning regulatory alignment into a competitive advantage.

Tenant Verification in Co-living space

India’s Co-living Boom & The Need For Tenant Verification

If you’ve landed on this page, you’re likely one of these people:

  1. A co-living owner anxious about new laws and eager to scale safely
  2. An aspiring tenant (a student, working professional, or single woman), trying to explore the best accommodation options and find a new home in the city that’s both stylish and secure.
  3. Or maybe you’re an investor peering into the co-living boom, keen to bet on spaces that won’t collapse under legal or safety pressure.

Co-Living Has Now Gotten Mainstream

Walk through Bengaluru’s HSR Layout, Gurugram’s CyberHub, or Mumbai’s Bandra-Kurla Complex. Most of the faces you see, whether they are students, coders, experienced professionals, designers, or management trainees, did not grow up in this area. They’ve moved for work, for study, for ambition, for autonomy. 

This is the engine behind the explosion of co-living in India. Once a boutique idea, co-living is valued at $40 billion in 2025. Nearly half of the co-living residents are professionals; the rest are students, women, and digital nomads, all wanting not just an address, but a way of life.

Why PGs And Flats Are Losing Their Edge

Let’s look at 2025 and how things have changed: PGs (paying guest accommodations) and old-school rentals no longer feel as welcoming as they once did.
You arrive in a new city. You meet a broker and pay a massive deposit. You sign a run-of-the-mill, four-page contract with a landlord whose temperament you can’t anticipate. Wi-Fi, if it exists, is patchy. Cleaning is ad hoc. Bills you thought were settled suddenly aren’t. If anything goes wrong, a leak, a theft, a dispute, you’re stuck with a WhatsApp group and crossed fingers.
For women, the series of events is even trickier: safety, privacy, and support can feel like luxuries rather than guarantees.

Co-living feels like turning the tables altogether. Managed by professional teams, with digital payments, 24/7 support, and curated social calendars, it’s meant to feel effortless, modern, and transparent. The promise is more than a room; it’s a sense of belonging, with Wi-Fi, gym, lounge, cleaning, and repairs included in an honest, all-in rent.

Co-Living vs. PGs, By The Numbers

A shared PG room in a Big city might cost ₹5,000 – ₹12,000 a month, which may seem cheaper on paper, but it rarely includes Wi-Fi, cleaning, or reliable repairs. Single rooms or premium PGs can cost ₹15,000 – ₹30,000, with hidden costs, slow response times, and a landlord who may never answer the phone.
Co-living, by contrast, typically charges ₹9,000–₹18,000 for a shared room, and upwards for a private studio. What you get, though, is no surprise bills, digital onboarding, dedicated maintenance, and a team that’s responsible for your peace of mind.
Is it more expensive? Sometimes, on paper. Is it a better value? Almost always. But the real difference is who you’re sharing your space with, and how you know you’re safe.

Safety, Security, And The Role Of Tenant Verification

Let’s be honest – the amenities in the world don’t matter if you can’t trust your neighbours.

For young students, especially women, moving to these cities for the first time brings in unspoken anxiety. For parents, sending their children into the unknown makes things even tougher.
A few years ago, most rental operators didn’t bother much with background checks. Police verification was a formality if it happened at all.
But as co-living has gone corporate, as occupancy rates have soared, and as investors have poured in significant investments, safety and verification have become the price of entry.

What Does Tenant Verification Look Like Today?

  1. It starts with digital onboarding: prospective residents submit government ID, address, and sometimes employment or student proof through a secure portal.
  2. Next, police verification: the operator submits these details through the city’s or state’s official system for a criminal background check. No clearance, no keys.
  3. Then, digital contracts: everything, rules, rent, rights, responsibilities, is clear, signed digitally, and easily accessible.
  4. Finally, record-keeping: every document, every clearance, every police receipt is archived, so if authorities ask for proof, it’s there in minutes.


This is about peace of mind for residents, owners, and investors. But not every operator gets this right. Some still rely on paper or skip checks for “regulars,” or ignore renewals.

The Legal Consequences Of Not Verifying Tenants

The Bharatiya Nyaya Sanhita (BNS), Section 223, makes it a punishable offence for any owner, including co-living operators, to withhold or skip police-verified background checks.
Goa’s 10,000 rupees-per-unverified-tenant penalty was a serious step on this front. However, the real story is across India’s big cities. Pune, Chandigarh, Dehradun, Bengaluru, and Mumbai authorities are cracking down, levying mass fines, filing FIRs, and even blacklisting non-compliant landlords.

Why? Because a single bad tenant can have severe repercussions on many, including the industry’s reputation. Goa’s crackdown came after a tragic crime involving an unvetted tenant. Pune and Chandigarh have prosecuted non-compliant operators. Dehradun police fined nearly four hundred property owners in a single sweep.

