Mini-project Banking & Fintech Case Studio

Payment success rate dashboard

Inspired by publicly reported work at Razorpay

Find where online payments fail (method, bank, time) and show a merchant where they lose money.

The brief

Razorpay has written about payment success rates: how failures by bank, method and gateway cost merchants revenue, and how smart routing helps. Build the analysis a merchant needs first: generate realistic payment-attempt logs, measure success rates by method, bank, gateway and hour, find the biggest losses, and present them in a dashboard. Good looks like: a clearly documented simulation, success rates with confidence intervals, losses in rupees, and a dashboard a finance manager understands.

Read the case first

What Razorpay has said in public about this kind of work, on its own pages:

Make it your own

Model a merchant you know: a college fee portal, a small online store or a local gym's subscriptions. Base the simulated method mix on what that merchant's customers actually use.

AITeky has no link with Razorpay, which has not reviewed or endorsed this brief. The brief only draws on what the company has published, uses open data rather than its data, and is a learning exercise: don't present your project as Razorpay's work or system.

What you will build

Design and generate payment-attempt logs (methods, banks, gateways, failure reasons)
Compute success rates with confidence intervals
Find the largest revenue losses
Compare with UPI ecosystem statistics where possible
Build a dashboard for a finance manager

Free, open data to build it with

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