If you could travel back to 2019 and warn a lender about one thing, what would it be?
"Don't trust the Average Bank Balance." They'd laugh at you. ABB was one of the more important metrics for risk assessment after bureau scores.
The one number that could tell you a borrower’s ability to repay a loan.
Five years later, that same metric is enabling loan approvals for people who will never pay back a rupee.
Take the example of Ramesh and Suresh, who both live in Mumbai. Both are freelance graphic designers earning ₹1 lakh monthly, who pay their bills on time, invest in SIPs, and manage similar household expenses. They even had identical credit histories. Yet when they each visited their neighborhood bank last month, something extraordinary happened:
Suresh walked out with approval for twice the loan amount that Ramesh received.
The difference wasn't in their income statements or credit scores. It was in a single number that has quietly become the backbone of India's credit assessment system:
Average Bank Balance (ABB).
Ramesh's ABB: ₹70,000
Suresh's ABB: ₹3,00,000
For decades, Average Bank Balance has been the North Star of credit assessment, particularly for India's vast population of self-employed individuals and small business owners. With MSMEs contributing over 30% to India's GDP and most lacking traditional income proofs, ABB became the great equalizer, a simple, quantifiable measure of financial health.
But here's what every risk manager needs to understand: that metric is now fundamentally broken.
The Digital Disruption Nobody Saw Coming
Going back to our example of Ramesh and Suresh.
Suresh didn't earn a rupee more than Ramesh. He simply gamed the system and asked his friends to transfer him money via UPI, artificially inflating his balance to create an illusion of financial prosperity. Welcome to the era of "ABB inflation fraud," where India's digital payment revolution has turned our most trusted underwriting metric into a weapon of financial deception.
The Scale of Digital Distortion
India's digital payments ecosystem has exploded beyond anyone's projections. UPI alone processes over 20 billion transactions monthly, with transaction values exceeding ₹24.85 lakh crores. What was once a cash-heavy economy has become a digital-first, financial playground, where money can be transferred faster than you might finish reading this sentence!
This transformation has fundamentally shattered the assumptions behind ABB as a reliable metric.
How Digital Convenience Creates Credit Illusions
Every family dinner bill split among friends, every household expense transferred between spouses, every emergency loan between relatives now creates a digital footprint that unintentionally inflates average balances in ways that make traditional ABB-based underwriting dangerously misleading.
Genuine borrowers with active digital lives suddenly appear more creditworthy than they actually are. A software engineer splitting vacation costs with friends, a homemaker receiving temporary funds from relatives, or a small business owner managing family finances all see their ABB spike without any real change in their repayment capacity.
When Smart Money Management Looks Like Credit Risk
On the flip side, unintentional inflation hides another equally problematic issue: unintentional deflation. Perhaps more damaging than fraud is how lenders' reliance on ABB could, in some ways, systematically exclude their most creditworthy customers.
Consider the affluent segment that uses sweep accounts, automatically moving surplus funds to higher-yield instruments, or sophisticated cash managers who maintain minimal operational balances while maximizing returns elsewhere.
Their relatively lower average balances often mask substantial assets and income streams, leading to loan rejections that push profitable customers away.
This can result in 2 outcomes:
- It may mask the borrower’s true financial behavior, resulting in over-lending to people who may struggle to repay larger loan amounts.
- It may penalize those whose bank balance drops temporarily, say, due to transferring funds to savings or other accounts. This might cause them to be denied loans they could actually repay, or be offered only at higher interest rates.
However, there's an even more sinister side to this digital distortion.
How Fraudsters Have Started Weaponizing Digital Transactions
The intentional manipulation is where ABB becomes truly dangerous. Sophisticated fraudsters have discovered that inflating ABB is embarrassingly simple. Unlike document forgery, which requires skill and leaves traces, ABB manipulation exploits the very features that make digital payments convenient.