Best Practices For Tenant Verification

If you’re running a co-living brand, here’s the playbook for 2025:

  • Digitise everything: Paper is your enemy. Use secure portals for document collection, police verification, and digital contracts.
  • Partner wisely: Solutions like AuthBridge are designed for this ecosystem, scalable, law-aware, fraud-proof, and audit-ready.
  • Educate your team: Everyone from the front desk to the regional manager must know the drill.
  • Communicate with residents: Make verification a badge of pride and explain why it matters.
  • Prepare for audits: Keep logs, batch reports, and digital proof in order. When the police come knocking, you want to be the operator with everything filed, not the one scrambling for last month’s paperwork.

Best Practices For Tenants Looking For Co-Living Spaces

If you’re looking for a new home, here’s your checklist:

  • Ask about verification: Is everyone who lives here police-verified? Can you show me your process?
  • Look for digital onboarding: If you’re filling out paper forms, red flag. AuthBridge manages everything online.
  • Check the contract: Is it digital, clear, and easy to access?
  • Safety for women: Seek spaces with female-only floors or wings, CCTV, and responsive support.
  • Community matters: The best operators foster real community- events, shared spaces, a sense of belonging.
  • Support: Can you reach management day or night?
    If any of this feels fudged, walk away. There are too many good options now to settle for less.

Best Practices For Investors: Due Diligence

If you’re thinking of investing in co-living, your questions should go beyond occupancy rates and cap tables.

  • Ask for compliance logs: How are tenants verified? Are background checks policed and documented?
  • Audit a sample: Randomly pick a few leases, are the digital contracts, police clearances, and KYC all present and correct?
  • Know the red flags: Paper documentation, patchy verification, vague responses about audits or city enforcement.

The brands that win today are the ones that treat verification as a core strength, not a bureaucratic chore.

Conclusion

India’s co-living boom is about more than beds and amenities. It’s about reimagining urban trust for residents, operators, and investors alike.

For residents, robust tenant verification means safety, clarity, and a home you can believe in. For operators, it’s the foundation of scale, compliance, and investor confidence. For investors, it’s the marker of a brand built to last.

In a country where city life is being reinvented by the month, the co-living spaces that thrive will be the ones that make verification visible, seamless, and central to their promise, not just an afterthought or a legal headache.

CPV in Banking

Importance Of Contact Point Verification (CPV) In Banking

Introduction To Contact Point Verification In Banking

Contact Point Verification (CPV) is a key step in banking operations, focused on confirming that the communication channels provided by customers. This includes checking for active and authentic mobile numbers, email addresses or postal addresses. By validating these contact points, banks make sure that important alerts such as transaction notifications, OTPs for Internet banking and statements reach the right recipient without delay or interception.

A strong CPV process strengthens security across multiple touchpoints. For Internet-banking log-ins and fund transfers, an OTP sent to a verified number or e-mail ensures that only the genuine customer can approve high-value transactions. In customer onboarding, instant confirmation of email addresses prevents mistyped or fraudulent entries from entering the system. Even routine communications, like sending monthly statements or promotional offers, benefit from CPV. Banks avoid the costs and reputational risks of bounced emails or messages sent to inactive numbers.

Moreover, CPV contributes to operational efficiency. Automated checks, such as carrier lookups to verify number status or SMTP pings to test e-mail server availability, can be completed in minutes. This significantly reduces manual follow-up. When automated channels fail, voice-call or letter-dispatch methods ensure no customer is left unverified. This multi-channel approach enhances the customer experience by minimising onboarding friction. It also reduces the resource burden on call centres and branch staff.

Core Methods And Best Practices For CPV In Banking

In banking, Contact Point Verification relies on a multi-channel strategy to ensure that customer communication details are both valid and in active use. Automated mechanisms, such as carrier lookups and SMTP handshakes, quickly filter out invalid entries. One-time passwords (OTPs) sent via SMS or e-mail provide a near-instant confirmation of possession. While interactive voice response (IVR) calls serve as a secondary digital protection. Where digital channels fail, a manual agent call or postal confirmation letter bridges the gap, ensuring that even customers in low-connectivity regions can complete verification.

A hallmark of an effective CPV programme is its fallback logic: if an SMS OTP isn’t delivered, the system should automatically trigger an IVR prompt or e-mail link without manual intervention. This continuity reduces customer effort and cuts down support overhead. Moreover, all verification attempts and outcomes should be logged in real time to create an audit trail capable of withstanding regulatory scrutiny and forensic review.

Banks aiming for excellence in CPV adopt several best practices:

  • Time-Bound Automated Checks: Carrier and SMTP checks are executed within seconds, flagging invalid entries before consuming OTP resources.

  • Dynamic Fallback Rules: The system should escalate only once per failed channel, e.g., one SMS attempt, one IVR attempt, then route persistent failures to a human agent for resolution.

