Credit Illusions: The Flawed Logic of MSME Working Capital Assessment

Section 1: The Illusion of Structure

For decades, India’s MSMEs have been navigating a labyrinth of credit norms designed to bring structure, logic, and discipline to working capital financing. From the moment a small business approaches a bank, its viability is judged not by its agility, relationships, or digital revenue trails, but by a maze of ratios, margin assumptions, and stock statements. It’s a framework meant to standardize risk — but what if that very framework is fundamentally flawed?

The dominant narrative in credit underwriting still worships the “current ratio,” the “turnover method,” and projections derived from last year’s trial balances. These are comfort zones for both bankers and auditors. But for the average kirana trader, services provider, or digital-first start up — this model is often a poor reflection of reality. Their business cycles are fluid, informal, and rapid. Their customers pay via UPI, not bills of exchange. Their inventory turns every 7 days, not 90. And yet, the credit they receive is tethered to an outdated checklist built in another era.

The illusion is seductive. Ratios provide the comfort of numbers. But beneath this comfort lies a dangerous complacency — a system that frequently ends up penalizing genuine entrepreneurs for not conforming to form, not for failing in business.

We’re told that this model ensures prudence. That it's the backbone of risk control. But what if the real risk lies in ignoring data trails that actually reflect behaviour — not just balance sheets?

This blog is not an attack on structure. It’s a call for relevance.

Section 2: How We Got Here — Historical Roots of MSME Working Capital Assessment

The roots of India’s working capital (WC) assessment framework lie in the industrial economy of the 1970s and 1980s — a time when capital was scarce, foreign exchange tightly controlled, and credit discipline a national priority. In this environment, the Reserve Bank of India (RBI) commissioned committees that sought to bring method to the madness. Chief among them was the Tandon Committee (1975), which introduced the idea of minimum borrower contribution to current assets — and laid the groundwork for what we today know as “drawing power” and “margin norms.”

Later came the Chore Committee (1979), which sought to tackle the problem of "excess borrowing" by suggesting strict monitoring of inventory and receivables and discouraging cash credit as the default option. Ironically, cash credit went on to become the default structure across the banking system — not because it was efficient, but because it was elastic.

The Nayak Committee (1991) was arguably the first major attempt to simplify credit access for small businesses. It proposed a rule-of-thumb method — 20% of projected turnover as the WC limit — to bypass the cumbersome analysis small units could not support. While this worked well in principle, it got codified into a lazy underwriting practice. What was meant to be a workaround became the primary route. Credit officers stopped asking questions; they just applied the formula.

What began as progressive reform slowly ossified into a rigid set of norms. Regulatory circulars institutionalised the 20% turnover rule. Margins were hardcoded at 25%. Drawing power logic became sacrosanct. And the cash credit/OD format — meant for seasonal and fluctuating needs — morphed into the permanent WC model for 80% of MSMEs.

The problem is not that these models once made sense. The problem is that the economy has moved, but the models have stayed behind.

Small businesses no longer rely on bill discounting or cheques. They're on UPI. Their customers are B2C, not B2B. They restock daily, not monthly. Yet, we still ask them for audited stock statements and 3-monthly receivables aging reports to justify credit limits.

In short, we’re applying an industrial-era model to a post-digital, hyper-fluid, fragmented MSME landscape.

Section 3: The Gaps Between Model and Reality

Despite its structured elegance on paper, the current credit assessment framework collapses in the face of on-ground MSME realities. The mismatch is not marginal — it’s fundamental. It stems from five critical assumptions embedded in conventional underwriting that no longer hold true in today’s MSME ecosystem.

🧱 1. Working Capital Gap (WCG) = Financeable Reality? Not Always.

The WCG method calculates:(Current Assets – Current Liabilities – Margin) = Financeable Bank Credit. This assumes that current assets (inventory + receivables) are both accurately reported and reliably monetisable. But what if:

• Inventory is fast-turning or purchased just-in-time?

• Receivables are cash-based or rolling daily?

