Growth, risk, and finance all run different numbers.
Acquisition and product teams talk CAC and activation, risk teams talk losses and exposures, finance talks revenue and margins—and none of the metrics reconcile cleanly.
Industry · Fintech, Payments & Lending
Tie growth, risk, and revenue to one trustworthy analytics spine.
We help fintech, payments, and lending teams build analytics that respect regulation and risk—without losing the speed you need to grow. From KYC and onboarding to repayment, churn, and fraud, we connect the dots so product, growth, and risk speak the same language.
- Clean funnels from first touch → application → KYC/KYB → activation → usage → repayment or churn.
- Revenue, losses, and risk signals wired into GA4, your warehouse, and decision dashboards.
- Measurement that respects compliance, privacy, and security constraints from day one.
Built for B2C and B2B fintech: payments, credit, lending, wealth, neobanks, insurtech, and vertical-specific platforms.
Example · Growth & Risk in One View
Growth lens
- ✦ Application start → approval conversion
- ✦ Activation and first-value milestones
- ✦ Channel-level CAC and payback
- ✦ Product usage by segment and cohort
Risk & revenue lens
- ▸ Loss rate and charge-offs by cohort
- ▸ Fraud flags and manual review outcomes
- ▸ Interest / interchange / fee revenue
- ▸ LTV (net of losses) by channel/product
Result: growth is judged on risk-adjusted economics, and risk teams see the full journey—not just what hits the ledger.
Fintech Reality
You're moving real money and risk—but analytics still looks like a generic SaaS product.
We rebuild analytics around how fintech actually operates: regulated, risk-bearing, high-stakes systems where "events" must tie cleanly to customers, accounts, transactions, losses, and revenue—without exposing you to extra risk.
Onboarding and KYC funnels are a black box.
You know how many users land on the signup page and how many end up approved, but not where they drop or which steps cause rework, fraud risk, or regulatory headaches.
Manual spreadsheets are doing the real decision-making.
Critical questions about channel quality, LTV, and risk are answered in fragile Excel models, not in a source-of-truth analytics stack that can be trusted and scaled.
Regulation, consent, and security slow every change.
Every small change to tracking, experimentation, or data pipelines gets stuck between legal, security, and engineering, so the business keeps flying half-blind.
Foundations First
Model people, accounts, and money correctly—dashboards come later.
Instead of bolting events on top of whatever exists today, we start from how your business actually books value and risk. Then we instrument onboarding, product, and lifecycle flows to match that reality.
Event schema for onboarding, KYC/KYB, and activation
- Instrument application, verification, and onboarding flows step by step.
- Capture KYC/KYB outcomes, reasons for rejection, and manual review signals.
- Define activation events that match your real product milestones—not just logins.
Customer, account, and transaction modelling
- Design clean IDs and joins between customers, accounts, cards, and instruments.
- Map key transaction types, balances, and fees to analytically friendly models.
- Align GA4 / product events with ledger events so flows match money movement.
Risk, fraud, and loss visibility
- Instrument risk checks, fraud scores, and manual interventions as events.
- Track charge-offs, disputes, and losses at cohort and segment level.
- Give risk teams views that tie interventions to changes in growth and unit economics.
Compliance-aligned measurement posture
- Separate PII from behavioural analytics while keeping joins workable in the warehouse.
- Implement consent-aware and region-aware tracking that satisfies regulatory expectations.
- Document how measurement, data retention, and access controls are designed for auditors.
Fintech Data Architecture
A measurement spine where flows match how money and risk really move.
We make sure every "step" in your funnels corresponds to something that matters: approvals, activated balances, spend, repayments, losses, and long-term economics—not just clicks and button presses.
Acquisition & Application Layer
- Map campaigns and channels to applications and approved accounts—not just signups.
- Track drop-off throughout onboarding and verification, including rework loops.
- Measure CAC and approval rates by channel, segment, and risk profile.
Typical tech
GA4, sGTM / server-side events, marketing platforms, CRM, attribution logic wired to application systems.
Identity, Accounts & Ledger Layer
- Define robust IDs across customer, account, and instrument entities.
- Mirror ledger events into analytics-friendly fact tables without breaking accounting.
- Tie behavioural events (clicks, flows) to ledger events (transactions, fees, interest).
Typical tech
Core banking / ledger, internal services, warehouse (BigQuery/Snowflake/Redshift), dbt or SQL models.
Risk, Fraud & Compliance Layer
- Model risk scores, flags, investigations, and outcomes as structured data.
- Track loss events, fraud attempts, and charge-offs by cohort and channel.
- Provide audit-ready views of decisions, thresholds, and outcome distributions.
Typical tech
Risk engines, fraud tools, case management systems, warehouse models, secure reporting surfaces with role-based access.
Revenue & Unit Economics Layer
- Calculate ARPU, LTV, and contribution margins net of losses, fees, and incentives.
- Compare unit economics by product, segment, geography, and acquisition source.
- Allow finance, growth, and product to use the same definitions and views.
Typical tech
Warehouse models, financial systems, BI tools (Looker Studio / Power BI), standardized metrics layer.
Decision & Experimentation Layer
- Test changes to onboarding, risk thresholds, pricing, and product surfaces with guardrails.
- Measure impact of risk strategies and compliance changes on growth and unit economics.
- Feed learnings back into product roadmaps and capital allocation decisions.
Typical tech
Experimentation frameworks, GA4 / in-app experimentation, analysis notebooks, BI dashboards with pre-defined experiment views.
Selected Fintech Patterns
Growth that survives risk, audits, and the next board meeting.
The common thread: put flows, money, and risk on the same map. Once everyone trusts that spine, growth and risk stop fighting and start optimising the same machine.
B2C lending / BNPL platform
Problem: Rapid growth hid deteriorating risk quality. Marketing reported strong CAC and approvals; risk and finance saw rising losses, but nobody agreed on which channels or cohorts were the problem.
What we did: Connected acquisition, application, risk, and ledger data in a unified model. Instrumented onboarding and repayment flows in GA4, and built risk-adjusted unit economics dashboards.
Impact: Clear view of loss rates and payback periods by channel and cohort. Growth reallocated spend without killing volume; risk updated policies based on evidence, not anecdotes.
B2B payments and invoicing platform
Problem: Product and sales pushed hard into new segments, but leadership lacked visibility into activation, feature adoption, and revenue per account over time.
What we did: Defined account-level activation and value milestones, instrumented them in the app, and tied them to billing and payment flows in the warehouse.
Impact: Sales and product focused on segments with strong activation and expansion; experiments targeted specific steps in the onboarding and value delivery journey.
Consumer investing & wealth app
Problem: Marketing and product decisions were based on installs and KYC completions, not on funded accounts, assets under management, or retained investors.
What we did: Redesigned measurement around funded accounts, AUM, and retention. Connected GA4 and product events to custody and transaction systems.
Impact: Marketing looked at CAC-to-funded-account and AUM contribution; product optimized education and onboarding flows that actually increased assets and retained users.
For product & engineering
Clean definitions of activation, value, and risk that you can wire directly into your services, feature flags, and experimentation frameworks—without fighting over what a "customer" means.
For growth & marketing
CAC, LTV, and payback views that account for losses, charge-offs, and incentive costs—so spend decisions are defendable to finance and the board.
For risk, compliance & leadership
Dashboards and models that expose risk posture, tail events, and economics in one place—designed to withstand scrutiny from investors, partners, and regulators.