  • Consent Management: Before dispatching any OTP or call, explicit customer consent must be captured and stored by data protection regulations.

  • Periodic Re-Verification: High-risk or dormant accounts should undergo CPV at defined intervals, typically every 12–24 months, to ensure contact information remains current.

Method

Check Performed

Data Captured

Carrier Lookup

Is the mobile number active and valid?

Live/deactivated status, network operator

SMTP Handshake

Does the e-mail server accept incoming connections?

Bounce responses, server latency

SMS OTP

Does the user receive and submit the code correctly?

OTP send time, validation success/failure

IVR Prompt

Does the automated call connect and confirm user?

Call logs, DTMF or voice confirmation result

Manual Agent Call

Can a human agent reach and verify the contact?

Agent notes, final disposition

Postal Letter Dispatch

Does physical mail reach the stated address?

Delivery confirmation or returned mail flag

Regulatory Framework And RBI Guidelines For CPV

The Reserve Bank of India embeds Contact Point Verification into its KYC and CDD norms across these key scenarios:

  • Periodic KYC Updation: When a customer updates only their postal address, the new address must be verified through positive confirmation within two months, by means such as an address-verification letter, contact point verification, deliverables, etc.

  • Sole Proprietorship Documentary Exception: If a sole proprietor cannot furnish two activity-proof documents, the bank may accept one, but only after it undertakes contact point verification … to establish the existence of such firm and satisfy itself that the business activity has been verified from the address of the proprietary concern.

  • Enhanced Due Diligence for Remote Onboarding: Before allowing operations in a non-face-to-face account, banks must confirm the customer’s current address via positive confirmation methods, with CPV listed alongside letters and other deliverables. 

Practical Use Cases And Benefits Of CPV In Banking

Contact Point Verification delivers multiple advantages across a wide range of banking operations, enhancing security, efficiency and compliance.

1. Secure Onboarding and Account Activation

When a new customer applies for a savings or current account, whether in branch or via digital channels, CPV prevents fraudulent or erroneous enrolments. By confirming mobile numbers and e-mail addresses in real time, banks ensure that onboarding credentials (such as Internet-banking log-ins or debit-card PINs) reach bona fide applicants only. This not only reduces the incidence of “dead” or fraudulent accounts but also diminishes manual rework.

2. Safe Transaction Authorisations

High-value fund transfers and bill payments depend on one-time passwords delivered to verified channels. CPV underpins transaction security by ensuring that OTPs cannot be intercepted via stale or spoofed numbers. 

3. Dormancy Reactivation and Periodic Re-Verification

Many customers fall into dormancy, typically after 12 – 24 months of inactivity, raising the risk of unauthorised reactivation. CPV applied at the point of dormancy reactivation (sending OTPs or verification calls) confirms that contact details remain under the customer’s control. 

4. Regulatory Audit and Compliance Reporting

CPV generates a rich audit trail: every carrier-lookup response, OTP dispatch, IVR call log and agent-confirmation note is timestamped and stored. This comprehensive record helps banks demonstrate compliance with KYC Directions and Data Protection norms during inspections. 

Conclusion

In a nutshell, Contact Point Verification is what keeps banking both safe and straightforward: by quickly checking that your phone number, email or address is yours, whether through a simple OTP, a quick automated call or a brief manual check, banks stop fraudsters in their tracks, avoid endless back-and-forth during sign-up, and stay on the right side of RBI rules. It’s a small step that makes a big difference, building customer trust and setting the stage for banking that’s as seamless as it is secure.

How to avoid deepfake scam user onboarding

5 Ways To Avoid Deepfake Scam In Customer Onboarding

Introduction

Deepfake technology has emerged as a significant threat to digital security, particularly during customer onboarding. Fraudsters increasingly use this technology to impersonate genuine customers, bypassing traditional identity verification systems. In this blog, we’ll explore how deepfake scams are impacting customer onboarding and the best strategies to counter these threats using advanced detection technologies, process optimisations, and security best practices.

What Are Deepfake Scams?

Understanding Deepfake Technology

Deepfakes are a type of synthetic media generated using artificial intelligence and machine learning models, particularly Generative Adversarial Networks (GANs). These technologies allow fraudsters to create incredibly realistic fake media, videos, images, and even audio that mimic real people with near 100% accuracy.

In customer onboarding, deepfakes are used to deceive identity verification systems by creating fake videos of individuals that closely resemble their real counterparts. With advancements in AI, these deepfakes are becoming harder to detect, making it easier for fraudsters to bypass traditional verification mechanisms.

How Deepfake Scams Target Customer Onboarding

The primary vulnerability lies in digital onboarding systems that rely heavily on video-based verification, such as those used in Know Your Customer (KYC) processes. Fraudsters use deepfake technology to create convincing fake videos, often bypassing facial recognition, liveness detection, or other biometric checks.

