Product analytics for fintech
Datalyze is a product analytics consultancy for fintech apps in payments, lending, investing and insurance. We find where users stall between sign-up, KYC and their first transaction, why payments fail, and what brings users back to transact again.
What fintech founders ask us, again and again
Why do users sign up but never finish KYC?
What's usually going onKYC is tracked as one event, or run by a vendor SDK that sends nothing back. You see the drop, not the step.
Why don't verified users transact?
What's usually going onPassing KYC isn't activation. Users hit an empty wallet or a bank to link, and dashboards stop at "KYC complete".
Why do payments fail, and how often?
What's usually going onGateway, bank, UPI app and your app each report failures differently, so a bad provider hour looks like users leaving.
Why don't users transact again?
What's usually going onTeams count first transactions, but major revenue comes much later.
Where do loan applicants drop off?
What's usually going onRejections and abandonment look the same in most funnels, so product problems hide behind credit decisions.
How do we track users without leaking personal data?
What's usually going onPAN, phone numbers and balances slip into event properties and sit in a third-party tool.
What we do about each one
- 01KYC
Track every KYC step, including the vendor's
We map the full KYC journey and track each screen and each vendor response with its failure reason, then build a step-by-step funnel. That shows whether you're losing people to a blurry document, a failed PAN match or a slow bank check.
- 02First transaction
Measure the gap between verified and transacting
We treat the first transaction as activation and track what happens between approval and money moving: bank linked, wallet funded, first amount chosen. Then we find where the drop is and design nudges and defaults that shorten it.
- 03Payments
Monitor payment success by provider
We log every payment attempt with its method, bank, provider and failure code, reconcile it with gateway data, and report success rate by provider.
- 04Repeat usage
Find what makes the second transaction happen
We build cohorts on transaction frequency and find the behaviours that separate repeat users from one-time ones, such as setting up autopay or a SIP in the first week.
- 05Lending
Separate credit decisions from product drop-off
We track the application, bureau check, offer and disbursement as separate events with the decision and its reason. Rejections are counted apart from abandonment, so you can see which losses the product can fix and which come from credit policy.
- 06Data privacy
Design tracking that keeps personal data out
We write the tracking plan with a privacy rule for every property, hash identifiers before they leave the app, and send amounts as ranges where exact values aren't needed. We also audit what's already in your tool.
Fintech teams we've worked with
CRED's payment routing was leaking money on both success rate and cost. We built a linear-programming routing engine plus a real-time outage-detection model, taking success rate up 7%, cost down 12%, and provider outages down 93% month over month.
Read the case studySpeedyloans, a US lending platform, was emailing millions of borrowers who were unlikely to come back. We built a scoring model on loan behaviour, engagement and recency to rank who to contact. Email cost fell 30% while re-engagement rose 1%.
Read the case studyTermPlus had a half-finished setup and data spread across separate systems. We built the full analytics infrastructure, brought every source together under one user identity, and built the dashboards the team runs on.
Read the case studyThese are real results from payments, lending and financial services teams.
Book a callWhat teams say after working with us
Fintech analytics questions
Mixpanel, Amplitude or PostHog for a fintech app?
All three work. The deciding question is usually data residency and personal data. PostHog can be self-hosted, so events never leave your infrastructure. Mixpanel and Amplitude offer regional data residency, and Mixpanel has an India region. We implement all three and help you choose based on your compliance needs.
How do you handle personal data and compliance?
We keep personal and financial data out of the analytics tool by design. Every property in the tracking plan is marked as safe, hashed or excluded, identifiers are hashed before they leave the app, and amounts are sent as ranges where exact values aren't needed. We also audit existing data for anything that got through.
Can you track payment failures across gateways and UPI?
Yes. We log every attempt with the method, bank, provider and failure code, and reconcile it with the gateway's own data so the numbers match. That's what tells you whether a spike in failures is one provider, one bank or your own app.
Do you work with lending, investing and insurance apps?
Yes. We've worked with payments (CRED), lending (Speedyloans) and financial services (TermPlus). The funnels differ, but the pattern is the same: onboarding with verification, a first transaction or application, then repeat usage.
Where do most fintech teams start?
With the funnel from sign-up to first transaction. It's usually where the biggest drop is, and tracking it properly often shows one KYC step or the empty-wallet moment losing most users. If your current tracking can't show it, we start with a one to two week audit.