• Margin calculations are based on last year’s closing stock, not real-time cash flow needs?

For service-based MSMEs, the notion of “inventory” is often irrelevant. Yet, they're expected to submit stock statements — only to justify a drawing power limit that doesn't match their actual working capital needs.

📉 2. Turnover-Based Limits Don’t Reflect Business Cycles

The 20% of turnover rule is a blunt instrument. It makes no distinction between:

• Seasonal vs. non-seasonal business

• Margin-light trading vs. high-margin services

• First-time entrepreneurs vs. established family businesses

  
  

In many cases, turnover does not capture order-book volatility, input cost fluctuation, or digital channel revenues — all of which affect liquidity and WC requirements.

📊 3. Ratios ≠ Risk Insight

The holy grail — a current ratio of 1.33 — is a regulatory relic. It assumes a consistent relationship between current assets and liabilities. But in today’s MSMEs, liquidity is often managed dynamically through:

• UPI/QR-based rolling payments

• Supplier credit extensions

• Just-in-time purchases

• Deferred GST payments

  
  

  None of these show up in audited ratios. And yet, they’re critical to cash flow resilience.

  
  

🧾 4. Documentation Over Data Trails

Instead of digital payment trails or bureau-backed repayment behaviour, the system continues to ask for:

• Provisional balance sheets

• Projected income statements

• Physical stock audits

  This biases lending in favour of MSMEs who can afford Chartered Accountants — not those with actual repayment capacity. In effect, creditworthiness is based on paperwork, not behaviour.

  
  

🔄 5. Fund-Based Assumptions for Non-Fund-Based Realities

Many MSMEs today rely on platforms, digital sales, and informal channels. Their capital cycles are faster, leaner, and more liquid. But the credit model continues to be asset-heavy, treating collateral as a proxy for intent. This leads to over-sanctioning or under-utilisation — both of which distort true credit demand.

📉 Summary:

The current WC credit assessment process:

• Ignores digital footprint

• Penalises low-document MSMEs

• Assumes static business models

• Promotes a compliance culture over a performance culture

  
  

It’s not that MSMEs aren’t creditworthy. It’s that the model we use to judge them has become blind to how they really work.

Section 4: Case Studies That Expose the Gaps

🧾 Case Study 1: The High-Turnover Retail Trader Penalised for Not Holding Inventory

Profile:

• A small FMCG distributor in Kerala

• Monthly turnover: ₹80 lakhs

• Works on wafer-thin margins (~4–5%)

• Inventory cycle: 3–4 days

• All payments via UPI and NEFT

  
  

What the Banker Sees:

• Low closing stock on books

• No receivables pending beyond 7 days

• Low current ratio (~0.9)

• No traditional “margin” in current assets

  
  

What the Model Says:“Sanction ₹16 lakhs under turnover method (20% of turnover). Drawing power to be calculated based on stock and debtors.”But the stock value is under ₹5 lakhs most days, and receivables are ~₹3 lakhs — resulting in a calculated drawing power of less than ₹8 lakhs.

Fallacy:The unit gets penalised for efficiency — rapid working capital churn is misread as under-capacity. The sanctioned limit doesn’t match their actual credit absorption need, which fluctuates daily.

📉 Case Study 2: The Collateral-Rich, Liquidity-Poor Manufacturer

Profile:

• A light engineering unit in Tamil Nadu

• Sales dropped post-COVID, but land and building valued at ₹1.5 crore

• Files taxes showing ₹40 lakhs turnover, but real turnover is higher

• Most expenses are cash-based

• No GST filing done regularly

  
  

What the Banker Sees:

• Sound collateral

• Thin financial documentation

• Sporadic credit history

• Negative trends in audited ratios

  
  

What the Model Says:“Eligible for ₹8 lakhs working capital using Tandon norms and ₹4 lakhs on turnover method.”Limit is sanctioned with tight conditions and high margin requirement due to weak documentation.

Fallacy: Bank is comforted by land value but remains blind to real cash flows. Undocumented digital/UPI payments and unfiled GST returns create a perception of weak viability.