Deepfake scams pose a significant threat in India, where digital onboarding processes are becoming increasingly important, especially with services like Aadhaar linking. Fraudsters could create fake identities, using manipulated videos to bypass security systems, leading to fraudulent account creation, financial theft, and important data breaches.

The Risks Of Deepfake Scams In Customer Onboarding

Financial Losses

Deepfake scams directly expose businesses to financial risks. Fraudsters who get access to accounts via deepfake manipulation can perform illegal activities such as money laundering, fraudulent loan applications, or unauthorised transactions. In India, the rise in digital banking and mobile payments makes financial fraud using deepfakes a serious concern. Financial institutions, e-commerce platforms, and fintech companies could face major financial losses if their security systems aren’t up to the challenge. Moreover, Indian banks and financial institutions face strict KYC/AML regulations, making it even more important to prevent fraud. 

Reputational Damage

The reputational risk is one of the most damaging repercussions of deepfake scams. If a company allows deepfake videos to bypass their onboarding system, it will damage the trust customers place in their brand. As digital onboarding is becoming the norm, especially in sectors like banking, insurance, and e-commerce, the public perception of a company’s security protocols plays a critical role in retaining customers.

For instance, if a fintech company in India allows deepfake fraud to occur, the public backlash could be severe. News of such incidents can go viral, causing a loss of customer confidence, reduced user engagement, and a negative impact on the company’s stock value or market position.

Legal And Compliance Risks

India has stringent laws around data privacy and financial fraud. The Personal Data Protection Act aims to regulate how businesses collect and handle personal data. Companies operating in sectors like banking and e-commerce must also adhere to KYC and AML regulations. Deepfake scams can bypass these identity checks, resulting in a breach of compliance obligations. If deepfake fraud occurs and is linked to an institution’s failure to comply with KYC regulations, the company could face lawsuits, regulatory scrutiny, and hefty penalties from the RBI.

Increased Operational Costs

As deepfake scams become more prevalent, businesses will need to invest more in advanced detection technologies, such as AI-powered deepfake detection systems and liveness detection tools. These technologies, while effective, can be expensive to implement and maintain, increasing operational costs for companies.

Moreover, businesses will need to allocate resources for manual reviews of flagged cases, which could further increase the workload on customer service and fraud prevention teams. This additional overhead can detract from the overall efficiency of the onboarding process.

Intellectual Property Theft And Identity Fraud

Deepfake technology allows fraudsters to impersonate not only customers but also high-level executives or key stakeholders in the company. In a sophisticated scam, fraudsters could create fake videos of executives to perform social engineering attacks, such as requesting confidential information or authorising financial transfers.

For example, an employee could be tricked into revealing sensitive company data after receiving a video message from a CEO or senior executive that appears entirely legitimate. In India, where digital platforms are heavily used for business communication, these types of scams can lead to intellectual property theft and severe corporate security breaches.

Impact On Customer Experience

Customer experience is pivotal in any industry, but particularly in sectors like fintech, banking, and e-commerce, where trust and security are integral to success. Deepfake scams that bypass customer verification can frustrate legitimate customers, leading to lengthy account verification processes or even account freezes, as companies scramble to address the fraud.

In India, where digital literacy is still growing in certain regions, these complications can deter users from completing their onboarding or even cause them to abandon the process altogether. The negative user experience could reduce conversion rates, leading to lost business and revenue.

5 Tips To Prevent Deepfake Scams In Customer Onboarding

1. Implement Video KYC with Liveness Detection

Using video KYC along with liveness detection is the first line of defence against deepfake scams. Liveness detection ensures that customers are physically present during the onboarding process, making it harder for scammers to use deepfake videos or images.

2. Use AI-Powered Deepfake Detection Tools

AI-based deepfake detection tools can automatically scan video content for discrepancies, such as unnatural lighting, facial movement irregularities, or mismatched audio. Tools like Sensity AI and Deepware Scanner are designed to detect deepfake videos and flag them for further review.

3. Multi-Factor Authentication (MFA)

Implement multi-factor authentication (MFA) in addition to video KYC. Using two or more forms of verification, like facial recognition, OTPs, and fingerprint scanning, adds another layer of security, making it much harder for fraudsters to bypass the system using deepfake technology.

4. Cross-Platform User Verification

By cross-referencing data submitted during onboarding with other trusted platforms, companies can verify the authenticity of the person. This cross-checking process adds an extra layer of validation and is essential for preventing deepfake fraud in India, where government IDs are widely used for verification.

5. Collaborate With An Industry-Leading Customer Onboarding Service Provider

Working with a provider like AuthBridge means that businesses benefit from the expertise and ongoing support of an experienced team. They will help implement, maintain, and update the latest technologies designed to prevent deepfake fraud, offering best practices and assistance to navigate any challenges that arise during the onboarding process. This partnership ensures that businesses remain proactive in adapting to emerging security threats, offering customers a seamless and secure experience.