How DSAs Game Your Metrics
The ABB problem is amplified by the ecosystem around it. Direct Sales Agents (DSAs) and channel partners, who are fully aware of how lenders inflate ABB, actively coach borrowers on balance manipulation techniques.
"Maintain ₹2 lakh for three months before applying," they advise.
"Ask family members to park money in your account temporarily."
This coaching creates a perverse selection bias: sophisticated fraudsters and coached borrowers pass ABB filters easily, while genuine small business owners with efficient cash management practices get rejected.
And the truth is, borrowers don’t even need a coach. This loophole is so obvious that many figure it out on their own.
You're not just missing good customers, you might be systematically selecting for the wrong ones.
What Traditional Risk Models Can't See
What if there was a way to see through this digital noise?
What if you could distinguish between a ₹2 lakh salary credit and a ₹2 lakh temporary deposit from a friend?
What if your underwriting could actually reward efficient cash management instead of penalizing it?
Modern AI can decode the story behind every transaction, revealing patterns that ABB as a metric misses entirely:
- Transaction purpose patterns: Income flows have a clear business context; P2P transfers lack a commercial purpose.
- Sender analysis: Business payments come from registered entities; personal transfers from individual accounts
- Behavioral patterns: Systematic investments and sweep activities indicate financial sophistication, not weakness
The technology exists.
The question is: are you ready to evolve beyond metrics that digital India has quietly made obsolete?
The Future of Intelligent Underwriting
Imagine a world where your credit decisions are based on true financial behavior, not digital illusions. A world where fraudsters can't game the system with simple UPI transfers or where your most sophisticated customers get the credit they deserve instead of being turned away by outdated metrics.
Picture your risk team having complete clarity on every applicant:
- Real income flows, separated from temporary fund parking and P2P noise
- Genuine business transactions, distinguished from personal fund movements
- Financial sophistication signals that traditional models miss
- Fraud patterns are flagged automatically before they enter your portfolio
This isn't a distant vision; it's happening today for lenders who've moved beyond Average Bank Balance and toward true transaction intelligence.
Your competitors who evolve first will capture the profitable segments that ABB-dependent models systematically reject. They'll avoid the losses that sophisticated manipulation schemes create. They'll build portfolios based on actual financial behavior rather than manufactured metrics.
The question isn't whether this evolution will happen; it's whether you'll lead it or be left behind by it.
Transaction Intelligence Platform (TIP)
IDfy's Transaction Intelligence Platform (TIP) represents the next evolution in credit underwriting. Instead of relying on crude balance averages, TIP uses advanced AI to understand the true nature of every transaction in a borrower's statement.
TIP transforms the core challenge of modern underwriting: separating financial signals from digital noise. Early adopters report more accurate identification of genuine versus inflated average balances, enabling them to see through digital noise to borrowers' true financial capacity. This clearer picture directly influences overall portfolio quality as lenders approve based on actual repayment ability rather than manufactured metrics.
Lenders can finally base credit decisions on actual financial capacity rather than manufactured metrics by understanding the true story behind every transaction.
This gives you the power to:
- Approve creditworthy customers whose efficient cash management makes them invisible to traditional models
- Reject sophisticated fraudsters Real income flows, whose manipulation techniques fool ABB-based systems
- Optimize pricing on real risk profiles rather than distorted balance averages
- Scale confidently knowing your underwriting evolves with India's digital transformation
The Choice Is Yours
Relying on Average Bank Balance isn't just outdated, it's dangerous. It's an open door for fraud to slip into your credit funnel while pushing profitable customers toward competitors who understand their true financial strength.
In Suresh and Ramesh's story, the real problem wasn’t just with the bank that approved the wrong borrower; it was an entire industry's faith in a metric that digital India has quietly made meaningless.
The future of credit belongs to those who can separate financial signals from digital noise.
It's time to underwrite with Transaction Intelligence.
Ready to move beyond Average Bank Balance?
Discover how IDfy’s Transaction Intelligence Platform (TIP) can transform your underwriting.
Reach out to us at anika@idfy.com.