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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 support – 15.60%
Credit underwriting – 13.70%
Sales and marketing – 11.80%
Cybersecurity and fraud detection – 10.60%
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.

By Abhinandan, 1 dayAugust 27, 2025 ago

Background Checks

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

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

A co-living owner anxious about new laws and eager to scale safely
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.
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?

It starts with digital onboarding: prospective residents submit government ID, address, and sometimes employment or student proof through a secure portal.
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.
Then, digital contracts: everything, rules, rent, rights, responsibilities, is clear, signed digitally, and easily accessible.
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.

By Abhinandan, 1 monthJuly 29, 2025 ago

BFSI

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.

By Abhinandan, 2 monthsJuly 4, 2025 ago

How to avoid deepfake scam user onboarding

Background Checks

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.

By Abhinandan, 2 monthsJune 16, 2025 ago

Background Checks

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.

By Abhinandan, 3 monthsJune 13, 2025 ago

Background Checks

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.

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.
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.
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.
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.

By Abhinandan, 3 monthsJune 9, 2025 ago

Blogs

How Warehouse Ops Verification Ensures Quick Commerce Compliance

On June 1, 2025, the Maharashtra Food and Drug Administration (FDA) took a major step in suspending the food business license of a well-known quick-commerce platform operating in Mumbai. This action followed a comprehensive inspection of its Dharavi warehouse, where inspectors discovered a series of serious violations. Among the most concerning findings were fungal contamination on consumable products, expired items stored next to fresh stock, and poorly maintained cold storage conditions, each of which posed a direct threat to consumer safety.

These lapses showcase a significant breach of consumer trust. In the customer-driven and super-fast sector of quick-commerce, the repercussions of such negligence can be severe. The suspension of the license is just one of the immediate repercussions, but the long-term damage to the platform’s brand reputation is also concerning. This scandal is a pressing reminder of why businesses must prioritise compliance and consumer safety, not only as a legal obligation but as a basis of their operational integrity.

Unfortunately, incidents like these are not isolated. As the e-commerce and quick-commerce sectors continue to grow, the challenge of maintaining rigorous standards becomes more complex. While regulatory bodies play a key role in enforcing these standards, the responsibility for safeguarding against such fraud lies equally with the businesses themselves. The failure to conduct thorough due diligence, implement effective verification processes, and maintain high operational standards can quickly lead to catastrophic outcomes for both businesses and consumers.

The Impact Of Quick-Commerce Scandals On Brand Reputation And Consumer Trust

The Maharashtra FDA’s decision to revoke the quick-commerce platform’s license after discovering fungal growth on food items and expired products in unhygienic storage conditions highlights a key weakness in the industry. A breach of consumer trust, especially in a sector where convenience and safety are non-negotiable, can lead to lasting reputational damage that no amount of marketing or customer service recovery can easily fix. Once consumer confidence is lost, the path to regaining that trust is laden with challenges.

The impact of this incident goes beyond the company in question. E-commerce platforms, particularly those dealing with perishable FMCG, must acknowledge the fact that their operational standards are under constant scrutiny, and any failure to adhere to stringent safety protocols can result in a loss of market share, legal consequences, and a sharp decline in consumer loyalty.

How Thorough Warehouse Operations Verification Can Prevent Fraud

The risks of not implementing a comprehensive verification process are quite detrimental, as the recent scandal in Mumbai has shown. Fortunately, e-commerce platforms can take proactive steps to minimise these risks by incorporating thorough and multi-layered verification practices that address all areas of concern.

Key Areas of Verification

Compliance with Regulatory Standards: Ensure that all sellers and warehouses of Food Business Operators (FBO) are legally registered and have the necessary licences to operate. This includes validating:
- GSTIN (Goods and Services Tax Identification Number)
- CIN (Corporate Identification Number)
- FSSAI (Food Safety and Standards Authority of India) certification for food-business operators
- Valid business address verification
Financial Health: Evaluate the FBO financial stability by:
- Credit Score Verification
- Bank Statement Validation
- Payment History Checks
Background Checks: Assess the FBO’s employees’ history to uncover any potential risks by conducting:
- Criminal Background Checks
- Employment History Verification

Ongoing Monitoring

Verification doesn’t end with the initial check. Continuous monitoring is crucial for maintaining a secure marketplace. Regularly track and evaluate warehouse operators to ensure that they uphold safety and compliance standards. Some tools to aid ongoing monitoring include:

Automated Alerts based on sales patterns and customer reviews
Returns and Disputes Analysis to identify potential red flags
Regular Audits to check for adherence to health and safety standards

By employing these comprehensive measures, e-commerce platforms can ensure that fraudulent or non-compliant sellers are filtered out before they can cause harm. Preventing fraud and ensuring operational integrity goes beyond initial verification; it requires ongoing diligence.

