Your fintech app drove 50,000 installs last month. Your product dashboard shows 35,000 MAU and hundreds of daily transactions. Then your CFO asks: "How many users who installed last month are actually depositing money?" You pull reports and discover that only 2,800 users (5.6%) who installed completed their first deposit. The other 47,200 users are either stuck in KYC, exploring without committing, or churned before experiencing core value.

This is the measurement gap that separates growing fintech products from those that burn acquisition budgets without building sustainable user bases. Generic event tracking (installs, sessions, screen views) tells you people are using your app. Financial services event tracking tells you whether they're trusting you with their money, which is the only metric that matters for fintech unit economics.

Fintech apps require specialised event taxonomies because the conversion funnel is fundamentally different from ecommerce, gaming, or social apps. Users must complete regulatory verification, link financial accounts, overcome psychological friction around money, and develop trust before generating revenue. Each step requires specific measurement to identify drop-off points and optimise conversion.

Why Generic Event Tracking Fails for Fintech

Most mobile analytics guides recommend tracking standard events: app_opened, screen_viewed, button_clicked. These work for content apps and games where engagement itself creates value. They fail catastrophically for fintech because they don't capture the financial behaviour that determines whether users generate revenue.

Generic tracking shows you have 40,000 active users. But active doing what? Are they browsing features without linking accounts? Completing verification but not depositing? Making one transaction then churning? Without financial milestone events, you're measuring motion instead of progress.

Fintech funnels have unique friction points that generic tracking can't expose. KYC verification has 20-40% drop-off in most apps due to document quality issues, identity mismatch, or user abandonment during multi-step processes. First deposit has psychological friction where users hesitate to transfer real money despite completing verification. Transaction frequency separates engaged users from one-time experimenters.

The 10 events below represent the minimum viable event taxonomy for any fintech app. They track the complete user journey from first open through habit formation, revealing exactly where users drop off and which acquisition sources drive users who actually complete valuable financial actions.

Event #1: Account Created (KYC Initiation)

Event name: account_created

When to fire: Immediately after user completes initial account setup (email/phone verification, password creation)

Why it matters: This event marks conversion from anonymous visitor to identified prospect. Users who create accounts have expressed initial intent and cleared the first commitment threshold. This event enables you to measure what percentage of installs convert to accounts and how quickly conversion happens.

Properties to track:

• Registration method (email, phone, social_auth)

• Time to registration (minutes from install to account creation)

• Referral source (if applicable)

• Device type (iOS/Android)

Benchmark targets: 30-50% of installs should complete account creation within 24 hours for fintech apps. Higher conversion rates (above 50%) suggest strong value proposition or effective onboarding. Lower rates (below 25%) indicate friction in signup flow or unclear value communication.

Common issues detected:

If account creation rates drop suddenly week-over-week, investigate technical issues in signup flow. If certain acquisition channels show significantly lower account creation rates, their ad creative might be attracting low-intent users or setting wrong expectations.

Optimisation opportunities:

Segment account creation rates by acquisition source to identify quality channels. Track time-to-registration to find friction in onboarding flow. Users taking 15+ minutes to register likely encountered confusion or error states.

Event #2: KYC Completed (Conversion Milestone)

Event name: kyc_completed

When to fire: When user successfully completes all Know Your Customer verification steps (identity documents uploaded and approved, address verified, regulatory checks passed)

Why it matters: KYC completion is the critical conversion milestone that separates users who are serious about using your financial services from those who are exploring casually. This event enables calculation of true activation rate (percentage of accounts that complete verification) and reveals whether KYC friction is killing conversion.

Properties to track:

• Verification method (Aadhaar, PAN, passport, etc.)

• Time to completion (hours/days from account creation to KYC approval)

• Number of attempts (failed submissions before success)

• Drop-off stage (if abandoned: which verification step?)

