Explainable AI Fraud Detection for Lenders, Leasing and Automotive Finance

Bleckwen is a Paris-based fraud detection company serving credit institutions, leasing firms, factoring companies, insurers and automotive finance businesses. It was established in 2019 as a spin-off from the French cybersecurity firm Ercom, with its first real-time fraud prediction engine co-created alongside BNP Paribas. The team of data scientists and fraud specialists concentrates on financing use cases rather than card payments, covering application fraud, first-party fraud, trade-in fraud and payment default risk across consumer credit, BNPL, equipment leasing and mobility finance.

The platform pairs a configurable rules engine with machine learning models, on the premise that rules alone no longer hold up against evolving fraud patterns. Financial crime teams build scenarios and models from a library of advanced variables, backtest them against historical transactions to measure impact and performance before release, then push them live under governance controls. Scoring runs on a real-time transactional architecture with sub-200-millisecond latency, integrated through APIs or an event-based plugin architecture and connected to custom data dictionaries.

Explainability sits at the centre of the positioning: alerts are delivered with enough context for analysts to understand and justify a decision, and an agentic Investigation Assistant centralises case information to make reviews faster and more consistent. A managed scoring option builds bespoke models on a client's own data, enriched with Bleckwen's, with continuous monitoring, retraining and tuning delivered through a dashboard portal. Named customers include BNP Paribas, Carrefour Banque, Stellantis Finance Services, Mobilize Financial Services, Arkea and Evollis.