AuthBridge’s Comprehensive Verification Solutions For E-Commerce

At AuthBridge, we understand the complexities of running a secure, compliant, and consumer-friendly marketplace. Our suite of verification solutions is designed to provide e-commerce platforms with the tools they need to perform comprehensive checks on their sellers and ensure that only legitimate, trustworthy businesses make it onto their platform.

Key Verification Services for E-Commerce:

KYC (Know Your Customer) Solutions: Our KYC solutions are designed to quickly and efficiently verify the identity of sellers. We offer digital identity verification using government-issued IDs, ensuring that all sellers are who they claim to be.
GST and PAN Verification: AuthBridge’s tools help verify GSTIN and PAN details to ensure that sellers are registered with the correct tax authorities and compliant with India’s tax regulations.
Business Information Verification: We provide detailed reports on a business’s legal status, financial health, and operational history. This includes verification of:
- CIN (Corporate Identification Number)
- Company Registration
- FSSAI Certification (for FBO warehouse operators)
Criminal Background Screening: We conduct comprehensive background checks on FBOs and their key personnel to ensure they have no criminal records or legal issues that could jeopardise the safety and trust of the platform.
Address and Location Verification: Our solutions also include verifying the physical addresses of FBOs, ensuring that products are sourced from reliable, compliant, and traceable locations.

Technology-Driven Verification

At AuthBridge, we leverage advanced technologies like AI, machine learning, and facial recognition to streamline the verification process and enhance accuracy:

AI-Powered Document Verification: Our automated solutions use AI to validate documents, ensuring that they are authentic and meet regulatory standards.
Facial Recognition and Liveness Detection: To enhance security, we offer facial recognition technology that matches users with their official identification documents. This also includes liveness detection to prevent spoofing attempts during remote verifications.
Automated Risk Scoring: Our platform uses machine learning algorithms to assign a risk score to sellers based on their compliance and past performance, helping e-commerce platforms make informed decisions quickly.

Continuous Monitoring and Compliance

Verification doesn’t stop after the onboarding process. E-commerce platforms must continuously monitor their sellers to ensure they maintain compliance with safety, quality, and regulatory standards. AuthBridge provides ongoing monitoring solutions that help businesses track seller activities and flag any unusual patterns or violations. This proactive approach reduces the risk of fraud and ensures that platforms remain compliant with ever-changing regulations.

Conclusion

The recent incident in Mumbai highlights the pressing need for e-commerce platforms to prioritise comprehensive warehouse operations verification. With the increasing risks of fraud and regulatory scrutiny, platforms must adopt rigorous verification processes to safeguard their reputation, ensure consumer trust, and remain compliant. At AuthBridge, our advanced verification solutions provide businesses with the tools needed to prevent fraud, protect customers, and build a secure, trustworthy marketplace.

By Abhinandan, 3 monthsJune 4, 2025 ago

BFSI

Redo KYC Before June 30: FIU-IND’s Mandate

Introduction

The Financial Intelligence Unit-India (FIU-IND) has recently issued a notification that could change the compliance environment for cryptocurrency exchanges operating in India. In alignment with the Prevention of Money Laundering Act (PMLA), the FIU has mandated that all crypto exchanges must redo Know Your Customer (KYC) procedures for their users before June 30, 2025.

This directive highlights a larger regulatory push to ensure that Virtual Digital Asset (VDA) platforms implement robust identity verification mechanisms and manage financial risks effectively.

What FIU’s Notification Means For Crypto Exchanges

Under the new guidelines:

Exchanges must update user details comprehensively.
Fresh KYC must be conducted for accounts older than 18 months.
Enhanced due diligence is required for high-risk accounts, demanding additional documentation and information.

This move signals the government’s intent to tighten oversight on crypto transactions and ensure platforms are not used for money laundering, fraud, or other illicit activities.

The Increasing Importance Of Seamless Digital KYC

The need for quick, reliable, and compliant KYC processes has never been more pressing. Crypto exchanges must rethink their onboarding and verification processes to meet these stringent demands without compromising user experience.

