GST Returns bank Statement Analyser

Why Verify GST Returns & Bank Statements In Third-Party Onboarding?

Introduction

Onboarding third-party vendors, suppliers, or distributors is an important aspect of business operations, particularly in sectors such as e-commerce, manufacturing, and retail. As a business expands its supply chain or distribution network, ensuring that these third parties comply with all financial and regulatory requirements becomes a thing of extreme importance.

Verifying GST returns and bank statements during the onboarding process plays a key role in mitigating financial risks and ensuring business integrity. These documents not only help in verifying the third party’s legitimacy but also ensure compliance with national regulations.

Understanding GST Returns

What are GST Returns?

GST returns are filed by businesses to report their sales, purchases, tax collected, and tax paid to the government under the Goods and Services Tax (GST) Act in India. There are different types of GST returns, each serving a specific purpose:

  • GSTR-1: Reports all outward supplies (sales).

  • GSTR-3B: A summary return filed monthly or quarterly, reporting tax liability and paid taxes.

  • GSTR-9: An annual return consolidating all transactions during the year.

  • GSTR-2A/2B: A self-generated return reflecting purchases and input tax credits available.

Why Verifying GST Returns Is Crucial During Onboarding

  • Tax Compliance Check: Verifying a third party’s GST returns ensures that they are fulfilling their tax obligations.

  • Input Tax Credit (ITC) Verification: By examining the GST returns, businesses can verify whether a third party is eligible for input tax credits, which can have a direct impact on the cost structure, especially in B2B transactions.

  • Identifying Non-Compliance Risks: Non-compliant vendors or suppliers might have discrepancies in their GST filings. Verifying GST returns helps identify any potential tax evasion or fraud.

For example, a manufacturing unit may onboard a new supplier. Verifying the supplier’s GST returns ensures that the supplier is adhering to tax laws, which ultimately impacts the pricing and credit claims for the buyer. If the supplier is not compliant, the buyer could face penalties or loss of input tax credits.

What Are Bank Statements?

A bank statement is a detailed record of all financial transactions that have taken place in a company’s bank account during a given period. This document lists both incoming and outgoing payments, including transactions with clients, suppliers, and employees.

Talk to sales - AuthBridge

Key Components Of A Bank Statement:

  • Deposits (Receipts): Payments received from customers or other sources.

  • Withdrawals (Expenditures): Payments made to suppliers, employees, or for other business expenses.

  • Closing Balance: The final balance in the account at the end of the period.

Why Verifying Bank Statements Is A Must In Third-Party Onboarding:

  • Financial Health Assessment: By verifying bank statements, businesses can assess the financial stability of their vendors or suppliers. A supplier who regularly faces overdraft charges or delayed payments may indicate financial instability.

  • Tracking Transaction Accuracy: Verifying bank statements ensures that the payments made to vendors match the amounts invoiced. Discrepancies here may highlight potential fraud or operational inefficiencies.

  • Ensuring Authenticity: Third-party vendors or suppliers who cannot provide clean, consistent bank statements may indicate that their financial operations are not well-managed, posing a risk to business relationships.

For example, a logistics company onboarding a new distribution partner can verify the partner’s bank statements to ensure that the partner’s financial transactions are transparent and the payment history aligns with the company’s invoicing practices. Discrepancies here could be a red flag for potential payment issues or financial instability.

GST Returns vs Bank Statements: Key Differences And Similarities

Aspect

GST Returns

Bank Statements

Purpose

Verifies tax compliance and eligibility for input tax credits

Reflects the actual flow of cash, demonstrating financial health

Frequency

Monthly/Quarterly/Annually (depends on the type of return)

Typically monthly

Issued By

Government of India (GST portal)

Banks or financial institutions

Data Reflected

Sales, purchases, tax collected and paid

Deposits, withdrawals, bank charges, balances

Legal Requirement

Mandatory for businesses registered under GST

Not mandatory, but essential for business financial health

Key Insights

Tax liabilities, GST credits, tax paid

Cash flow, financial stability, and payment history

Why Verifying GST Returns & Bank Statements Is Important For Compliance

Compliance is at the heart of successful third-party onboarding, especially in India, where regulations are strict, and penalties for non-compliance can be very harsh.

