Real-time fraud detection
Models that score transactions on the fly, cut false positives and adapt to new patterns, with rules and thresholds your risk team controls.
Applied AI · Fintech
Applied AI for Fintech
We bring models, agents and RAG into your financial product to detect fraud, speed up scoring and automate KYC/AML, with the explainability and risk control the regulator 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, AI can't be a black box: every decision about a loan, a transaction or a customer has to be justifiable to the user and to the regulator. We apply artificial intelligence to the cases that move the needle for the business —fraud, risk, compliance, support— embedded in your platform and not in an isolated demo, with clear metrics for accuracy, cost and latency. Fewer false positives, faster decisions and an auditable trail behind each one.
Explainable credit scoring
Scoring engines that combine alternative and traditional data, with per-decision explainability to stay compliant and avoid losing good customers to an unfair rejection.
Automated KYC/AML
Document extraction and verification, list matching and risk analysis that speed up onboarding without lowering the bar on regulatory compliance.
Support agents with guardrails
Assistants that resolve queries about products, transactions and processes using your own documentation, with clear limits so they don't give improper financial advice.
WHAT YOU GAIN
Applied AI, results-driven
- Use cases prioritised by business impact
- Integrated with your data and your product, not an isolated chatbot
- Model cost and latency under control
- Evaluation and guardrails for reliable answers
- From prototype to production with judgement
FAQ
Frequently asked questions
Is your scoring and fraud AI explainable to the regulator?
Yes. We prioritise techniques and traces that let you justify every decision: which factors weighed in, at what threshold and why. We document the model and its evaluation so you can respond to audits and complaints.
How do you avoid false positives in fraud detection?
We tune the models with your historical data, measure precision and recall per segment, and leave thresholds and rules configurable so risk can balance blocking fraud against friction for the legitimate customer.
Can you automate KYC/AML without compromising compliance?
Yes. We automate document extraction, identity verification and list screening, leaving human review where the risk demands it. The goal is to speed up onboarding while keeping control.
Does financial data leave our environment?
Only if you decide it should. We design the architecture to fit your policy: models via API with minimised and anonymised data, or open models deployed in your own environment when privacy or regulation require it.
Will AI actually work for my case or is it just a demo?
We start from the business problem, not the technology. If a use case doesn't deliver measurable value, we'll tell you. We only take to production what justifies it.
Do you use your own models or third-party ones?
Both, as appropriate: commercial models via API to move fast, and open or fine-tuned models when cost, privacy or latency demand it.
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.