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💳 Banking & Financial Apps

Analytics for
Fintech Apps

Data minimization architecture for banking, trading, payment, and neobank apps. Only 5 fields stored. No device IDs. IP never retained in analytics.

🔒 No transaction data stored 🚫 No account numbers possible 📋 Minimal audit surface

The Fintech Analytics Challenge

Financial apps face unique challenges with standard analytics tools that weren't designed for sensitive financial data

📱

Device Identifiers + Financial Behavior

Standard tools store IDFA/GAID alongside events like "loan_applied" or "investment_made"—creating linkable financial profiles that persist across sessions.

💸

Transaction Data Leakage

Tools accepting unlimited custom properties risk developers accidentally sending account balances, transaction amounts, or account numbers in analytics events.

🌐

IP Addresses + Financial Events

IP addresses combined with financial activity patterns become personal data under GDPR—and nonpublic personal information under GLBA.

🔗

Persistent User Tracking

User IDs that persist across sessions create a complete financial behavior history—every investment viewed, every loan considered, every payment made.

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Third-Party Data Sharing

Many analytics tools share data with parent companies or ad networks. For financial data, this creates complex disclosure requirements under multiple regulations.

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Vendor Risk & DORA

DORA requires EU financial entities to conduct due diligence on ICT vendors. The more data your analytics vendor stores, the more complex your vendor assessment becomes.

Our Approach: Data Minimization by Design

Return of Avoidance (ROA) — the best way to protect sensitive financial data is to never collect it

What We Store (5 Fields)

  • 1.
    event_name

    What happened (e.g., "payment_completed", "account_opened")

  • 2.
    session_id

    RAM-only, hashed with daily rotating salt, resets every 2 hours

  • 3.
    timestamp

    When the event occurred

  • 4.
    platform

    iOS, Android, or Web

  • 5.
    country

    Approximate location (country-level only)

What We Never Store

  • Device identifiers (IDFA, IDFV, GAID)
  • IP addresses (processed transiently, then discarded)
  • Persistent user IDs
  • Custom properties (API rejects them)
  • Transaction amounts or account balances
  • Account numbers or financial identifiers
  • Device fingerprints or hardware IDs
  • Browser cookies or local storage tokens

⚙️ Technical Architecture

💾

RAM-Only Storage

Session identifiers stored only in device memory—never written to disk, NSUserDefaults, or SharedPreferences

🔄

2-Hour Rotation

Session IDs automatically rotate every 2 hours and reset on app restart—cross-session tracking is impossible

🔐

Server-Side Hashing

Session IDs are hashed with a daily rotating salt server-side before storage—even we can't link sessions

What Fintech Apps Can Measure

Session-based analytics provide actionable insights without tracking individual users across sessions

📈

Onboarding Conversion

Track KYC completion rates, document upload success, and account opening funnels without storing personal data

💳

Payment Flow Success

Measure payment initiation → confirmation rates and identify drop-off points in transaction flows

🎯

Feature Adoption

See which banking features drive engagement—budgeting tools, card controls, savings goals, investment options

🚪

Drop-Off Detection

Automatically identify where users abandon loan applications, account setup, or card activation flows

📱

Platform Distribution

Compare iOS vs Android performance, inform platform investment decisions and QA priorities

🌍

Geographic Trends

Country-level engagement patterns for international expansion and market-specific feature planning

⚠️ Honest Limitations

Session-based analytics mean you trade some metrics for privacy. Here's what you can't measure:

  • Cross-session user identification
  • Traditional DAU/MAU requiring persistent IDs
  • Multi-week retention cohorts
  • Individual customer lifetime value
  • A/B tests targeting returning users
  • User-level behavioral sequences

If your fintech app requires these metrics, Respectlytics may not be the right fit. We believe in transparent trade-offs.

Fintech App Types We Serve

Data minimization architecture works across the financial services spectrum

🏦

Neobanks & Digital Banks

Challenger banks need to understand feature adoption and onboarding funnels without creating detailed financial behavior profiles.

