Most fintech founders can rattle off their total downloads and monthly active users in seconds. Ask them which marketing channels actually deliver profitable users, or what their Day 7 retention looks like by acquisition source, and you'll get a long pause followed by "we're still building that dashboard."

The metrics that separate growing fintech apps from ones burning cash aren't the vanity numbers in your pitch deck—they're the unit economics, attribution data, and retention cohorts that show whether your business model actually works. This guide covers the core growth, revenue, engagement, and attribution metrics fintech apps track to make faster decisions, prove ROAS, and scale profitably.

Core Growth Metrics Every Fintech App Tracks

Customer acquisition cost (CAC), lifetime value (LTV), and monthly recurring revenue (MRR) form the foundation of fintech unit economics. You can't know if your business model works until you track what it costs to acquire each user and what they generate in return. Tracking CAC by channel—not just blended across all sources—reveals which campaigns on Meta, Google, or TikTok actually deliver users profitably and which ones burn cash.

Customer Acquisition Cost (CAC)

CAC is total marketing spend divided by new users acquired in that period. Spend ₹5 lakhs on Meta ads and acquire 1,000 users? Your CAC is ₹500 per user.

Most fintech apps track blended CAC across all channels. That hides the truth. Your Instagram influencer campaign might deliver ₹200 CAC while Google App Campaigns cost ₹800—blending them shows ₹500 and masks which source is bleeding money. Track CAC by source (organic, paid social, search, referral) so you know where to double down and where to cut.

Monthly Active Users (MAU) and Daily Active Users (DAU)

MAU counts unique users who open your app at least once in a month. DAU counts users who open it daily. The DAU/MAU ratio shows stickiness—how often users return after their first session.

For fintech apps, a DAU/MAU ratio above 20-25% signals strong habit formation. Users are checking balances, making payments, or tracking investments regularly. Lower ratios mean your app is transactional—users install it, complete one action, then forget it exists.

User Activation Rate

Activation is the moment a user completes your app's core action: first payment sent, KYC completed, bank account linked, or first investment made. Installs don't matter if users never activate.

Activation rate separates real users from tire-kickers. If 1,000 people install your lending app but only 200 complete KYC and apply for a loan, your activation rate is 20%. That 80% drop-off points to onboarding friction—too many steps, unclear instructions, or document upload failures.

Time to First Value

Time to first value measures how quickly a new user experiences your app's core benefit. For a payment app, it's the time from install to first successful transaction. For an investment app, it's the time from signup to first trade.

Shorter time to first value correlates with better retention. Users who get value fast come back—users who hit friction during onboarding churn before you ever monetize them. Fintech apps with complex KYC processes often see users drop off between Day 1 and Day 7 because it takes too long to complete verification and start using the product.

Unit Economics That Make or Break Fintech Success

Unit economics determine whether your business model is profitable at the user level. Investors scrutinize LTV, CAC ratios, and payback periods in every pitch deck because the numbers reveal if you're building a sustainable company or just renting users with paid ads.

Lifetime Value (LTV)

LTV is the total revenue you expect from a user over their entire relationship with your app. You calculate it by multiplying average revenue per user (ARPU) by the average lifespan of a user, adjusted for churn.

For fintech, LTV varies wildly by business model. A digital lending app might see ₹10,000+ LTV from repeat loans, while a UPI payment app might generate ₹500 LTV from transaction fees over two years.

LTV to CAC Ratio

LTV to CAC ratio shows whether you're spending the right amount to acquire users. Divide LTV by CAC. A ratio of 3:1 means you earn ₹3 for every ₹1 spent acquiring a user—generally considered healthy for fintech apps.

Ratios below 2:1 signal unsustainable growth. You're spending too much to acquire users relative to what they generate. Ratios above 5:1 suggest you're under-investing in acquisition—you could be growing faster by spending more on channels that already work.

Payback Period

Payback period measures how long it takes to recover CAC from a user's revenue. If your CAC is ₹500 and users generate ₹100 per month, your payback period is five months.

Shorter payback means faster cash flow. Lending and investment apps typically see longer payback periods (6-12 months) because users take time to generate revenue, while payment and wallet apps can hit payback in 2-4 months if transaction frequency is high.

Contribution Margin

Contribution margin is revenue per user minus variable costs: payment processing fees, fraud losses, and customer support costs. This shows true profitability, not just top-line revenue.

Many fintech apps look profitable on paper until you account for costs like:

• Payment processing fees: 1-2% of transaction value to Razorpay, Stripe, or card networks

• Fraud and chargeback losses: Often 2-5% of transaction volume, especially high for lending and wallet apps

• Customer support costs: KYC issues, transaction disputes, and onboarding help add up fast

If your contribution margin is negative, you lose money on every user—even before accounting for CAC.

Engagement and Retention Metrics for Mobile-First Fintech

Retention is the single best predictor of long-term success. Fintech apps that don't retain users burn cash acquiring replacements every month.

Day 1, Day 7, and Day 30 Retention

Retention cohorts track what percentage of users return after install. Day 1 retention shows onboarding quality—did users find value immediately? Day 7 shows habit formation—are users coming back regularly? Day 30 shows long-term stickiness.