Utilising Advanced Technology For Enhanced Security

AI And Blockchain For Secure Onboarding

Combining AI and blockchain can provide an extremely effective and secure onboarding process. While AI helps detect deepfake fraud through facial recognition and video analysis, blockchain can ensure that the entire verification process is recorded in an immutable and transparent ledger. This combination makes it incredibly difficult for fraudsters to manipulate records.

In India, where Aadhaar-based identity systems are frequently used for verification, blockchain can serve as an additional layer of security by providing a tamper-proof audit trail of the customer onboarding process. Blockchain technology ensures that every action taken during the onboarding process is securely recorded, reducing the chances of fraudulent manipulation.

  • AI detects fraudulent activities by analysing visual and auditory cues.
  • Blockchain records all actions, making it nearly impossible to alter records.

Real-Time Video Analysis

Real-time video analysis tools can detect deepfake fraud as it happens. Using machine learning models, these tools continuously scan video data for inconsistencies, such as facial movements or lighting issues that deepfakes commonly exhibit. With the rapid advancements in computer vision and AI, these tools can now detect deepfakes in real-time during video-based onboarding processes.

This process helps businesses instantly flag suspicious activities without needing to manually review the entire video. This is particularly crucial in sectors where time-sensitive decisions are made, such as banking, lending, and insurance in India, where real-time processing is critical to maintain operational efficiency.

Legal And Compliance Considerations For Preventing Deepfake Scams

Ensuring Regulatory Compliance

In India, businesses must comply with various data protection and financial regulations. Companies are legally obligated to protect their customers’ data, and preventing fraud is a key component of this responsibility.

Deepfake scams not only expose businesses to fraud but also to compliance risks. If a company allows deepfake fraud to slip through its onboarding system, it could face severe legal consequences for breaching privacy laws or failing to meet regulatory requirements. Regulatory bodies such as the Reserve Bank of India (RBI) and Securities and Exchange Board of India (SEBI) impose strict penalties for non-compliance, which can include fines and even the suspension of operations.

To stay compliant:

  • Regular audits should be performed to ensure deepfake detection measures are robust and up to industry standards.
  • Businesses should continuously update their systems in line with the evolving regulatory landscape.

Maintaining Data Privacy

Data privacy is a significant concern when handling sensitive customer information. Deepfake detection tools, especially those powered by AI, should be carefully evaluated to ensure that they do not violate data privacy regulations such as GDPR or India’s PDPB. These tools must be integrated in a way that respects user consent and ensures that data is processed securely.

  • User Consent: Ensure customers are informed about the use of AI in the verification process.
  • Data Protection: Implement encryption and secure storage methods to protect data from breaches.

Conclusion

As deepfake technology advances, businesses must take proactive steps to secure their customer onboarding processes from fraud. The risks of financial loss, reputational damage, and regulatory penalties are significant, especially in India, where digital transformation is rapidly evolving. By integrating AI-powered detection tools, multi-factor authentication, blockchain for audit trails, and real-time video analysis, companies can safeguard against deepfake scams, ensuring both compliance and customer trust. Implementing these strategies now is essential to stay ahead of emerging threats and protect your business and customers from fraud.

QCommerce FDA case

Ensuring Regulatory Compliance In The Quick Commerce Space

The fast-growing quick-commerce industry, characterised by ultra-fast deliveries from dark stores, has undoubtedly moulded the e-commerce space. However, as with all these sectors, it is not immune to scrutiny from regulatory bodies. In recent months, the Maharashtra Food and Drug Administration (FDA) has ramped up inspections of quick-commerce facilities, uncovering significant non-compliance issues, particularly in food safety.

Government inspections have revealed a concerning pattern of operational failures. Key violations have included the lack of proper food business licenses, expired stock being stored next to fresh items, and unhygienic storage conditions. In some cases, inspections found that dark stores, small, unstaffed facilities designed for rapid order fulfilment, had failed to meet even the most basic health and safety standards required by food safety regulations. 

With such serious violations surfacing, the FDA has immediately suspended operations at affected facilities. Any failure to meet compliance requirements could result in severe penalties, business shutdowns, and long-term reputational damage.

The Issue At Hand: Regulatory Crackdown In Quick-Commerce

The quick-commerce sector, known for its promise of ultra-fast deliveries, has faced increased scrutiny from regulatory bodies in recent weeks. In a recent incident, the Maharashtra Food and Drug Administration (FDA) took immediate action after discovering significant lapses in the food safety practices at a dark store in Pune. The store, which operated as part of a well-known quick-commerce platform, was found to violate multiple food safety and operational regulations.

Following a surprise inspection, the FDA uncovered significant findings. The store lacked the necessary food business license, a key requirement for any facility engaged in the sale or distribution of food. In addition to this, inspectors discovered several health and safety violations, including the storage of expired products alongside fresh stock. The facility’s storage conditions were deemed unhygienic, and in some areas, the lack of proper temperature control posed a risk to food safety.

