FinTech & Financial Services
Financial data that stands up to an audit
Regulators, auditors and customers expect exact numbers. We build secure, governed platforms that give every team the same figures and give customers live insight in the app.
The problem
01
A fragmented customer view
Onboarding, transactions, risk and support data are held in separate systems.
02
Manual reconciliation
Finance and product reconcile numbers by hand before each board pack.
03
No live customer insight
Customers want real-time analytics and receive a monthly PDF.
What we build
What we build for FinTech teams
Compliance foundation
Access controls, lineage, PII handling and audit trails.
360° customer view
Every product, transaction and interaction linked to one customer.
Embedded analytics
Secure, live dashboards inside your customer experience.
Data team enablement
The processes and skills to run the platform safely yourselves.
Typical stack
BigQuerySnowflakedbtLookerCubeEmbeddableDagsterGA 360
Results
Related case studies
Snap Finance FinTech · Consumer lending ENT Credit Union Financial services · Enterprise Embroker InsurTech · B2B SaaS
Ad spend measured against real loan applications for the first time
A full GA4 build, server-side tracking and an attribution model that matches marketing spend to applications, including the ones completed offline.
OfflineApplications matched
Server-sideTracking live
Wasted spendReduced
Siloed reporting replaced with one view across business lines
An enterprise analytics account built from scratch, with tracking, custom dimensions and the dashboards each team uses daily.
AccountBuilt
DimensionsCustom
DashboardsDaily use
One version of the numbers, then experiments on top
We rebuilt tracking and reporting so marketing, product and finance read the same figures, connected marketing data to Salesforce, then ran a structured testing programme.
ReportingUnified
TrackingRebuilt
CRORunning
Services
Services that fit
Digital Analytics & Tracking
Tracking that ties every sale and lead to the spend that produced it.
Data Platform Build
One warehouse and one set of numbers for every team and AI tool.
Warehouse Migration
Move warehouses on a fixed date, with proof the numbers match.
Data Team Modernisation
Free your data team from the ticket queue to work on what moves revenue.
How we work
How an engagement starts
The work runs in three steps. You see working output within weeks and can stop after any stage.
01
Discovery call
A 30 minute call with the engineer who would do the work. We look at your setup, tell you what we would fix first, and whether you need us for it.
Day 1 02
Blueprint sprint
We map your sources, stakeholders and goals, then give you an architecture and a prioritised roadmap. You keep it whether or not we do the build.
2 to 4 weeks 03
Build in sprints
We ship working tracking, models, dashboards and agents every two weeks. You can stop after any sprint, and everything built stays yours.
Every 2 weeksWhat happens on the call
Book your call- 30 minutes with the engineer who would do the work
- No slides or sales pitch
- A clear answer on whether we can help, and a referral if we can’t
- The first fix we would make, which you can use either way