Traditional manual KYC methods are time-consuming, error-prone, and costly. Digital verification solutions, powered by advanced APIs and real-time data validation, offer a scalable and secure alternative.

At AuthBridge, we have been at the forefront of enabling enterprises to achieve faster, safer, and compliant identity verification across industries, and the crypto sector is no exception.

By integrating AuthBridge’s verification solutions, exchanges can not only comply with the FIU’s directives but also build greater trust with users and regulators alike.

Conclusion: Compliance As A Competitive Advantage

As India sharpens its regulatory frameworks around cryptocurrencies, compliance will no longer be a back-end function — it will become a core competitive differentiator.

Exchanges that invest early in AI-powered, API-first verification platforms like AuthBridge’s will be better positioned to scale sustainably, avoid penalties, and foster greater confidence among users and investors.

At AuthBridge, we remain committed to partnering with organisations to help them stay ahead of regulatory changes with innovative, reliable, and secure digital verification technologies.

By Siddharth, 4 monthsApril 29, 2025 ago

Background Checks

New Aadhaar App Beta Version: Key Features, How To Download

In an age where digital services are omnipresent, security and efficiency in identity verification have never been more crucial. Over a billion Indians rely on the Aadhaar system for their digital identity, yet the process of authentication has remained filled with complexities and concerns around privacy. The new Aadhaar app, currently undergoing beta testing, promises to change this narrative.

This new Aadhaar app is designed to give Aadhaar number holders more control over their data. With this app, users can share only the information needed for specific services, ensuring complete privacy. The app enables digital verification and data sharing through a requesting application or by scanning a QR code, eliminating the need for physical photocopies.

A standout feature of the app is its integration of Aadhaar Face Authentication, which has quickly gained popularity and now handles over 15 crore transactions per month across various sectors.

The Key Features Of The New Aadhaar Mobile App

Facial Recognition

At the heart of the new Aadhaar app is the integration of facial recognition technology. This innovation allows users to authenticate their identity without the need for physical Aadhaar cards or even a fingerprint scan. With a simple face scan, users can verify their identity within seconds, making the entire process far quicker and more reliable.

Unlike traditional methods of verification, where documents can be forged or tampered with, facial recognition ensures that the person presenting their Aadhaar details is indeed the rightful owner of the identity. This is particularly crucial in combating identity theft and fraud, both of which have become growing concerns in a digital-first world.

QR Code-Based Authentication

For those looking for an even simpler method, the new Aadhaar app allows users to generate a dynamic QR code, which can be scanned by businesses, service providers, or government agencies. This QR code links directly to the user’s Aadhaar details and ensures a seamless authentication process without the need for physical documents. Whether at a retail counter or a government office, this feature speeds up the verification process, reducing waiting times and enhancing user experience.

The shift from paper-based verification to QR codes also marks a significant step towards reducing physical contact, a critical consideration in the post-pandemic world. Moreover, QR code-based authentication helps avoid issues such as data entry errors, which are common in manual verification methods.

Enhanced Privacy Controls

One of the primary concerns surrounding digital identity systems has always been privacy. The new Aadhaar app addresses this head-on by giving users control over what information they wish to share. With the app, individuals can choose to disclose only the essential details needed for verification, rather than handing over their entire Aadhaar data. This ensures that privacy is preserved and the risk of data misuse is minimised.

Additionally, the app’s reliance on biometric authentication—namely, facial recognition and QR codes—helps to ensure that sensitive data is not easily accessible to unauthorised parties. In a country like India, where data privacy laws are still evolving, this level of control could serve as a critical safeguard for millions of users.

Currently, the app is being released to a select group of early adopters, including all registered participants of the Aadhaar Samvaad event, where this update was showcased. UIDAI plans to expand access based on feedback from users and ecosystem partners.

Why This New Aadhaar Update Is Huge?

Streamlines the Verification Process

India’s digital transformation hinges on its ability to verify identities quickly and securely. The new Aadhaar app, by incorporating facial recognition and QR codes, simplifies what has traditionally been a cumbersome process. Whether applying for a loan, booking a train ticket, or verifying a bank account, the app makes the entire process faster, more reliable, and, most importantly, secure.

Moreover, the app’s user-friendly interface ensures that even those with minimal technical expertise can navigate through it effortlessly, bridging the digital divide that still exists in many parts of the country.

