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Fintech for Startups
Playbooks and case studies covering fintech for startups.
How KarroFin Scored 250K Users Without a Credit Bureau
KarroFin's underwriting model was rejecting creditworthy borrowers for the wrong reason: absence of bureau data. Here's the engineering call that fixed it, and why chasing the bureau score is the wrong target for any lender serving thin-file users.
Your AI Feature Has a Trust Problem, Not an Accuracy Problem
Your model is 92% accurate. Your acceptance rate is 11%. The fix is not a better model. The fix is making the output legible at the moment a user has to act on it.
Questions to Ask Before Hiring an AI Fintech Dev Partner
Most AI fintech vendors demo well and use the right words. These 15 questions separate the ones who have actually shipped under regulatory and credit-risk constraints from the ones who haven't.
How KarroFin Scaled AI Credit Scoring Without Killing Approval Rates
KarroFin's credit model wasn't broken. No alerts, no errors, no engineering fires. But approval rates were quietly compressing at scale — and the fix wasn't where the data science team was looking.
Feature Stores Explained: Why Your ML Models Stale Out
Your credit risk model nailed backtesting but production accuracy keeps slipping. The culprit is rarely the model — it's a silent mismatch between how features are computed at training time and at inference. Here's what a feature store actually does about it.
5 Mistakes We See Teams Make Shipping AI to Thin-File Users
Most thin-file AI lending models don't fail because the architecture is wrong. They fail because the team never audited what happens after the first batch of rejections starts retraining the model. Here are the five failure modes we see most often.
Stripe Radar vs. Custom ML Fraud Models: Which Wins?
Stripe Radar's false-positive problem in emerging markets isn't a model sophistication issue — it's a training data representation issue. Here's how to decide between Radar, a third-party ML layer, and a custom model trained on your own transaction graph.
Questions to Ask Before Hiring an AI Credit Scoring Vendor
Most credit scoring demos look great on the vendor's data and quietly fail on yours. Here are the adversarial questions to ask before signing — with what good and bad answers actually sound like.