IA en servicios financieros

Fraude, suscripción y decisiones de crédito en tiempo real, construidos para equipos que deben explicar cada puntuación a un regulador. Cuatro sistemas en producción en banca, seguros y fintech.

Lo que hemos construido aquí

Sistemas de clientes en producción, con las cifras que reportaron.

• 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

Los servicios detrás

Las capacidades en las que se apoya este trabajo.

• 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.