A Boost for Digital India

The rollout of the new Aadhaar app is also a crucial milestone in India’s ongoing journey to becoming a digital-first nation. As government services, banking, e-commerce, and healthcare continue to digitise, the demand for reliable, secure, and fast identity verification will only grow. The new Aadhaar app is well-positioned to meet this demand, offering a solution that is not only secure but also adaptable to the needs of an increasingly mobile and digitally literate population.

By digitising identity verification, the app also plays a significant role in reducing fraud and promoting transparency. Whether for government welfare schemes or private sector services, the app will ensure that the right person is getting access to the right benefits, minimising errors and, potentially, corruption.

A More Inclusive System for All

Another noteworthy aspect of the new Aadhaar app is its potential for inclusion. In a country as diverse as India, access to technology remains uneven. The app is designed to be accessible to all citizens, from those living in rural areas to urban dwellers, and works even on low-end smartphones. This broad accessibility will make it easier for a larger portion of the population to participate in the digital economy and gain access to essential services.

What’s Next for the New Aadhaar Mobile App?

Feedback from the beta testing will be crucial in fine-tuning the app before its national rollout. Once launched, the app is set to transform the way identity verification is done, making it faster, more secure, and more convenient than ever before.

As more sectors adopt this new form of authentication, we can expect to see a significant reduction in fraud, errors, and delays. Moreover, as India continues its march towards a fully digital future, the Aadhaar app will likely play an integral role in shaping the landscape of digital governance and service delivery.

How To Install The Beta mAadhaar App?

For Android Users:

Open the Google Play Store:
- Tap on the Play Store icon on your Android device.
Search for ‘mAadhaar’:
- In the search bar, type ‘mAadhaar‘ and press Enter.
Install the App:
- Locate the official mAadhaar app developed by UIDAI.
- Tap ‘Install’ to download and install the app on your device.
Set Up the App:
- Open the mAadhaar app.
- Agree to the terms and conditions.
- Create a 4-digit PIN/Password for app access.
- Enter your 12-digit Aadhaar number and the captcha code.
- An OTP will be sent to your registered mobile number. Enter this OTP to verify.
- After verification, your profile will be created, and you can start using the app.

For iOS Users:

Open the App Store:
- Tap on the App Store icon on your iOS device.
Search for ‘mAadhaar’:
- In the search bar, type ‘mAadhaar‘ and press Enter.
Install the App:
- Locate the official mAadhaar app developed by UIDAI.
- Tap ‘Get’ to download and install the app on your device.
Set Up the App:
- Open the mAadhaar app.
- Agree to the terms and conditions.
- Create a 4-digit PIN/Password for app access
- Enter your 12-digit Aadhaar number and the captcha code.
- An OTP will be sent to your registered mobile number. Enter this OTP to verify.
- After verification, your profile will be created, and you can start using the app.

Important Notes:

Registered Mobile Number: Ensure your Aadhaar is linked to your current mobile number, as OTP verification is required during the setup.
App Permissions: Grant necessary permissions to the app for optimal functionality.
Security: Keep your app PIN confidential to prevent unauthorized access.

Conclusion

In a country of over 1.3 billion people, efficient and secure identity verification is no small feat. The new Aadhaar app offers a solution that addresses both security and convenience, making it easier than ever for Indians to authenticate their identity. With its use of facial recognition, QR code authentication, and enhanced privacy controls, the app is set to redefine how identity verification is done in India. As it moves from beta testing to full rollout, the new Aadhaar app promises to be a cornerstone of India’s digital identity infrastructure for years to come.

By Abhinandan, 5 monthsApril 10, 2025 ago

Background Checks

EPFO Boosts UAN Activation With Aadhaar Face Authentication

In a significant step towards streamlining the experience for millions of Indian workers, the Employees’ Provident Fund Organisation (EPFO), under the Ministry of Labour and Employment, has launched a pioneering initiative to make the UAN (Universal Account Number) generation and activation process both simpler and more secure. By integrating Aadhaar Face Authentication Technology (FAT) through the UMANG Mobile App, EPFO aims to empower employees directly, eliminating the need for intermediaries and addressing long-standing challenges.