Benchmark targets: 40-60% of account creators should complete KYC within 72 hours in well-optimised fintech apps. Lower rates indicate excessive friction, unclear instructions, or technical issues. Higher rates (above 65%) suggest strong onboarding design or highly motivated user base.

Common issues detected:

High abandonment at specific KYC steps (document upload, selfie verification, address proof) indicates UX problems or unclear requirements. Long time-to-completion (5+ days) suggests verification queue delays or insufficient user motivation to complete process.

Optimisation opportunities:

Create funnels showing progression through KYC steps. Identify where most users abandon. A/B test clearer instructions, reduced steps, or alternate verification methods. Send push notifications reminding users to complete pending verification.

Event #3: First Deposit (Activation Signal)

Event name: first_deposit_complete

When to fire: When user successfully transfers money into your app for the first time (via bank transfer, UPI, card, or any other method)

Why it matters: First deposit is the strongest activation signal in fintech. It represents overcoming psychological friction around trusting your platform with real money. Users who deposit are dramatically more likely to transact, stay active, and generate lifetime value. This event enables calculation of deposit conversion rate (percentage of KYC-complete users who deposit) and average time from verification to deposit.

Properties to track:

• Deposit amount (bucketed: under ₹500, ₹500-₹2000, ₹2000-₹10000, above ₹10000)

• Deposit method (UPI, bank transfer, card)

• Time since KYC completion

• Source campaign (which acquisition campaign drove this user)

Benchmark targets: 50-70% of KYC-complete users should make first deposit within 7 days in healthy fintech products. Lower conversion (below 40%) suggests lack of compelling use case or unclear value proposition. Higher conversion (above 75%) indicates strong product-market fit.

Common issues detected:

Long delay between KYC completion and first deposit (4+ days) indicates users aren't motivated to use product immediately. Low deposit amounts (majority under ₹500) suggest users are testing cautiously due to lack of trust or uncertainty about value.

Optimisation opportunities:

Send targeted push notifications offering first deposit incentives (bonus rewards, zero-fee promotions). Create onboarding flows that guide users toward their first deposit immediately after KYC approval. Segment first deposit rates by acquisition channel to identify which campaigns drive users with actual financial intent.

Event #4: First Transaction (Usage Confirmation)

Event name: first_transaction_complete

When to fire: When user completes their first financial transaction using your platform (payment, transfer, investment, or product-specific action)

Why it matters: First transaction confirms that users understand your product's core value and have successfully navigated the full workflow. This event measures conversion from deposited funds to actual platform usage. The gap between first deposit and first transaction reveals whether users deposit but can't figure out how to use your product.

Properties to track:

• Transaction type (payment, transfer, investment purchase, bill pay, etc.)

• Transaction amount

• Time since first deposit

• Success vs failed (to track technical issues)

Benchmark targets: 70-85% of users who deposit should complete first transaction within 48 hours. This high conversion rate is expected because users who deposit have clear intent. Lower rates suggest UX confusion or limited product utility.

Common issues detected:

If many users deposit but don't transact, your interface is confusing or your product doesn't solve the problem users thought it would. High failed transaction rates indicate technical problems with payment processing, bank integrations, or insufficient balance handling.

Optimisation opportunities:

Create guided tutorials showing how to complete first transaction. Offer incentives for first transaction (cashback, fee waiver). Track failure reasons to fix technical issues. Analyse which transaction types have highest conversion to identify most compelling use cases.

Event #5: Repeat Transaction (Habit Formation)

Event name: repeat_transaction

When to fire: When user completes their second, third, and subsequent transactions (track as distinct milestones: 2nd transaction, 5th transaction, 10th transaction)

Why it matters: Repeat transaction indicates habit formation and ongoing product utility. Single-transaction users often churn; multi-transaction users become sticky. This event enables calculation of transaction frequency patterns and identification of power users versus one-time users.