  • Preventing Fraud and Evasion: Both GST returns and bank statements help identify discrepancies that could point to fraudulent activity, such as incorrect reporting of tax liabilities or irregular financial transactions.

  • Ensuring Transparency and Integrity: When businesses verify both GST returns and bank statements, they ensure the third-party vendor or supplier is operating within legal frameworks. This reduces the likelihood of engaging with entities involved in tax evasion or financial misconduct.

  • Minimising Risk in the Supply Chain: By conducting a thorough verification process, businesses can minimise risks in their supply chain, ensuring they are not unknowingly partnering with unreliable or non-compliant entities.

How Third-Party Onboarders Can Leverage GST And Bank Statement Verification

Third-party onboarding professionals in India can use these verification processes to ensure that vendors, suppliers, or distributors meet the required standards of financial and tax compliance.

  1. Step 1: Collect GST Returns and Bank Statements:
    Ensure that all third-party vendors provide these key documents, ensuring they are complete, accurate, and up-to-date.

  2. Step 2: Cross-Check GST Returns for Compliance:
    Verify the GST registration status, check for matching sales and purchases, and ensure the vendor has paid the required taxes.

  3. Step 3: Examine Bank Statements for Financial Stability:
    Look for consistent payments and receipts, and confirm there are no major discrepancies or signs of financial mismanagement.

  4. Step 4: Conduct Risk Assessment:
    Using these documents, perform a risk assessment to determine the financial and operational health of the third party.

Conclusion

In India, verifying GST returns and bank statements is not just about adhering to tax regulations. It is a key practice to ensure that the third-party vendors, suppliers, or distributors you onboard are financially stable, trustworthy, and compliant with the law. This process significantly reduces the risk of fraud, tax evasion, and financial instability that can lead to reputational damage or operational disruptions.

For businesses looking to onboard third parties in India, the importance of these documents cannot be overstated. They play a critical role in protecting the integrity of your supply chain and ensuring your compliance with India’s ever-evolving regulatory landscape.

AI in Bank Statement Analyser

The Impact Of AI In Bank Statement Analysis

The Importance Of Bank Statement Analysis

Have you wondered how important your Bank Statement can be? You can learn a lot about someone/a company by looking at their bank statement. It doesn’t just show how much they earn or what they spend, it quietly reveals patterns of trustworthiness, financial strain, lifestyle choices, and even integrity.

For lenders, insurers, gig platforms, and credit underwriting teams, this document has become one of the most valuable pieces of critical decision-making.

But here’s the problem. No two bank statements look the same. Some are downloaded as polished PDFs. Others arrive as scans, screenshots, or even photos taken in a hurry. They’re filled with acronyms, bank codes, fee entries, bounced transactions, and sometimes, clever manipulation. Reviewing these manually is tedious and inconsistent. And it breaks under pressure when you’re trying to process hundreds or thousands of applications a day.

This is where Artificial Intelligence (AI) has quietly made an impact like never before.

AI can read any format, in any layout, and turn it into clean, structured data. But more importantly, it makes sense of that data. It finds anomalies that a human might miss. It learns over time and spots signs of tampering, synthetic salaries, or income that doesn’t match the furnished information.

And it does all this in seconds.

If your business depends on knowing who to trust, whether you’re lending ₹10,000 or over ₹10 crore, then understanding how AI handles bank statement analysis is indispensable.

How AI Understands Bank Statements Like A Risk Analyst Would

A bank statement, when read correctly, is not just a ledger of deposits and withdrawals. It is a behavioural data set that shows financial discipline, income reliability, exposure to debt, and potential red flags. For decades, skilled underwriters have relied on their intuition to extract these insights. The challenge now is to do it at scale, without compromising judgment and accurate decision making.

Artificial Intelligence enables precisely that, by replicating how experienced analysts read statements.

The first layer of interpretation begins with data structuring. AI uses computer vision and contextual learning to convert unstructured statements into standardised tables, regardless of format or source. But beyond parsing, the important bit lies in identifying what the numbers mean.