These findings were a direct violation of the Food Safety and Standards Authority of India (FSSAI) guidelines, which regulate food handling and storage in India. The FDA’s response was swift, suspending the food business license of the dark store and halting its operations. This move by the FDA has significant implications, not only for the brand involved but for the entire quick-commerce sector, which is under increasing pressure to adhere to food safety and operational regulations.

How To Ensure Compliance In Quick-Commerce Operations

The quick-commerce industry, due to its fast-paced nature, requires rigorous attention to operational and regulatory compliance. To avoid incidents like the recent suspension of a dark store in Pune, companies in the sector must implement strong measures to ensure they meet all food safety and regulatory requirements. This can be accomplished by adopting comprehensive verification processes and continuous monitoring systems.

1. Secure the Necessary Licenses

The first and most fundamental step in ensuring compliance is obtaining the necessary licenses and certifications. As revealed in this case, operating without an FSSAI license can lead to severe consequences, including suspension and forced closures. Every business handling food products, even in a quick-commerce setting, must secure proper licensing from the relevant food safety authorities. This includes:

  • FSSAI License: Required for any food business operator involved in the storage, distribution, or sale of food products.

  • Other Sector-Specific Licenses: Depending on the nature of the products, businesses may require additional certifications (e.g., GSTIN, import/export licenses).

Maintaining up-to-date and valid licenses is critical, as non-compliance in this area can lead to immediate shutdowns by regulatory authorities.

2. Implement Hygienic Storage and Handling Practices

The inspection in Pune revealed several lapses in hygiene and food storage practices, including food items found on the floor and improper pest control. These violations not only breach regulatory standards but also directly compromise consumer safety. To ensure compliance, quick-commerce companies must establish and enforce the following practices:

  • Proper Storage Systems: Food products should be stored in clean, temperature-controlled environments that meet FSSAI guidelines. This includes using calibrated cold storage units and ensuring that food is stored on clean, non-dusty surfaces.

  • Regular Cleaning and Sanitisation: Dark stores and warehouses must be regularly cleaned, with a clear protocol for waste disposal and pest control.

  • Health and Safety Standards: Personnel handling food should undergo regular health checks, including mandatory medical examinations, to ensure they are fit for food handling.

3. Adhere to Regulatory Standards and Guidelines

Each quick-commerce operation must comply with industry regulations outlined by authorities such as FSSAI, the Maharashtra FDA, and other regulatory bodies. These include general hygiene standards, as stipulated in FSSAI Schedule 4, which sets out the necessary sanitary and operational practices for food businesses. Compliance with these guidelines ensures that operations meet both local and national standards, preventing violations such as those uncovered during the FDA’s recent inspection.

4. Conduct Regular Internal Audits and Inspections

Continuous monitoring is vital for ensuring that dark stores and fulfilment centres remain compliant with safety protocols. Routine internal audits and inspections help identify potential risks and ensure the business operates within regulatory frameworks. Audits should cover:

  • Product quality checks: Ensuring that expired or damaged stock is regularly identified and discarded.
  • Temperature control checks: Verifying that cold storage units are functioning properly and are calibrated as per industry standards.
  • Pest control and cleanliness: Regular inspections to maintain hygiene levels and prevent contamination.

AuthBridge’s Solutions For Preventing Non-Compliance In Quick-Commerce

AuthBridge offers a comprehensive suite of verification solutions designed to help businesses stay compliant, mitigate risks, and protect their reputation.

1. Warehouse Audits and Risk Mitigation

AuthBridge conducts thorough warehouse audits to proactively identify operational lapses, including:

  • Inventory Reconciliation: Verifying stock against records to identify discrepancies.
  • Security & Access Review: Assessing access controls and CCTV effectiveness.
  • Compliance & Process Adherence: Ensuring adherence to SOPs for inbound, storage, and outbound activities.
  • Loss Prevention: Strengthening measures to deter theft and tampering.

These audits reduce risks of non-compliance, financial loss, and reputational damage.

2. Vendor Onboarding and KYC Solutions

We provide comprehensive vendor onboarding solutions that ensure compliance by:

  • KYC Verification: KYC, powered by Digital Identity checks, to verify vendor legitimacy.
  • FSSAI License Verification: Ensuring vendors hold the required licenses.
  • Food Safety Document Verification: Digitally verifying essential food safety documents.

These checks ensure your vendor ecosystem is compliant and trustworthy.

3. Continuous Compliance Monitoring

Ongoing compliance is essential. AuthBridge’s monitoring services include:

  • Automated Alerts: Flagging expired licenses, overdue audits, and potential compliance breaches.
  • Regular Audits: Conducting periodic inspections to maintain operational standards.

This monitoring keeps businesses ahead of compliance issues.