Fintech retention is typically lower than social or gaming apps because use cases are transactional. You might see 40-50% Day 1 retention, 20-30% Day 7, and 10-15% Day 30 for payment apps. Investment and neobanking apps often retain better because users keep funds in the platform.

Churn Rate by User Segment

Churn is the percentage of users who stop using your app in a given period. Segmenting churn by user type reveals where to focus retention efforts—high-value users churning costs more than low-value users.

For fintech, churn often spikes after specific events: first transaction failure, KYC rejection, or account lockout due to fraud detection. Tracking churn by segment (organic vs. paid, high-value vs. low-value, geography) shows you which groups are at risk and why.

Feature Adoption Rate

Feature adoption tracks what percentage of users engage with specific features: bill pay, auto-invest, referral programs, or premium subscriptions. High adoption of revenue-driving features means better LTV—users who engage with multiple features stick around longer and generate more revenue.

Low adoption signals product-market fit issues. If you built a savings feature but only 5% of users try it, either they don't understand it or they don't want it.

Session Frequency and Duration

Frequency measures how often users open your app. Duration measures how long they stay. For fintech, frequency matters more than duration—users want fast, frictionless transactions, not long browsing sessions.

A payment app user who opens the app 10 times a week for 30 seconds each time is more valuable than one who opens it once a week for five minutes. High frequency signals habit formation and trust.

Revenue Metrics That Prove Sustainable Growth

Revenue metrics show whether your fintech app is building a scalable, repeatable business model. Investors ask for MRR, NRR, and ARPU in every pitch deck.

Monthly Recurring Revenue (MRR)

MRR is predictable revenue from subscriptions or recurring fees: premium accounts, SaaS tools for businesses, or subscription-based credit monitoring. It's easier to forecast and value than one-time transaction revenue because it's stable and compounds.

Not all fintech models have MRR. Payment and wallet apps rely on transaction fees (variable revenue), while lending apps generate interest income (lumpy and dependent on loan book growth).

Net Revenue Retention (NRR)

NRR measures revenue retained from existing users, including upsells and cross-sells, minus churn. An NRR above 100% means you're growing revenue without needing new users—a sign of strong product-market fit.

If you start a month with ₹10 lakhs in revenue from existing users, upsell ₹2 lakhs in premium features, and lose ₹1 lakh to churn, your NRR is 110%. This metric matters most for subscription-based fintech models (neobanks, investment platforms) where expanding revenue per user drives growth.

Average Revenue Per User (ARPU)

ARPU is total revenue divided by active users. It shows monetization efficiency—how much value you extract from each user.

For fintech, ARPU varies by model: lending apps have high ARPU (₹1,000-5,000+ per user annually), wallet apps have low ARPU (₹50-200) but high volume. Track ARPU by cohort and segment to see if newer users monetize faster than older ones.

Transaction Volume Growth

Transaction volume (also called Total Payment Volume or TPV) tracks the total value of transactions processed through your platform. For payment and wallet apps, TPV growth is often more important than user growth—it shows deepening engagement and trust.

A user who sends ₹5,000 through your app in Month 1 and ₹15,000 in Month 3 is growing their TPV. That's a signal they trust your platform for larger transactions.

Operational Metrics by Fintech Model

Different fintech business models require different operational KPIs. Track the metrics that match your revenue model and user behavior.

Payment and Wallet Apps

Transaction success rate measures the percentage of attempted payments that complete without errors. Failed transactions—due to payment gateway issues, insufficient balance, or fraud blocks—erode trust and drive churn.

Key metrics to track:

• Transaction success rate: Aim for 95%+ success; anything lower signals technical or UX issues

• Average transaction value: Shows user spending behavior and trust level

• Repeat transaction rate: Users who transact 3+ times in the first month typically retain

Digital Lending Platforms

Loan approval rate is the percentage of applications approved. Default rate is the percentage of loans not repaid. Balancing the two is the core challenge for lending fintechs—approve too many and defaults spike, approve too few and growth stalls.

Track:

• Loan approval rate: Typically 30-50% for consumer lending

• Default rate: Varies by loan type; personal loans see 5-10%

• Loan book growth: Total outstanding loan value

Neobanks and Digital Banking

Deposit growth tracks total funds held in user accounts. Account funding rate measures what percentage of users deposit money after signup—a critical activation metric for neobanks.

Key metrics:

• Deposit growth: Month-over-month increase in total deposits

• Account funding rate: Percentage of signups who deposit funds

• Cross-sell rate: Users adopting multiple products (savings + credit + investment)

Trading and Investment Apps

Assets under management (AUM) is the total value of user portfolios. Trading frequency measures how often users buy or sell. Investment apps have high LTV but are sensitive to market conditions—users churn during downturns when portfolio values drop.

Track:

• Assets under management (AUM): Total value of user portfolios

• Trading frequency: How often users transact

• Portfolio retention: Percentage of users who keep funds invested over time

Trust and Compliance Metrics That Build Confidence

Fintech apps handle money and sensitive data. Trust and compliance metrics prove your app is reliable, secure, and audit-ready.

