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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Deep-Tier SCF is Magical, But Here’s Why It Doesn’t Work
8 minutesDeep-tier Supply Chain Finance (DTSCF) is often sighted as a magic spell that could transform the funding landscape for SMEs. While the concept has caught…
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Credit Risk Blindspots: Hidden Biases in Lending
9 minutesBias is an inherent human tendency, and recognising and minimising it requires deliberate effort. No matter how advanced the financial models or how experienced the…
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SME Lending Channel Strategy: Key Success Factors
7 minutesLenders—Banks, NBFCs, or FinTechs—face the classic ‘Knapsack Problem’ while trying to create an optimal SME lending distribution structure. Each channel mix—branches, digital, phygital, own, agents,…
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Designing Loan Products: A ‘First Principles Thinking’ Blueprint
9 minutesIn Banking, there are no barriers to imitation. Any lender-Bank, NBFC, or Fintech, can easily build a Loan product suite simply by following the leader.…
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Hyper-Personalisation in Banking: The Paradox of Customisation
8 minutesHyper-personalisation promises to revolutionize banking by creating a “Segment of One” experience, but the path is riddled with complexities. Challenges of execution and technological demands…
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.