AI models trained on financial behaviour can:

  • Identify whether an inflow is salary, a loan, or a one-time deposit.

  • Map EMI deductions to outstanding liabilities.

  • Quantify net monthly surplus or deficit.

  • Detect anomalies such as sudden spikes in income, altered balances, or round-tripped transactions.

It does this not by keyword detection, but by assessing transaction frequency, narrative context, metadata, and long-term balance trends. Income validation, bounce history, recurring obligations, and financial stress indicators can all be extracted within seconds, without requiring human intervention.

What makes this useful is not just accuracy, but consistency. Every profile is assessed using the same logic, removing subjectivity and reducing error rates. This standardisation becomes crucial for lenders, especially in unsecured credit, where traditional credit scores fall short.

The strength of AI is not that it reads faster, but that it reads comprehensively. It ensures that every entry is considered, every inconsistency is flagged, and every applicant is assessed based on actual financial behaviour.

Where AI-Based Bank Statement Analysis Delivers The Most Impact

AI in bank statement analysis solves core business problems that financial institutions have struggled with for years. These include delayed decisions, operational bottlenecks, poor visibility into risk, and exposure to manipulated data.

The impact is the highest in cases where accuracy, speed, and scale are extremely important.

1. Lending and Credit Risk Assessment

For lenders, particularly those dealing in unsecured or short-term credit, there is a non-negotiable need for high reliability of stated income and repayment behaviour. AI enables lenders to check not just credit scores, but also get access to more nuanced, real-time insights from transactional behaviour.

A few key benefits:

  • Income classification: AI identifies regular salary credits, freelance income, or inconsistent gig payments across banks and formats.

  • EMI tracking: Ongoing loan commitments, including informal borrowings, are mapped against net disposable income.

  • Bounce and penalty detection: AI highlights dishonoured cheques or insufficient balance incidents, often missed in manual reviews.

  • Cash flow profiling: Monthly surplus, deficit, and balance trends are charted to evaluate repayment capacity more reliably than stated income.

2. Fraud Detection and Document Forensics

Tampering with bank statements is a common problem, particularly in areas where PDF uploads are accepted without source verification. AI-led systems are trained to detect:

  • Inconsistent fonts, spacing, or layout shifts that point to edits

  • Metadata mismatches or file generation anomalies

  • Repeated transaction IDs or misaligned account balance flows

Not only does AI highlight document-level manipulation, it also detects synthetic behaviour patterns, like inflated one-time credits to fake a high income or backdated entries to mimic salary history. This layer of intelligence allows fraud teams to act earlier, with stronger audit trails and fewer false positives.

3. Gig Economy and Blue-Collar Underwriting

In segments like logistics, delivery, and home services, traditional documents like Form 16 or credit bureau scores don’t exist or are outdated. Bank statements become the only reliable source of verification.

AI systems trained on these patterns can:

  • Read salary-like credits from platforms such as Swiggy, Zomato, or Ola

  • Assess income regularity even in cash-heavy or high-churn environments

  • Create risk bands based on observed transactional hygiene, not just KYC data

This expands the pool of underwritable applicants and supports financial inclusion at scale, without compromising on risk visibility.

4. SME and Self-Employed Profiles

For small business owners or self-employed individuals, balance sheets are often unavailable or unaudited. Here, AI-analysed bank statements function as cash flow statements, providing insights into:

  • Revenue streams

  • Seasonal income fluctuations

  • Vendor payments

  • Tax payments and GST-related outflows

This is especially valuable for NBFCs and digital lenders operating in Tier 2 and 3 cities, where documentation is limited, and credit demand is high.

Advantages Of AI Bank Statement Analyser

In lending, risk management, and compliance, time and accuracy are everything. For decades, financial institutions have relied on manual processes to sift through bank statements, identify risks, and make key decisions. The problem, however, is that this method doesn’t scale, and it misses valuable data that could be used to make more informed, faster decisions.

This is where AI comes in handy.

