KI im Finanzsektor

Betrugserkennung, Underwriting und Kreditentscheidungen in Echtzeit, gebaut für Teams, die jeden Score einer Aufsichtsbehörde erklären müssen. Vier Systeme im Produktivbetrieb in Banking, Versicherung und Fintech.

Was wir hier gebaut haben

Kundensysteme im Produktivbetrieb, mit den berichteten Kennzahlen.

• Financial Services

  Enterprise Fraud Detection System

  A financial services company was facing significant losses due to sophisticated fraud. Their existing rule-based system couldn't keep up with evolving threats.

  • £3.2M Annual Savings
  • 97% Alert Precision
  • 86% Recall

• Insurance

  Predictive Risk Selection & Underwriting Optimization

  A major insurer faced deteriorating loss ratios in their safe segments. They relied on static heuristic rule-sets that failed to distinguish between profitable risks and hidden liabilities in a high-volume underwriting queue.

  • 28% Reduction in Severity
  • 12% Margin Expansion
  • 4.2x Lift in Risk Detection

• Insurance

  Moral Hazard Detection in Insurance Claims

  A leading UK insurer struggled to identify potential fraud in lengthy, unstructured claims notes without benchmark data and under significant technical constraints.

  • 32% More Fraud Detected
  • 83% Precision
  • 76% Recall

• FinTech

  Real-time Decision Engine

  A fintech company needed a high-performance system to make lending decisions in milliseconds while maintaining accuracy.

  • 100k+ Daily Decisions
  • <300ms Response Time
  • 25% Loss Reduction

Die Leistungen dahinter

Die Fähigkeiten, auf die diese Arbeit zurückgreift.

• Fraud Detection & Risk Systems Implement real-time fraud detection and risk assessment systems to protect your assets and ensure compliance.
• Advanced Machine Learning Solutions Developing bespoke machine learning models for critical business functions, from personalized recommendations to robust fraud detection and credit scoring.
• MLOps & Production AI Building robust, scalable, and compliant MLOps pipelines to ensure deployment, monitoring, and management of AI models in production.
• AI Security Audits & Secure Deployment Hardening AI agent infrastructure, securing LLM deployments, and implementing governance frameworks to protect your intellectual property.