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FINTECH AI DEVELOPMENT / UNITED KINGDOM

AI for financial services, with the controls the FCA expects.

Fintech AI development for UK banks, lenders, payment companies and wealth platforms: onboarding and KYC automation, document intelligence, risk signals and customer support assistants built with FCA and UK GDPR obligations in view.

UK-registered company. International engineering team.

01 / THE OPPORTUNITY

Fintech AI development for UK businesses.

Financial services is where AI must be explainable, auditable and fair. Krapton builds fintech AI products for UK firms that automate the paperwork-heavy parts of onboarding, lending and servicing while keeping every decision traceable and every customer outcome fair under Consumer Duty.

From document intelligence that reads bank statements and identity documents, to assistants that resolve support queries from approved policy, to risk signals that help analysts prioritise, we design for the regulated context: model risk management, audit trails, human review and clear customer communication.

  • Azure OpenAI and Anthropic
  • UK and EU hosting
  • Open Banking APIs
  • Python
  • Node.js
  • Next.js
  • PostgreSQL
  • Kafka and queues

02 / Use cases

Where itearns its keep.

  • Onboarding and KYC documents

    Extraction and checks across statements, payslips and identity documents, with exceptions routed to analysts.

  • Support and complaints assistants

    Grounded answers from policy and product documentation, with escalation and vulnerability cues built in.

  • Risk and fraud signals

    Pattern detection that prioritises cases for human investigation rather than deciding outcomes alone.

  • Operations intelligence

    Summaries, reconciliations and reporting from transaction and case data for operations teams.

03 / Our approach

Built to betrusted in production.

Evaluation before release, guardrails by design and people in control of the decisions that matter.

AI development overview
  1. 01

    Regulatory framing

    Which functions are customer-affecting, which need explainability, and how Consumer Duty, SM&CR and model-risk expectations apply. Agreed with your compliance lead.

  2. 02

    Data and controls design

    Data lineage, access, retention, audit logging and human-in-the-loop checkpoints designed before the model is chosen.

  3. 03

    Evaluate for fairness and accuracy

    Test sets that include edge cases and protected characteristics analysis where relevant, with results documented for your governance.

  4. 04

    Monitored deployment

    Drift, quality and cost monitoring, incident procedures and periodic reviews as part of the operating model.

04 / Before you start

The decisions that shape the build.

Automated decisions with legal or similar effects on individuals engage Article 22 UK GDPR and FCA expectations on fairness and explainability. We design human review into those paths and document how the system reaches its outputs; your firm remains responsible for regulatory compliance.

What every AI engagement includes

  • A use case with a measurable result and representative examples
  • An evaluation set rerun on every prompt, model or data change
  • UK GDPR-aware data flows, with UK or EU hosting where residency matters
  • Human review and defined permissions for anything consequential
  • Cost and quality monitoring after launch

05 / From the portfolio

Applied AI,connected to a real product.

Examples from Krapton’s international portfolio. Each success story describes the work delivered for that project.

Sendora project visual
Fintech / Cross-border Payments

Sendora

Sendora lets users send money internationally with zero transfer fees, spend on a global debit card and build credit from their phone — but the marketing site had to communicate trust, speed and global coverage at a glance, in a category where trust is everything.

Read the success story

FAQ

Fintech AI development: questions UK teams ask.

Yes, with governance: clear accountability, explainable outputs, human review of customer-affecting decisions, monitoring and records. We build to support those controls; your compliance function owns the framework.

Related

Connect thecapabilities.

YOUR NEXT STEP

Let’s scope your fintech ai product.

Bring the task, the examples and the systems involved. We’ll tell you what an evaluation set, a prototype and a first release would look like.

YOUR NEXT CHAPTER

What are you thinking?