The Fintech Cauldron- Loan Risk Calculation in SME Lending | Data Sutram

The Fintech Cauldron- Loan Risk Calculation in SME Lending

FinancialLocation Intelligence
Samriddhi Ganguly

Samriddhi Ganguly

September 9, 2021

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Chicken Or Egg Problem

The microfinance and SME lending sector in a developing nation like ours poses a perennial challenge. While SMEs contribute to 95% of the industrial units, they lack the much necessary 5Cs of creditworthiness. The eligibility threshold for loan approval for MSMEs sets the bar high for them to cross.

· The Small and Medium Enterprise entrepreneurs cannot pledge collateral

· Lack of financial backing generates poor credit score

· Banks reject loan applications fearing default

· Micro merchants fail to develop a credit history

This vicious cycle goes on like an infinite loop, begging for policies to break the chain of the chicken and egg problems.

A Never-Ending Loop of SME Finance Fiasco

The Fintech Route

Spotting a viable market for digitizing the financial merchant lending chain, fintech firms have taken the lead in reviving the Indian economy. The gigantic chunks of data scattered around have the potential to revolutionize the lending ecosystem.

Not solely relying on traditional credit bureau data, the fintech boom in India mines out alternative data that fuels decisions, enhances the underwriting and risk evaluation process for SME Loans. With banks still lagging far behind the digital curve, startups like MobiKwik, Lending Card are leveraging alternate data for risk evaluation and loan disbursement under minutes.

Alternate Credit Scoring parameters

Bridging The Credit Gap

In the present era, credit history is not a must-have for SMEs. Nor is collateral. An amalgamation of financial services with technology drives alternative risk scoring algorithms, that ease the cumbersome SME lending process.

  • The analysis of magnanimous data available from alternate sources like Utility Bills, Rental Bills, Payments, POS Terminals gauge the business potential of a micro merchant.
  • Geospatial data adds a cherry to the cake with a deep dive into granular analysis about the creditworthiness of a region.
  • Location profiling based on parameters like affluence, age, customer footfall, merchant density, and high street score generates a location scorecard that indicates the business propensity of the region.

Combining all these, fintech platforms become the guardian angels for SMEs, with their enhanced risk analysis and loan approval with minimum processing time.

The transition from the nuances of traditional loans to microloans in a minuscule time period, loan against card swipe, Peer to Peer lending, merchant cash advance pushed the MSME sector forward, guaranteeing smoother operations and financial flow.

Leveraging the Power of Location Intelligence for Loan Risk Calculation

Towards A “Trillion Dollar Economy”?

In a nation teeming with 1.3 billion people, only half of which comes under the gambit of formal finance, fintech serves as Noah’s Arc that provides space for the underbanked. That businesses in Tier 2 and Tier 3 markets, Kirana stores, and SMEs are finally getting some much-deserved credit options is a boost to the economy and promises growth. The fintech cauldron has the potential to churn the elixir of SME lending and liquidity to turn the ambitious dream of achieving a $5 trillion economy into reality.

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