Properties to track:

• Transaction count (2nd, 5th, 10th milestone)

• Days since previous transaction

• Transaction type consistency (same type repeatedly vs varied usage)

• Average transaction value trend (increasing/decreasing)

Benchmark targets: 50-65% of users who complete first transaction should complete second transaction within 14 days. This indicates product stickiness. Lower rates suggest product solved one-time need but lacks ongoing utility. Users reaching 5+ transactions typically show 60-80% D90 retention.

Common issues detected:

If users transact once then disappear, your product may be solving a narrow use case without ongoing relevance. Long gaps between transactions (20+ days) suggest product isn't top-of-mind or lacks compelling reasons to return.

Optimisation opportunities:

Create retention campaigns targeting users after first transaction, encouraging second transaction through rewards or relevant use case suggestions. Analyse what triggers repeat transactions (promotions, scheduled needs, social reminders) to inform engagement strategy.

Event #6: Savings Goal Set (Long-Term Intent)

Event name: savings_goal_created

When to fire: When user creates any savings goal, investment plan, or long-term financial objective within your app

Why it matters: Goal-setting indicates long-term intent and mental commitment to using your platform over time. Users who set goals have higher retention and lifetime value because they've mentally committed to future behaviour. This event is particularly relevant for investment apps, neobanks, and savings-focused products.

Properties to track:

• Goal type (emergency fund, house purchase, retirement, education, general savings)

• Target amount

• Target timeline (months to goal)

• Funding frequency (weekly, monthly, one-time)

Benchmark targets: 25-40% of active users (defined as 3+ transactions) should set savings goals within 30 days of first deposit. This varies significantly by product type; investment platforms expect higher rates while payment-focused apps expect lower rates.

Common issues detected:

Very low goal-setting rates (below 15%) suggest feature is hidden, poorly explained, or not valuable to users. Users setting goals but not funding them indicate lack of follow-through mechanisms or insufficient motivation.

Optimisation opportunities:

Prompt goal-setting after successful transactions with contextual messaging ("You just paid rent. Want to save for next month's rent automatically?"). Gamify goal progress with milestones and celebrations. Send reminders when users are off-track from goal timelines.

Event #7: Premium Feature Enabled (Monetisation Path)

Event name: premium_feature_enabled

When to fire: When user subscribes to premium tier, enables paid features, or converts from free to paid offering

Why it matters: Premium conversion is the primary monetisation event for subscription-based fintech products. This event measures conversion funnel effectiveness and revenue generation efficiency. Time from first transaction to premium conversion reveals whether free tier successfully demonstrates value.

Properties to track:

• Premium tier selected (basic, standard, premium)

• Pricing plan (monthly, yearly)

• Features that drove conversion (which premium features user viewed before converting)

• Time since first transaction

Benchmark targets: 8-15% of active users (10+ transactions or 30+ days active) should convert to premium offerings within 60 days. Higher conversion rates indicate strong premium value proposition. Lower rates suggest unclear differentiation or insufficient free tier limitations.

Common issues detected:

If users view premium features repeatedly but don't convert, pricing may be too high or value unclear. If premium users churn quickly (within first month), premium tier isn't delivering expected value.

Optimisation opportunities:

Offer limited-time premium trials to let users experience value before committing. Create paywalls at strategic friction points ("You've reached your free transaction limit. Upgrade for unlimited transactions"). Analyse which features premium users use most to focus marketing messaging.

Event #8: Referral Sent (Viral Loop)

Event name: referral_sent

When to fire: When user shares referral link, invites contacts, or generates referral code

Why it matters: Referrals indicate satisfaction and trust. Users only refer financial products they trust and believe provide value. This event measures viral coefficient and enables calculation of organic growth contribution. Referred users typically have higher LTV because they arrive with trusted recommendation.

Properties to track:

• Referral method (link share, contact invite, social share)

• Number of referrals sent

• Referral incentive offered (if any)

• Time since first transaction

Benchmark targets: 15-30% of satisfied users (5+ transactions, 60+ days active) should send at least one referral. Higher rates indicate strong product-market fit and effective referral incentives. Lower rates suggest users aren't motivated to refer or product doesn't create shareable moments.