Transaction Success Rate

Transaction success rate measures the percentage of transactions that complete without errors. Failed transactions—due to payment gateway downtime, insufficient funds, or fraud blocks—erode trust faster than almost anything else.

Track success rate by payment method (UPI, cards, net banking) to identify weak points. If UPI transactions succeed 98% of the time but card transactions only 85%, you have a gateway or integration issue to fix.

KYC Completion Rate

KYC (Know Your Customer) is the identity verification process required by regulators. Completion rate shows how many users finish onboarding—low completion means friction in your flow.

Common drop-off points include document upload failures (poor image quality, unsupported formats), Aadhaar/PAN verification delays, or too many steps before users see value. If your KYC completion rate is below 50%, you're losing half your potential users to onboarding friction.

Fraud Detection Accuracy

Fraud detection accuracy tracks how well your system catches bad actors without blocking legitimate users. High false positives (blocking real users) hurt conversion and trust—users who get flagged as fraudulent often churn immediately.

Fintech apps balance fraud prevention with user experience. Too strict and you block good users; too loose and you lose money to fraud.

Customer Support Resolution Time

Resolution time measures how quickly your team solves user issues: failed transactions, account lockouts, KYC rejections. Fast resolution builds trust—slow support drives churn, especially for money-related problems.

Track:

• First response time: How quickly support acknowledges a ticket

• Resolution time: How long it takes to fully solve the issue

• Ticket volume by category: Reveals common pain points

Attribution Metrics for Fintech Marketing Campaigns

Attribution metrics show which marketing channels and campaigns drive installs, transactions, and revenue. Without clean attribution, you're guessing where to spend your budget.

Return on Ad Spend (ROAS) by Channel

ROAS is revenue generated divided by ad spend. Tracking ROAS by channel (Meta, Google, TikTok, influencer campaigns) reveals which sources are profitable versus which ones burn cash.

Blended ROAS hides underperforming channels. If Meta delivers 4x ROAS and Google delivers 1.5x, blending them shows 2.75x and masks the fact that Google is barely breaking even. Linkrunner unifies attribution data from Meta, Google, TikTok, and other networks in one dashboard—you see true ROAS by channel without reconciling spreadsheets or screenshots.

Install to First Transaction Rate

Install to first transaction rate tracks what percentage of installs complete a revenue-generating action: first payment, first investment, or first loan application. Low conversion signals onboarding friction or poor targeting—you're acquiring users who don't convert.

Fintech apps often see drop-off at KYC or bank linking steps. If 1,000 users install your app but only 300 complete KYC and 150 make a first transaction, your install-to-transaction rate is 15%.

Cross-Platform Customer Journey Tracking

Users often discover your app on one device (Instagram ad on mobile) but complete KYC or transactions on another (desktop web). Tracking the full journey across platforms reveals hidden drop-off points and attribution gaps.

Linkrunner's identity stitching connects user actions across devices and sessions—you see the complete journey from ad click to revenue, not just the last touchpoint. This matters for fintech because users frequently switch devices during high-friction actions like KYC or large transactions.

Marketing Mix Efficiency

Marketing mix efficiency measures how well your overall budget is allocated across channels. Are you over-investing in expensive channels and under-investing in efficient ones?

Track:

• Channel contribution to revenue: Which channels drive the most paying users, not just installs

• Budget allocation vs. performance: Are you spending 40% of budget on a channel that delivers 15% of revenue?

• Incrementality: Which channels bring new users versus cannibalizing organic growth

Turn Metrics Into Growth With Unified Analytics

Tracking all your metrics across dashboards, spreadsheets, and ad platforms is slow and error-prone. Growth teams waste hours reconciling data instead of making decisions.

Linkrunner unifies attribution, deep linking, and marketing analytics in one platform. You see installs, revenue, ROAS, and retention by channel in real time—no more stitching together reports from five different tools. Linkrunner's AI surfaces underperforming campaigns and suggests where to shift budget, so you move from manual reporting to always-on intelligence.

Request a demo to see how fintech apps track metrics that matter in one place.

FAQs About Fintech Metrics

How often do fintech apps review their key metrics?

Daily for real-time metrics like transaction success rate and ROAS, weekly for engagement and retention cohorts, monthly for unit economics and revenue trends.

Which metrics do early-stage fintech startups prioritize?

Focus on CAC, activation rate, Day 7 retention, and transaction success rate—the metrics that show whether your product works and users stick around before scaling paid acquisition.

What are typical LTV to CAC ratio benchmarks for fintech apps?

Healthy fintech apps aim for 3:1 or higher, but it varies by model—lending and investment apps can sustain higher CAC due to higher LTV, while payment apps need lower CAC due to lower ARPU.

How do I track attribution metrics across web and mobile platforms?

Use a mobile measurement partner (MMP) like Linkrunner that stitches user identity across devices and platforms—you see the full journey from ad click on mobile to transaction on web (or vice versa).

What is the difference between vanity metrics and actionable metrics in fintech?

Vanity metrics like total downloads or social media followers look good but don't drive decisions—actionable metrics like ROAS by channel, churn rate by segment, and payback period tell you exactly where to invest or fix problems.