📲 Case Study 3: The Digital Services Startup With No Fixed Assets

Profile:

• App-based HR recruitment services for MSMEs

• Works fully online, collects advance payments

• No inventory, no receivables

• ₹12 lakh monthly collections, ₹2 lakh monthly expenses

• No fixed asset base; works from co-working space

  
  

What the Banker Sees:

• Zero inventory, zero collateral

• No credit history

• Profitable but not “traditional”

  
  

What the Model Says: “Ineligible under WC framework — no current assets to finance. Turnover method not applicable due to lack of audited books.”

Fallacy: Despite high monthly cash flows and nil defaults, the startup is excluded from credit due to absence of traditional WC components.

🔍 The Pattern Across These Cases:

• Efficiency is penalised.

• Digitally visible MSMEs remain invisible to traditional credit scoring.

• Documentation is a gatekeeper, not a validator.

• Cash flow visibility matters less than balance sheet presentation.

Section 5: Why This Matters — Systemic Risks and Lost Opportunities

The credit assessment blind spots discussed so far aren’t just inconvenient — they’re structurally dangerous. When assessment frameworks fail to reflect ground reality, three classes of problems emerge: misallocation, systemic risk buildup, and opportunity cost to the economy.

⚠️ 1. Misallocation of Capital: Risky Borrowers Get Rewarded

When documentation and collateral become the key to credit — rather than business viability or repayment behaviour — banks inadvertently end up:

• Sanctioning excessive limits to legacy borrowers with poor governance but clean papers

• Underserving digitally vibrant MSMEs with strong performance but weak documentation

• Relying heavily on historical balance sheets, instead of live cash flow data or bureau repayment records

  
  

This creates a credit funnel where risk is mispriced, and the wrong customers get funded. The system, in turn, breeds "lazy underwriting". This was a term that I first heard my Mentor, Sri Murali Ramakrishnan use during scenario discussions and felt absolutely apt...

🧨 2. Systemic Fragility: Overdependence on Perpetual Working Capital

When 70–80% of MSME credit is in the form of cash credit/OD limits (as confirmed by RBI and TransUnion CIBIL MSME Pulse data), it results in:

• Permanent outflow of funds from banks with no sunset date

• Interest-only repayment culture, where principal is never repaid

• Evergreening incentives, where banks roll over limits to avoid NPAs

• Weak early warning signals, because drawing power erosion is rarely questioned

  
  

This is structurally unsound. It’s a system where capital once deployed never really comes back — it just gets serviced at the interest level.

📉 3. Creditworthiness Gets Diluted Over Time

Here’s a paradox: The longer a business operates under the same cash credit facility, the lower its creditworthiness becomes, for three reasons:

1. No principal reduction, so leverage remains static

2. Utilisation stays high, reducing internal liquidity buffers

3. CIBIL or bureau records reflect constant exposure, but not improvement in repayment capacity

   
   

The business may be making profits — but from a lender’s lens, it appears stagnant or over-leveraged. This traps even good MSMEs in a cycle of perceived risk.

🚫 4. Missed Opportunities for Data-Driven Credit

India now has rich MSME-level digital data via:

• GST filings

• Account Aggregator frameworks

• Payment gateways & UPI trails

• Utility and telecom bill behaviour

  
  

  Yet, this data remains underutilised because credit models still privilege PDFs over APIs. The very MSMEs who are doing everything digitally are still being judged on legacy yardsticks.

  
  

💸 5. The Economic Cost: Latent Demand, Unexpressed Growth

The biggest fallout is this: A large segment of MSMEs remain “undercapitalised.” They have potential, demand, and operational efficiency — but they don’t have the paper trail or collateral comfort that banks need. The result is a chronic credit gap..

A 2024 study by IFC estimates India’s formal MSME credit gap at over ₹25 lakh crores. That’s a growth engine idling at half capacity.

