2Tracks
6Problem Statements
₹30,000Prizes
1Track 1: Financial Inclusion for the Underbanked & Informal Economy 3 Problem Statements
Financial Inclusion for the Underbanked & Informal Economy
Problem Statements
ps111. Trust Scoring for the Credit-Invisible
Find a way to establish trust for someone with zero formal credit history, using signals beyond a traditional credit score.
Challenge
Millions of vendors, gig workers, and small farmers are excluded from formal credit — not because they're unreliable, but because banks have no way to read their reliability without paperwork or transaction history.
Objective
Explore what everyday signals — beyond a bank statement — could reasonably stand in for a credit history, and how you'd turn that into something a lender could actually trust. Teams are free to choose their own data sources, scoring approach, and the financial product (credit, savings, or insurance) it ultimately supports.
ps122. Reimagining Onboarding for First-Time Users
Rethink what it takes to onboard a low-literacy or first-time user into a financial product.
Challenge
Even well-designed products for underbanked users often go unused, because onboarding assumes digital literacy, English fluency, and trust many first-time users simply don't have.
Objective
Think about where trust and understanding actually break down for a first-time user, and what a fundamentally different onboarding experience could look like. The format, language, and medium are entirely up to the team.
ps133. Designing for Income Volatility
Find a way to make financial products work for people whose income doesn't arrive in predictable monthly amounts.
Challenge
Most financial products assume a steady paycheck, but gig workers, daily-wage labourers, and farmers earn in irregular bursts — making standard repayment or savings schedules a poor fit.
Objective
Consider what a savings, credit, or insurance product would look like if it were built around irregular income instead of a fixed salary. Teams are free to decide which product and which segment of irregular earners to focus on.
2Track 2: Fraud Detection & Financial Crime Prevention 3 Problem Statements
Fraud Detection & Financial Crime Prevention
Problem Statements
ps214. Real-Time Fraud Explainer
Find a way to flag a suspicious UPI transaction in real time, in a way the user can actually understand and trust.
Challenge
As digital payments scale, so does fraud — fake payment requests, scam loan apps, and laundering schemes that evolve faster than static checks can keep up with.
Objective
Consider what actually makes a fraud alert useful in the moment — timing, clarity, or the action it enables. Teams have full freedom over the detection approach and how (or whether) it intervenes in the transaction itself.
ps225. Tracing Financial Crime Across Patterns
Find a way to catch financial crime that only becomes visible across many transactions or accounts over time.
Challenge
The most damaging fraud rarely shows up in a single transaction — it's spread deliberately across many small transfers and accounts to avoid detection, faster than human analysts can trace.
Objective
Think about what it would take to spot a pattern that's deliberately spread out to avoid detection, and who should act on that finding once it's flagged. The scope, method, and level of human involvement are open to the team to define.
ps236. Verifying Legitimate Lenders
Find a way to help someone tell a genuine loan app or lender apart from a fraudulent one before they hand over money or documents.
Challenge
Fake loan apps prey on people who are already financially stressed and looking for quick credit, and there's no easy way for an everyday user to check legitimacy before it's too late.
Objective
Think about what information would actually let someone tell a real lender apart from a fake one, and at what point in their search that check needs to happen. Teams are free to decide the format — a lookup tool, a browser check, a verification badge, or something else.