Speed and Scalability Without Sacrificing Quality

As businesses scale, so do the demands on their underwriting teams. Processing bank statements manually can be time-consuming, often requiring multiple staff members to cross-check the same information. AI removes these bottlenecks. It can process thousands of bank statements at once, maintaining accuracy and consistency in every document.

This level of efficiency means faster decision-making, which is crucial when dealing with high volumes, such as during loan approvals, credit risk assessments, or compliance verifications. What might have taken hours with a manual team can now be achieved in minutes, without compromising on quality.

Improved Accuracy and Reduced Human Error

The complexity and variability of bank statements can make them prone to human error. Whether it’s an overlooked transaction, an incorrectly flagged anomaly, or an unreadable entry, these mistakes can lead to significant issues down the line.

AI in bank statement analysis mitigates these risks by being objectively consistent. It processes every statement using the same parameters, applying rigorous algorithms to detect inconsistencies, potential fraud, or unusual patterns that might otherwise be missed. For financial institutions, this reduces risk by increasing the accuracy of each analysis, which is particularly crucial when evaluating creditworthiness or assessing exposure.

Enhanced Risk Detection and Fraud Prevention

In today’s fast-moving digital landscape, fraud is evolving rapidly. Manipulated bank statements are one of the most common methods of fraud, especially when it comes to synthetic identities or artificially inflated incomes.

AI detects these discrepancies by analysing every aspect of the statement, from the metadata and formatting of the document to the transactional patterns. The ability to spot discrepancies, even subtle ones, ensures early detection of fraud before it escalates. This is invaluable in a landscape where preventing fraud before it happens is far more cost-effective than trying to recover losses afterwards.

Building Smarter, More Inclusive Credit Models

AI doesn’t just assess risk based on traditional financial indicators, such as credit scores or reported income. It also considers behavioural signals, such as spending patterns, cash flow cycles, and payment history, to build a more nuanced understanding of an individual’s or business’s financial health. This is particularly beneficial for underserved segments, such as gig workers or small businesses, who may not have access to traditional forms of credit reporting.

By incorporating these behavioural insights, AI enables businesses to make better, more informed lending decisions, even for individuals without a traditional credit history.

Get Faster, Smarter, and Accurate AI-powered Bank Statement Analysis With AuthBridge

The benefits of AI in bank statement analysis are undeniable. From improving decision-making speed to enhancing accuracy and detecting fraud, it’s clear that this technology is transforming how financial institutions handle large volumes of complex documents. However, the real challenge lies in implementing this technology effectively and ensuring it integrates seamlessly into your existing workflows.

At AuthBridge, we’ve developed a powerful AI-driven solution that takes the complexity out of bank statement analysis. Our tool parses data from the documents, providing financial institutions with deep insights and actionable data. Our solution enables smarter, faster decisions that drive business growth while reducing operational costs.

Key Features of AuthBridge’s Bank Statement Analyser:

  • High Accuracy & Precision: We ensure that every detail of a bank statement is captured and analysed correctly, eliminating human error and improving data integrity.

  • Customisable & Scalable: Whether you’re handling 10 statements or 10,000, our solution scales effortlessly, offering custom configurations to fit your unique business requirements.

  • Fraud Detection: Detects inconsistencies, metadata mismatches, and suspicious patterns that indicate potential fraud, all while improving operational efficiency.

  • Integration-Ready: Easily integrates with your existing systems to streamline operations, from loan approvals to compliance checks, without disrupting your current workflow.

Conclusion

AI has already begun revolutionising bank statement analysis. What once was a manual, slow, and error-prone process is now a fast, accurate, and automated decision-making tool that businesses and financial institutions can rely on. The next step is to integrate this technology into your operations, and AuthBridge’s Bank Statement Analyser is the ideal solution to help you do just that.

Hi! Let’s Schedule Your Call.

To begin, Tell us a bit about “yourself”

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

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

Thank You

We have sent your download in your email.

Case Study Download

Want to Verify More Tin Numbers?

Want to Verify More Pan Numbers?

Want to Verify More UAN Numbers?

Want to Verify More Pan Dob ?

Want to Verify More Aadhar Numbers?

Want to Check More Udyam Registration/Reference Numbers?

Want to Verify More GST Numbers?