Section 6: A Way Forward — Towards Behavioural and Dynamic Credit Models

If the existing credit frameworks are failing to capture the truth of MSME operations, the solution isn’t tinkering with margins or relaxing documentation norms — it is to fundamentally rethink what we measure, how we assess risk, and what signals we trust.

The MSME of today is not just a borrower — it's a data generator. Every invoice uploaded to GST, every UPI transaction, every payroll made through net banking — all of these are behavioural indicators of financial discipline. These real-time signals are more reflective of creditworthiness than static audited balance sheets prepared once a year, often with retrospective adjustments.

Here’s how we can start shifting the paradigm:

🔁 1. Shift from Static to Dynamic Credit Assessment

Instead of evaluating once at the time of sanction, banks must evolve to continuous credit scoring, based on live data inputs:

Traditional Model	Behavioural Model
Balance Sheet	GST Filing Pattern
Collateral	Cash Flow Consistency
Past Repayment	Bill Payment Regularity
Stock/Receivable Ageing	Digital Collections Ratio
Current Ratio	Daily Inflow/Outflow Trends

A borrower who pays vendors on time, files GST monthly without delay, and sees a rising UPI collection trend is far less risky — even if their audited ratios look weak.

📈 2. Redesign Products to Match MSME Needs

Why offer a 12-month cash credit with 25% margin when the business has:

• Weekly cash flow volatility

• Daily digital receivables

• No inventory to hypothecate?

  
  

Instead, banks should create:

• Dynamic overdrafts linked to GST or digital sales

• Working capital lines with repayment holidays based on business seasonality

• Event-based drawdowns triggered by digital invoice submission or payment gateway spikes

This is where co-lending models, neo-banking platforms, and Account Aggregator-driven products can lead.

🛡 3. Build Risk Models That Recognise Positive Behaviour

Today, MSMEs get penalised for a bounced cheque — but rarely rewarded for timely EMI payments. Future risk models must reward behaviours like:

• Timely GST filing (compliance score)

• Consistent credit inflows (stability index)

• Payment to statutory authorities (discipline index)

• Digital collections ratio (market traction score)

In other words, create a Credit Merit Index that doesn’t just punish default, but rewards discipline.

🤝 4. Regulators Must Drive Ecosystem-Wide Change

This shift won’t happen unless regulators take the lead. RBI and SIDBI can:

• Promote behavioural risk scores alongside traditional CRISIL ratings

• Encourage public-private data collaboratives (e.g., GSTN + TReDS + UPI data)

• Create regulatory sandboxes for MSME cash flow-based lending

• Mandate sunset clauses for OD/CC limits with review triggers

  
  

Just as the UPI revolutionised payments, India can lead the world in cash-flow-based MSME credit — if only the ecosystem aligns.

Section 7: Conclusion — Rewriting the Credit Code

India’s MSMEs are not weak; they are under-read. The problem isn’t with their ambition, effort, or even performance. It lies in how we, as lenders and regulators, read their story — with obsolete lenses, outdated yardsticks, and mechanical checklists.

We must stop treating credit assessment as a forensic audit of the past. It must become a forward-looking, behaviour-sensitive, dynamically adjusting tool. In a world where data flows in real time, credit too must flow in real time — calibrated not by what the borrower shows, but by what the borrower does.

The current methods — however time-tested — have run their course. It’s time to rewrite the credit code.

By shifting focus from paper to behaviour, from projections to patterns, and from compliance to conduct, India can unlock the true potential of its MSME sector — and with it, the next wave of inclusive economic growth.

The challenge is not technical. The technology exists. The data exists. What we need is the will to look again, rethink, and redesign.

The MSME of today is ready for tomorrow. Is our credit system?

Disclaimer:

The views and opinions expressed in this article are solely those of the author and do not necessarily reflect the official policy or position of any institution, employer, or agency. The information provided is for general informational and research purposes only and should not be construed as professional financial or regulatory advice. While every effort has been made to ensure the accuracy and completeness of data cited herein, the author does not accept responsibility for any errors or omissions or for any outcomes resulting from the use of this information. Readers are encouraged to consult official publications and professional advisors before making any financial decisions.