Historically, the UAN system had been marred by issues such as incorrect or missing details, ranging from fathers’ names to mobile numbers, which often caused delays and confusion. Furthermore, the cumbersome process of UAN activation left many employees unable to access their EPFO services without additional intervention. The new Aadhaar FAT-based process marks a significant departure from this legacy. Not only does it promise to resolve these issues, but it also adds a layer of security through biometric verification, making it a truly digital solution for today’s tech-savvy workforce.

Simplifying UAN Generation And Activation For Employees

For employees, the process of obtaining and activating their Universal Account Number (UAN) has traditionally been cumbersome. Historically, UANs were generated by employers, who submitted employee details to EPFO. However, issues such as incorrect or missing information, like the father’s name, mobile numbers, and birth dates, were common, often causing delays in accessing EPFO services or submitting claims. In many cases, employees never even received their UAN or had trouble with activation due to mismatched or missing contact details.

In response, EPFO has introduced a transformative solution that directly empowers employees to generate and activate their UAN through the UMANG Mobile App, using Aadhaar Face Authentication Technology (FAT). This new process resolves many of the previous challenges and streamlines UAN management, giving employees a fully digital, hassle-free experience.

Key Benefits Of The Aadhaar Face Authentication-Based UAN Process

The adoption of Aadhaar Face Authentication offers several advantages for employees:

100% Aadhaar Validation: The UAN generation process ensures complete validation of employee details through biometric face recognition, guaranteeing that the information is accurate and securely linked to the individual’s Aadhaar profile.
Pre-Populated Employee Data: The system pulls all relevant employee data directly from the Aadhaar database, reducing the possibility of human error and eliminating the need for manual entry.
Instant UAN Activation: Once the UAN is generated through the process, it is automatically activated in the EPFO Member Portal. This immediate activation means employees can start using EPFO services right away.
No Employer Dependence: Employees no longer have to wait for employers to generate or activate their UAN. Instead, they can complete the process themselves and download their e-UAN card PDF directly from the app, cutting out unnecessary delays.
Unlocks EPFO Services: Upon successful activation, employees can immediately access a range of EPFO services, including passbook viewing, KYC updates, claim submissions, and more.

Step-by-Step Guide For Employees To Generate And Activate UAN

The process for employees to generate and activate their UAN using Aadhaar Face Authentication is straightforward. Follow these simple steps:

Download the UMANG App: Start by downloading the UMANG App from the Play Store and installing it on your phone.
Install AadhaarFaceRD App: Install the AadhaarFaceRD App, which is required for face authentication during the UAN generation process.
Open the UMANG App: Launch the UMANG App and navigate to the “UAN Allotment and Activation” section under UAN services, choosing Face Auth.
Enter Aadhaar and Mobile Details: Provide your Aadhaar number and the mobile number linked to your Aadhaar account. An OTP will be sent to this mobile number for validation.
Complete Face Authentication: After verifying the OTP, the app will prompt you to take a live photo. Ensure the image is captured correctly—the green outline will indicate that the photo has been successfully taken.
Receive UAN and Download e-UAN Card: Once the face authentication is successful, your UAN will be generated and sent to your mobile via SMS. You can then download your e-UAN card PDF from the UMANG App or the EPFO Member Portal. Your UAN will be auto-activated on the Member Portal, eliminating the need for additional steps.

Enhanced Security Through Biometric Authentication

One of the standout features of the new UAN generation and activation process is the incorporation of biometric authentication. Unlike traditional methods that rely on demographic information or OTP-based verification, Aadhaar Face Authentication ensures a higher level of security, making it nearly impossible for fraud or mistakes to slip through the cracks.

Biometric authentication, specifically through face recognition, offers a foolproof way of verifying an individual’s identity right from the point of entry into the EPFO system. This level of accuracy not only strengthens security but also provides an added layer of convenience for both employees and employers.

Why Face Authentication Is More Secure Than Traditional Methods

Traditional methods of verifying identity, such as demographic verification or OTP-based authentication, are prone to errors. For example, users might mistype their name or birthdate, or face delays in receiving OTPs, leading to frustration and unnecessary steps in the process.

With Face Authentication, the system directly matches the employee’s live photo against the Aadhaar database, ensuring that the right person is linked to the correct UAN. This method is much more secure because it uses unique biometric identifiers that cannot be replicated, ensuring that only the rightful individual can generate and activate their UAN. Additionally, the use of Aadhaar-linked mobile numbers adds another layer of verification, ensuring the data is consistent and tamper-proof.