Account opening flows, card activation, feature usage
📊

Trading & Investment Apps

Track onboarding and feature adoption without linking device IDs to investment behavior or portfolio activity.

Onboarding completion, market feature usage, education engagement
💳

Payment & Transfer Apps

Measure payment flow success rates and drop-offs without storing transaction amounts, recipients, or payment patterns.

Payment initiation, recipient add flows, transfer completion
🪙

Crypto Wallets & Exchanges

Analytics without linking device IDs to wallet addresses or trading activity—critical as MiCA enforcement increases.

Wallet setup, trade execution flows, staking engagement
💰

Lending & Credit Apps

Track loan application funnels without storing credit-related behavior that could inform underwriting decisions.

Application flows, document upload, approval funnel analysis
🛡️

Insurance & Insurtech

Measure quote-to-bind conversion without collecting data that could be used for risk assessment or pricing.

Quote flows, claims reporting, policy management engagement

Regulatory Landscape Context

Fintech apps may face multiple overlapping regulations. Here's how data minimization relates to each.

🇪🇺

GDPR

Article 5 requires data to be "limited to what is necessary." Storing only 5 fields with no device IDs aligns with data minimization principles. However, consult your legal team about your specific lawful basis.

💶

PSD2

The Payment Services Directive focuses on payment data and strong authentication. Analytics data that doesn't contain transaction details or account information falls outside PSD2's primary scope.

🔒

DORA

Digital Operational Resilience Act requires vendor due diligence. A minimal data footprint (5 fields, no PII) simplifies ICT third-party risk assessment and vendor register documentation.

🇺🇸

GLBA

Gramm-Leach-Bliley protects "nonpublic personal information." Session-based analytics without device IDs or persistent user tracking minimizes what qualifies as NPI under GLBA definitions.

Important: This is educational information, not legal advice. We do not claim our product satisfies any specific regulatory requirement. Consult your legal team to determine what applies to your app.

Frequently Asked Questions

What data does Respectlytics store for fintech apps?

Exactly 5 fields: event_name, session_id, timestamp, platform, and country. No device identifiers (IDFA, IDFV, GAID), no user IDs, no custom properties. IP addresses are processed transiently for country-level geolocation and immediately discarded—never stored in analytics. This prevents accidental financial data leakage.

Can developers accidentally send financial data through analytics?

No. Unlike Firebase or Mixpanel, Respectlytics enforces a strict 5-field schema at the API level. Any extra properties—including account numbers, transaction amounts, or balance information—are silently rejected. This prevents accidental sensitive financial data leakage by design.

How does Respectlytics handle session identification?

Session IDs are generated in device RAM only (never written to disk), rotate automatically every 2 hours, and reset on app restart. Server-side, they're hashed with a daily rotating salt. This makes cross-session tracking technically impossible—you cannot link a user's Monday banking session to their Tuesday session.

What fintech analytics can you get without collecting personal data?

You can track onboarding completion rates, feature adoption (which banking features users engage with), payment flow conversion, drop-off points in loan applications, platform distribution (iOS vs Android), and geographic trends—all without tracking individuals across sessions.

How does data minimization help with fintech regulations?

Data minimization means collecting only what you need. By storing just 5 fields with no identifiers, you significantly reduce your data surface area. Less data means less risk of regulatory scrutiny across GDPR, PSD2, DORA, and GLBA. Consult your legal team to determine how this applies to your specific situation.

What are the limitations of session-based fintech analytics?

With session-based analytics, you cannot track individual users across sessions, calculate traditional DAU/MAU metrics requiring persistent IDs, measure multi-week user retention, or calculate individual customer lifetime value. You trade cross-session tracking for a minimal data footprint.

⚖️ Legal Disclaimer

This page provides educational information about fintech analytics and regulatory context. It does not constitute legal advice. Respectlytics does not claim compliance with any specific regulation including GDPR, PSD2, DORA, GLBA, PCI-DSS, or any other financial services regulation. Financial regulations vary by jurisdiction, app functionality, and change over time. Consult your legal team to determine the requirements that apply to your specific situation.

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