Actionable risk and scoring models
Credit scoring, limits and segmentation built on consistent, versioned data. Explainable, monitored models —not black boxes no one can defend before the regulator.
Data & Analytics · Fintech
Data and Analytics for Fintech
We turn your financial data into decisions: risk models, anomaly detection, regulatory reporting and real-time metrics, with the data governance the sector demands.
THE CHALLENGE
The challenges of Fintech
Fintech software operates under constant regulatory and security pressure, where a failure carries direct financial and reputational cost. It needs regulatory rigour, traceability and an architecture that scales without compromising trust.
- Regulatory compliance (PSD2, PCI-DSS, GDPR)
- Financial data security
- Scalability under transaction spikes
- Integration with payment gateways and core banking
- Time-to-market without compromising rigour
How we help you
In fintech, data isn't a report at the end of the month: it's the difference between approving a healthy loan or a delinquent one, between stopping a fraud or paying for it. We build the data layer a financial business needs —reliable pipelines, risk models, anomaly alerts and reporting the regulator accepts— without losing traceability or control. From the raw source to the dashboard the risk committee looks at, with a senior team that understands a miscalculated number here has a direct cost.
Anomaly and fraud detection
Real-time signals on transactions and behaviour to raise alerts before fraud takes hold, with rules and models that cut down false positives.
Regulatory reporting without surprises
Reproducible, auditable reports for PSD2, AML and supervisor requirements: same data, same figure, end-to-end traceability every time you have to file them.
Real data governance
Catalogue, lineage, quality and access control so you know where every metric comes from and who touches it. Trust in data is designed, not improvised.
WHAT YOU GAIN
Data & Analytics, results-driven
- Reliable, consistent data in a single place
- Dashboards that answer business questions
- Actionable metrics, not vanity ones
- Maintainable, documented pipelines
- A solid foundation for advanced analytics and AI
FAQ
Frequently asked questions
Can you build risk and scoring models on our data?
Yes. We start from your sources (core, transactions, bureaus) to build explainable, versioned risk and scoring models monitored in production, with the traceability you need to defend them before the regulator.
How do you detect fraud and anomalies in transactions?
We combine business rules with models over behavioural patterns and real-time signals. The goal is to raise useful alerts before fraud takes hold, tuning the threshold to minimise false positives.
Do you help with regulatory reporting?
Yes. We design reproducible, auditable reports aligned with PSD2, AML and your supervisor's requirements, with end-to-end data lineage so every figure is traceable and consistent across submissions.
What does data governance mean in a fintech project?
Data catalogue, lineage, quality controls and access management: knowing where every metric comes from, who can see it and how it's calculated. In fintech it's not optional —it's the foundation of trust and compliance.
Do you start from scratch or integrate our data sources?
We integrate what you already have: databases, events, SaaS tools and spreadsheets. We unify the sources into a coherent, reliable data model.
Which dashboard tools do you use?
We use the tool that best fits your team and budget, from open source solutions to cloud platforms, prioritising that people actually use them.
Shall we build something that scales, together?
Tell us about your project. We'll get back to you with a concrete plan and a senior team — not a generic quote.