Encouraging Employers To Adopt The New UAN Generation Process

While the new Aadhaar Face Authentication-based UAN generation system is designed to be employee-centric, employers also play a crucial role in ensuring its successful adoption. For many employees, particularly first-time jobholders, the process of generating and activating their UAN may seem unfamiliar or daunting. Here, employers can make a significant difference by encouraging and guiding their employees to use the new system.

Employers should consider promoting this direct method of UAN generation, helping employees understand the steps and benefits. By guiding employees through the process, employers can ensure that UANs are generated accurately and on time, eliminating the need for follow-up corrections. This proactive approach can significantly reduce the administrative burden on employers and speed up the onboarding process for new employees.

Additionally, employers should make it a point to educate their workforce about the advantages of self-service features that are now available through the EPFO Member Portal and the UMANG App. This can help employees take full advantage of EPFO services like passbook viewing, KYC updates, and claim submissions, streamlining their experience with EPFO.

EPFO’s Collaboration With My Bharat For Digital Life Certificates

In addition to the UAN generation process, EPFO is also expanding its digital services for pensioners. Through a collaboration with My Bharat, EPFO plans to promote the digital life certificate system known as Jeevan Pramaan, which will also leverage Face Authentication Technology.

This initiative aims to make life certificates available at the doorstep of pensioners, enabling them to authenticate their identity using biometric data, without the need for visiting EPFO offices. By extending the reach of digital services in this way, EPFO is ensuring that even pensioners who may face difficulties accessing physical offices can still benefit from timely and secure services.

The integration of Aadhaar Face Authentication into these services will provide an additional layer of security, ensuring that pensioners’ identities are verified accurately and promptly. This collaboration underscores EPFO’s commitment to improving accessibility and security for all members, regardless of their location or technical proficiency.

EPFO Simplifies Cash Withdrawals

Removal Of Cheque Leaf And Bank Passbook Upload Requirements

In this initiative aimed at reducing administrative bottlenecks, EPFO has also decided to completely remove the requirement for uploading images of cheque leaves or attested bank passbooks when filing online claims. For many EPF members, this step has been a source of delays and frustration due to the potential for poor-quality uploads, errors in document formatting, or even simple misunderstandings about what was required.

Historically, EPFO required these documents to verify the bank account details of members when they submitted claims. However, following the successful pilot of relaxing this requirement for KYC-updated members in May 2024, the policy has now been extended to all EPF members. This change is crucial as it eliminates one of the major reasons for claim rejections — poor-quality or unreadable uploads — thereby speeding up the process and reducing the volume of grievances related to documentation errors.

The UAN system, which links an employee’s bank account with their EPF account, already verifies the bank account holder’s name and account number at the time of account seeding. As a result, the need for additional documentation such as cheque leaf images or passbook attestation is now redundant.

By removing this additional step, EPFO aims to benefit an estimated 6 crore members, enabling faster, hassle-free claim settlements. With the elimination of this requirement, EPFO members will no longer face unnecessary delays in accessing their funds. This is particularly crucial for employees looking to withdraw or transfer their EPF balances in times of need, making the entire claims process more efficient and user-friendly.

Removal Of Employer Approval For Bank Account Seeding

EPFO has also introduced a key simplification to the process of seeding bank account details with the Universal Account Number (UAN), eliminating the need for employer approval after bank verification. This reform addresses one of the most time-consuming steps in the process of ensuring that an employee’s PF withdrawals are credited to their bank account.

Previously, after an employee submitted a request to seed their bank account with UAN, the employer was required to approve the verification, which added a layer of delay. On average, the bank verification took around 3 days, but the employer approval could take as long as 13 days, resulting in significant delays for members who were waiting for their PF balances to be credited to their accounts. This slow approval process created unnecessary backlogs and frustration for employees, especially for those who needed quick access to their funds.

To streamline this process, EPFO has now removed the employer approval step, making the seeding process faster and more efficient. This change will immediately benefit the 14.95 lakh members whose bank account verification requests were previously pending due to delays in employer approvals. With this reform, these members will now experience a much quicker resolution of their seeding requests.

In addition, the new system enables employees to update or change their bank account details linked to their UAN without needing employer intervention. The update process will be facilitated through Aadhaar OTP authentication, ensuring that the employee’s identity is securely verified. This makes the entire process more flexible, reducing dependency on employers and providing more control to the members over their account details.