Common issues detected:

High referral sending but low referral conversion (invited users don't install or complete KYC) indicates referral messaging doesn't effectively communicate value or sets wrong expectations. Users referring very early (before 3 transactions) might be incentive-gaming rather than genuinely satisfied.

Optimisation opportunities:

Time referral prompts strategically after positive moments (successful large transaction, reaching savings goal, receiving cashback). Offer two-sided incentives (referring user and referee both receive rewards) to increase conversion. Make referral sharing frictionless with pre-filled messages and easy share buttons.

Event #9: Customer Support Contact (Friction Signal)

Event name: support_contact_initiated

When to fire: When user opens support chat, submits ticket, or calls helpline

Why it matters: Support contacts indicate friction, confusion, or problems. While not inherently negative (good support builds trust), high support contact rates reveal product issues. This event enables measurement of support load by user segment and identification of features causing confusion.

Properties to track:

• Contact method (chat, email, phone)

• Issue category (technical problem, account question, transaction issue, feature confusion)

• User lifecycle stage (pre-KYC, post-KYC, active transactor)

• Resolution status

Benchmark targets: 15-25% of users contacting support at least once is normal for financial products due to inherent complexity. Higher rates (above 30%) suggest significant UX problems. Very low rates (below 10%) might indicate users are churning silently rather than seeking help.

Common issues detected:

Spikes in support contacts around specific features reveal UX problems. High support contact rates among new users (pre-KYC or immediately post-KYC) indicate onboarding confusion. Frequent contacts about transaction failures indicate technical problems.

Optimisation opportunities:

Analyse support contact patterns to prioritise product fixes. Create self-service help content addressing most common issues. Implement proactive guidance (contextual tooltips, in-app tutorials) at steps where support contacts concentrate.

Event #10: Failed Transaction (Technical Health)

Event name: transaction_failed

When to fire: When any transaction attempt fails for any reason (technical error, insufficient balance, bank rejection, network timeout)

Why it matters: Failed transactions directly impact user trust and retention. Users who experience multiple failures often churn without giving feedback. This event enables tracking of technical health, identification of problematic payment methods, and measurement of failure impact on retention.

Properties to track:

• Failure reason (insufficient balance, bank error, network timeout, validation failure)

• Transaction type attempted

• Payment method used

• User transaction history (first transaction vs repeat user)

Benchmark targets: Transaction failure rates should stay below 5% in well-functioning fintech apps. Rates above 8% indicate significant technical problems. New users experiencing failures have 40-60% higher churn rates than users with smooth experiences.

Common issues detected:

Failures concentrated on specific payment methods indicate integration problems with those providers. Failures spiking during certain times (evening hours, weekends) suggest infrastructure capacity issues. High failure rates for first-time users indicate onboarding doesn't adequately explain balance requirements.

Optimisation opportunities:

Implement automatic retries for network timeouts. Show clear error messages explaining why transactions failed and how to fix issues. Send alerts when users attempt transactions that will fail due to insufficient balance before processing. Track users who experience failures and proactively reach out with support.

Attribution Windows for Financial Products (7-30 Days Standard)

Fintech conversion funnels are longer than ecommerce or gaming. Users research financial products carefully before trusting them with money. Standard fintech attribution windows should be 7-14 days for consumer products and 14-30 days for investment and wealth management products.

Shorter windows (1-3 days) used by gaming apps miss legitimate fintech conversions. A user might click an ad for your investment app, research alternatives for a week, then install and complete KYC. With a 3-day attribution window, this conversion wouldn't be credited to the campaign that drove awareness.

Configure attribution windows in your MMP based on product type:

• Payments and UPI apps: 7-day window (shorter consideration period)

• Neobanks and savings: 14-day window (medium consideration)

• Investment and wealth management: 21-30 day window (longer research phase)

Track time-to-conversion metrics by channel. If 80% of conversions from Google Search happen within 3 days while 80% of conversions from display ads take 10+ days, these channels serve different funnel stages and should use different attribution windows.

