The Credit Gap No One Is Fixing Properly

Micro, Small, and Medium Enterprises (MSMEs) form the backbone of India’s economy. They contribute over 30% of India’s GDP, employ more than 120 million people, and power everything from local manufacturing and trade to essential services in rural India.

Yet, more than 80% of MSMEs lack access to formal credit.
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The reason isn’t just about documentation or risk—it’s about mindset. Most MSME lending is still built on a personal loan underwriting model. This outdated lens looks at the individual, not the business. It ignores cash flows, business patterns, and real-world repayment behavior.
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To truly close the credit gap—and unlock profitable growth for lenders—we need a new approach: contextual, domain-led lending.

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The Flawed Assumption: MSMEs = Personal Loan Borrowers

Today, most MSME borrowers are evaluated using personal credit scores and rigid eligibility checklists. While credit bureau data is useful to assess repayment intent, it doesn't offer insight into business health or operational strength.
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Consider these examples:

• A kirana store owner with consistent weekly sales but low credit visibility
• A dairy entrepreneur earning seasonally, based on livestock cycles
• A distributor with regular bank inflows but no formal balance sheet
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All three are viable borrowers. But most lending systems lump them into the same category—applying a one-size-fits-all model that leads to:
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• Low or mismatched credit limits
• High turnaround time (often 15–20 days per disbursal)
• Missed lending opportunities in Tier 3/4/5 towns
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This lack of context leaves lenders exposed to higher NPAs and slower growth, while MSMEs stay underfunded.
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What Contextual, Domain-Led Lending Looks Like
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A domain-led lending model shifts the focus from individual profiles to business models. It’s about understanding:

• What sector the MSME operates in (retail, agriculture, services, etc.)
• How and when it earns money (daily, weekly, seasonally)
• Where money flows (bank accounts, cash, digital wallets)
• What patterns emerge in their cash flows, banking transactions, and expenses
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At AllCloud, we’ve built domain-specific workflows for key MSME sectors:

• Retail (kirana, FMCG distributors)
• Agriculture & Allied (dairy, poultry, agri input sellers)
• Manufacturing (micro-units, home-based production)
• Services (local transporters, field agents, salons, etc.)
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These workflows allow lenders to build realistic credit assessments, improve loan utilization, and align repayment structures with income cycles.

Why Collections Must Match Business Realities
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Let’s look at common mismatches:

• A kirana store earning daily is placed on a monthly EMI cycle
• A poultry farm with seasonal sales is expected to pay fixed monthly dues
• A distributor with invoice-based payments is not aligned with due date flexibility

Smart collections are about matching repayment logic to cash inflow patterns. And this isn't a manual process anymore.
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With platforms like AllCloud, lenders can automate repayment logic by setting:

• Weekly, fortnightly, or custom repayment frequencies
• Dynamic installment dates based on cash flow cycles
• Repayment modes via eNACH, UPI 2.0 recurring, or field collections
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This not only reduces defaults—it builds borrower trust.