4. Third-Party Auditing and Risk Assessment

We help businesses ensure their third-party vendors meet compliance standards by offering:

  • Third-Party Vendor Audits: Verifying licenses and conducting background checks.
  • Risk Scoring: Using data to assess vendor risk and performance.
What is CPV

What Is Contact Point Verification (CPV)? All You Need To Know

The process of Contact Point Verification (CPV) has become a key step in financial and lending processes, especially as digital transactions and remote onboarding become more common. CPV involves verifying the authenticity of phone numbers, email addresses, and physical addresses provided by borrowers or customers.

The importance of CPV lies in its ability to reduce fraud, enhance credit risk assessment, and ensure compliance with regulatory standards. Today, where identity theft and synthetic fraud are increasingly sophisticated, verifying contact points helps financial institutions maintain the integrity of their operations and build trust with clients.

This blog talks about the role of CPV in credit decision-making, fraud prevention, and regulatory adherence. It also explores why lenders and financial institutions must prioritise CPV in their due diligence frameworks.

What Is Contact Point Verification (CPV) And Why Is CPV Important?

Contact Point Verification (CPV) is the process of confirming that the contact details, primarily phone numbers, email addresses, and physical addresses, provided by an individual or entity are valid and accessible. While it may seem straightforward, CPV is key to due diligence in financial services and lending.

In practical terms, CPV involves cross-checking contact information through automated systems and manual verification methods such as one-time passwords (OTPs), calls, or emails. The goal is to ensure that the communication channels through which lenders or businesses engage with their clients are legitimate and operational.

The significance of CPV has grown in recent years due to the rise of digital lending platforms and remote onboarding, where physical verification is limited. Incorrect or falsified contact points can undermine credit assessments, lead to poor recovery rates, and increase exposure to fraud.

Beyond improving communication efficiency, CPV also strengthens compliance with regulatory frameworks that mandate thorough customer identification and verification. It serves as a frontline defence against synthetic identities and fraudulent loan applications, which often use fake or stolen contact information.

How CPV Helps Creditworthiness And Lending Decisions

In credit risk management, reliable data is the backbone of sound decision-making. Contact Point Verification (CPV) plays an important role in ensuring that the information lenders base their assessments on is accurate and trustworthy. When contact details such as phone numbers and email addresses are verified, lenders can establish a direct line of communication with borrowers, which is important throughout the loan lifecycle, from application to repayment.

Verified contact points help lenders assess the authenticity of the applicant and reduce the risk of fraud. For instance, an unverifiable phone number or email may signal a higher likelihood of synthetic identity fraud or loan stacking, both of which contribute to increased default risk. CPV also enables better monitoring of borrowers, facilitating timely reminders, restructuring discussions, or recovery efforts in case of defaults.

Moreover, financial institutions increasingly rely on digital footprints and communication patterns as part of alternative credit scoring models, especially for borrowers with limited credit history. Verified contact points provide reliable data inputs for such models, enhancing credit decision accuracy.

From a regulatory standpoint, CPV aligns with Know Your Customer (KYC) and Anti-Money Laundering (AML) requirements, reinforcing lenders’ compliance posture. Regulators expect institutions to maintain robust verification protocols to prevent fraud and financial crime, making CPV a mandatory element in many credit origination workflows.

Hence, Contact Point Verification strengthens credit risk frameworks by ensuring data integrity, enabling effective borrower engagement, and supporting regulatory compliance, ultimately leading to more informed lending decisions and healthier loan portfolios.

How CPV Prevents Fraud And Compliance Risks

Fraud continues to pose a significant threat to financial institutions, with identity theft, synthetic identities, and phishing scams becoming increasingly sophisticated. Contact Point Verification (CPV) serves as a defence mechanism against these risks by ensuring that the communication channels linked to borrowers or customers are genuine and accessible.

Financial fraudsters often rely on falsified or temporary contact information to mask their identities and exploit vulnerabilities in onboarding processes. CPV disrupts such attempts by validating phone numbers and email addresses through methods such as OTP authentication, live call verifications, and cross-referencing with trusted databases. 

In addition, CPV enhances compliance with regulatory mandates. The Reserve Bank of India (RBI), among other regulators globally, has emphasised the need for rigorous KYC and AML checks to mitigate financial crimes. Verifying contact points is an integral component of these checks, helping institutions meet regulatory standards and avoid penalties.

Beyond fraud and compliance, CPV also improves operational efficiency by reducing failed communications and bounce rates in recovery and servicing processes. This has a direct impact on the cost and effectiveness of collections and customer service teams.

Contact Point Verification: Real-Life Use Cases

Contact Point Verification (CPV) plays a decisive role across various financial and lending scenarios, often acting as a key difference in making a sound credit decision and a costly error.