EPFO Expands Partnerships With Banks

In another key development, EPFO has expanded its network of empanelled banks to 32, including 15 new public and private sector banks. This move enhances transaction efficiency, ensuring quicker and more seamless processing of EPF contributions and claims.

Previously, employers were limited to a smaller pool of banks when remitting EPF contributions. With the inclusion of these 15 additional banks, EPFO is now providing employers with a wider range of options to choose from, improving flexibility and reducing administrative friction. The total annual collections managed through these banks amount to nearly Rs. 12,000 crore, allowing for smoother and more direct contributions to EPF accounts.

Employees will no longer face delays in the bank account verification process when they seed their accounts with UAN, as these newly empanelled banks will now directly verify the bank details of employees. This ensures that members can access their EPF balances more quickly, without relying on third-party aggregators, which previously added delays to the process.

This reform will also reduce the time taken for EPF dues to be processed, allowing for quicker investment and increasing the potential returns on members’ savings. Previously, dues remitted through non-empanelled banks often took T+2 days for processing, whereas transactions with empanelled banks are now processed on a T+1 day basis. This improvement not only speeds up the process but also benefits EPFO by lowering operational costs related to name validation and reducing dependency on intermediary channels.

For employers, the expanded network provides greater convenience when dealing with EPF payments. The ability to interact directly with a broader set of banks to resolve payment issues or grievances will lead to a more efficient and transparent process.

By Abhinandan, 5 monthsApril 10, 2025 ago

Employee Screening

Risk & Compliance

Financial Intelligence

Identity Verification

Utilities

Employment

Entity/Business Level

Professional

Banking & Payments

Fraud Detection

Background Verification

Due-Diligence

Resource Library

Featured Resource

KYC

RBI’s Push For Responsible AI In Financial Services

Opportunities Of AI In BFSI

Risks And Challenges Of AI Highlighted By RBI

The FREE-AI Framework Explained

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

Adoption Levels

Complexity Of Models

Infrastructure Choices

Use Cases (583 Applications Reported)

Generative AI

Governance And Control Mechanisms

Reading The Numbers

Inclusion, Digital Public Infrastructure And Sector-Specific Models

Barriers And Governance Gaps

Regulatory Trajectory: Proportionality, Outsourcing, Consumer Disclosures

Operational Safeguards: Policy, Monitoring, And Incident Reporting

Enablers: Innovation Sandbox And Sector Collaboration

How AuthBridge Helps BFSI Align With FREE-AI

What The Framework Expects vs What You Can Operationalise With AuthBridge

Conclusion

Co-Living Has Now Gotten Mainstream

Why PGs And Flats Are Losing Their Edge

Co-Living vs. PGs, By The Numbers

Safety, Security, And The Role Of Tenant Verification

What Does Tenant Verification Look Like Today?

The Legal Consequences Of Not Verifying Tenants

Best Practices For Tenant Verification

Best Practices For Tenants Looking For Co-Living Spaces

Best Practices For Investors: Due Diligence

Conclusion

Introduction To Contact Point Verification In Banking

Core Methods And Best Practices For CPV In Banking

Regulatory Framework And RBI Guidelines For CPV

Practical Use Cases And Benefits Of CPV In Banking

1. Secure Onboarding and Account Activation

2. Safe Transaction Authorisations

3. Dormancy Reactivation and Periodic Re-Verification

4. Regulatory Audit and Compliance Reporting

Conclusion

Introduction

What Are Deepfake Scams?

Understanding Deepfake Technology

How Deepfake Scams Target Customer Onboarding

The Risks Of Deepfake Scams In Customer Onboarding

Financial Losses

Reputational Damage

Legal And Compliance Risks

Increased Operational Costs

Intellectual Property Theft And Identity Fraud

Impact On Customer Experience

5 Tips To Prevent Deepfake Scams In Customer Onboarding

1. Implement Video KYC with Liveness Detection

2. Use AI-Powered Deepfake Detection Tools

3. Multi-Factor Authentication (MFA)

4. Cross-Platform User Verification

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

Utilising Advanced Technology For Enhanced Security

AI And Blockchain For Secure Onboarding

Real-Time Video Analysis

Legal And Compliance Considerations For Preventing Deepfake Scams

Ensuring Regulatory Compliance

To stay compliant:

Maintaining Data Privacy

Conclusion

The Issue At Hand: Regulatory Crackdown In Quick-Commerce