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Alternative-data credit scoring: lending to the credit-invisible

AIBy: Farzad Didehbaz2 min readSource: IBENA
Alternative-data credit scoring: lending to the credit-invisible

1Introduction

Traditional scoring relies on loan and cheque history, leaving young people, micro-businesses and freelancers unscored.

2Discussion

Alternative data — bill payments, account flows, instalment history, income patterns — combined with machine learning can estimate risk more accurately.

3Conclusion

Two conditions are essential: informed customer consent, and transparent, fair models. Regulators should define clear rules.

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Sources

  1. IBENA ↗
  2. MBRI ↗
همفکران فناوری شریفThis article summarises the official sources cited, prepared by the Hamfekran Fanavari Sharif team for finance leaders.
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