Featured Essay
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From Scorecards to AI: Why Automating Credit Decisions Is Harder Than It Looks
17 minutesWhat happens when a credit model becomes more confident than the evidence beneath it? Credit automation works best when the borrower, data and decision are predictable. Outside that boundary, better models can create greater confidence without greater understanding. From scorecards and machine learning to AI, the real challenge is knowing…
More Essays
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How are ‘Global Systemically Important Banks’ (G-SIB) monitored under BASEL
4 minutesFailure of a Systemically Important Bank amplifies the impact on world economy for two reasons. Firstly, banking services in many countries rely heavily on these…
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Credit Evaluation: How much information is Enough?
4 minutesHow much information is enough for credit evaluation? For a streamlined process a delicate balance needs to be maintained between timeliness and need for facts.…
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Helicopter Money as a Monetary Policy tool : Benefit and Risks
4 minutesHelicopter Money is a monetary policy concept proposed by economist Milton Freidman to overcome the liquidity and rate transmission challenges. However like everything else in…
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Retail Banking: The DIRECT model for Sales Excellence
3 minutesWith short sales cycles, low product differentiation and high competition it is critical that the Retail Banking teams follow a well thought out plan to…
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Payday Loans – Boon or Bane?
3 minutesPayday Loans is still a nascent category in India. But digital Lenders are finding their feet and formalising the segment. Mrityunjay Shahi explains Payday lending…
Topics
Lending Logic
How lenders assess borrowers, deal with uncertainty, and make credit decisions under imperfect information.
Policy Logic
How policy priorities, regulatory choices, and institutional trade-offs shape banking outcomes.
Banking Technology
How technology, data, and digital infrastructure are reshaping banking, from internal systems to ecosystem-wide rails.
About FrankBanker
Financial institutions follow perfect logic to absurd destinations. In these pages we explore how they land up there. We are practitioners who have spent decades as bankers, advisors and builders, learning our lessons on what goes wrong, the hard way. These pages aim to help evaluate the why, why not, and occasionally, how of banking and related technology. Our research team builds practical, information-rich Banker’s Guides worth keeping.