Digital Lending Platforms

Digital lending platforms have surged in India over the last few years. These platforms rely heavily on remote onboarding, where physical verification of documents and identities is limited or absent. CPV becomes essential to validate that the applicant’s phone number and email address are genuine and accessible. A verified contact point allows lenders to maintain communication throughout the loan lifecycle, from disbursal to repayment, and to respond quickly to potential red flags such as delayed payments or defaults.

Retail Banking Sector

In the retail banking sector, CPV supports fraud prevention by detecting inconsistencies early. For instance, if a borrower’s contact details cannot be verified or are linked to multiple accounts suspiciously, it raises immediate concerns about identity theft or synthetic identities. Banks use CPV as part of their layered verification process to flag such anomalies and initiate deeper investigations.

SME Credit Underwriting Services

CPV is equally critical in credit underwriting for small and medium enterprises (SMEs), where traditional credit history may be scarce or unavailable. Validated contact points enable lenders to reach out for additional documentation or clarification efficiently, reducing the turnaround time for loan approvals and improving the accuracy of credit assessments.

Collection And Recovery Operations

Furthermore, CPV is used extensively in collections and recovery operations. Confirmed contact information ensures that reminder calls, emails, and notices reach the borrower promptly, increasing the likelihood of repayment. In cases of default, verified contact points are crucial for successful recovery efforts, minimising non-performing assets (NPAs).

The Economic Impact Of Contact Point Verification On Businesses And Consumers

CPV holds significant economic implications for both financial institutions and their customers. At its core, CPV enhances the efficiency and reliability of credit markets by reducing information asymmetry.

  1. For businesses, especially lenders and fintech companies, accurate contact information translates into lower default rates and reduced operational costs. By verifying phone numbers and email addresses upfront, institutions can filter out high-risk applicants engaging in fraudulent activities or identity misrepresentation. This directly lowers the incidence of non-performing assets (NPAs), which can severely impact profitability and capital adequacy ratios.
  2. Moreover, verified contact points facilitate smoother communication throughout the credit lifecycle. This leads to improved customer engagement, timely repayments, and more effective recovery processes. Consequently, institutions benefit from higher portfolio quality and greater operational efficiency.
  3. From a broader economic perspective, CPV contributes to financial inclusion by enabling lenders to extend credit with greater confidence to underserved segments. Particularly in India, where many borrowers have limited credit history, reliable contact verification supports alternative credit assessment models that use communication data as proxies for creditworthiness. This can accelerate credit availability to MSMEs, first-time borrowers, and gig economy workers, fostering economic growth.
  4. Consumers, too, gain from CPV as it helps protect them against fraud, identity theft, and predatory lending practices. It enhances trust in financial service providers and improves the overall customer experience by ensuring transparent and secure communication.

In summary, robust CPV not only strengthens individual institutions’ risk profiles but also bolsters the health and inclusiveness of the financial ecosystem, contributing to sustainable economic development.

What’s Next For Contact Point Verification

As digital transformation accelerates across financial services, Contact Point Verification (CPV) is evolving beyond traditional checks to incorporate advanced technologies and data analytics. The future of CPV lies in leveraging artificial intelligence (AI), machine learning, and real-time data integration to deliver faster, more accurate, and scalable verification solutions.

AI-powered systems can analyse vast datasets to detect anomalies and predict the authenticity of contact points with greater precision. For example, machine learning models assess communication patterns, device fingerprints, and historical data to flag suspicious phone numbers or email addresses automatically. This proactive approach helps pre-empt fraud attempts before they escalate.

Integration with broader identity verification frameworks, such as biometrics and digital KYC platforms, is becoming increasingly common. CPV will no longer operate in isolation but as a critical component within multi-layered authentication systems, enhancing overall security and compliance.

Moreover, the expansion of mobile and internet penetration in emerging markets is driving innovation in verification methods. Instantaneous OTP-based validations, geo-location tagging, and social media data corroboration are gaining traction to ensure contact information reflects real, accessible individuals.

In conclusion, Institutions that invest in next-generation CPV technologies stand to benefit from reduced fraud risk, improved customer trust, and a competitive edge in an increasingly digital marketplace.

Conclusion

Contact Point Verification stands as a vital safeguard that goes far beyond simple data checks. By ensuring the authenticity and accessibility of contact details, CPV strengthens credit assessments, mitigates fraud risks, and upholds regulatory compliance. For lenders and financial institutions aiming to build resilient portfolios and foster trust, integrating robust CPV processes is no longer optional—it is essential. As technology advances, embracing innovative verification methods will be key to staying ahead in a rapidly evolving market and securing the foundation of trustworthy financial relationships.

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The most noteworthy aspects of our collaboration has been the ability to seamlessly onboard partners from all corners of India, for which our TAT has been reduced from multiple weeks to a few hours now.

- Mr. Satyasiva Sundar Ruutray
Vice President, F&A Commercial,
Greenlam

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