Compliance Considerations: PII Hashing and Data Governance

Fintech event tracking must comply with financial regulations, data privacy laws, and industry security standards. Mishandling user data creates legal liability and damages trust.

PII Hashing Requirements:

Never send personally identifiable information (PII) like email addresses, phone numbers, Aadhaar numbers, or PAN details to analytics platforms in plain text. Always hash PII before transmission using SHA-256 or similar algorithms. Your MMP and analytics tools can still identify unique users via hashed IDs without exposing sensitive data.

Data Retention Policies:

Implement data retention policies that delete user event data after regulatory-required periods (typically 5-7 years for financial records). Configure analytics platforms to automatically purge old data. Document retention schedules for compliance audits.

Consent Management:

Obtain explicit user consent for analytics tracking before collecting events. Provide clear opt-out mechanisms that stop event collection when users revoke consent. Honour deletion requests by removing all associated event data.

Geographic Restrictions:

Ensure event data stays within geographic boundaries required by regulations. Indian financial apps may need to store data within India to comply with RBI data localisation requirements. Configure analytics platforms to use India-region servers.

Event Data Minimisation:

Only track events and properties that serve business needs. Don't collect financial details (exact transaction amounts, account balances) unless necessary for specific analysis. The less sensitive data you collect, the lower your compliance risk.

Implementation Checklist: Week One Setup Guide

Implementing fintech event tracking follows a structured timeline that balances speed with accuracy.

Day 1-2: Event Definition

• Define the 10 core events above with exact trigger conditions

• Document property names and allowed values

• Create event specification sheet for engineering team

• Align stakeholders (product, growth, engineering) on event priorities

Day 3-4: SDK Integration

• Integrate analytics SDK (Mixpanel, Amplitude, CleverTap)

• Integrate MMP SDK (Linkrunner, AppsFlyer, Branch)

• Configure SDKs to communicate (MMP sends attribution data to analytics)

• Test SDK initialisation and basic event firing

Day 5-6: Event Implementation

• Implement all 10 events in app code

• Add property tracking for each event

• Test events in development environment

• Verify events appear in analytics dashboard

Day 7: Validation and QA

• Complete end-to-end user journey tracking all events

• Verify attribution data flows from MMP to analytics

• Check event property accuracy

• Create basic dashboards for monitoring

Request a demo from Linkrunner to see how fintech event tracking integrates with attribution data, providing complete visibility into which campaigns drive users who complete KYC, make deposits, and generate transactions.

Frequently Asked Questions

Should I track exact transaction amounts or bucketed ranges?

Use bucketed ranges (₹0-₹500, ₹500-₹2000, etc.) rather than exact amounts to reduce PII sensitivity and simplify analysis. Exact amounts create massive cardinality in analytics tools and rarely provide additional insight beyond ranges.

How do I track users who complete KYC but never deposit?

Create segments in your analytics platform for users who fired kyc_completed but never fired first_deposit_complete. Analyse their behaviour (session frequency, features viewed) to understand why they verified but didn't commit funds. This reveals product value communication gaps.

What's the best way to track users across app reinstalls?

Use persistent user IDs tied to account creation, not device IDs that reset on reinstall. When users reinstall and log back in, associate their new device with existing user ID to maintain event history continuity.

Should fintech apps track screen views in addition to these 10 events?

Screen view tracking helps debug user flows but provides limited strategic insight. Focus on outcome events (account creation, KYC completion, transactions) rather than engagement events (screen views, button clicks). Add screen tracking later if needed for specific UX analysis.

How do I measure marketing ROI for fintech with long conversion funnels?

Track cohort-based metrics by acquisition channel. Calculate percentage of each channel's installs that complete KYC, make first deposit, and reach 5+ transactions within 30, 60, and 90 days. Compare channels by cost per depositing user, not just cost per install, to understand true marketing efficiency.