Bleckwen’s AI model increases detection rates and generates half as many false positives.
We take the data of our partners and make it useful. Our team creates smart models by combining their data, enriched with ours, to solve their particular needs.
By constantly analyzing the models for drift and effectiveness, we retrain them as needed, saving businesses time, effort and money.
Fraud Solution Profile
Our adaptable solutions for credit actors bring data science to the frontline of your lending businesses.
- Powerful and easy to integrate API solution with well-documented REST APIs
- Get results fast without disrupting your business operations
A flexible API for easier and faster integration to minimize fraud losses and reduce operational cost
Personal loan fraud is a growing challenge for large companies. Our model reduces fraud by 80% using an efficient scoring tool to minimize the impact of false positives. The longer it runs on historical and real-time data, the more accurate the rules become to reduce fraud over time.
While most application fraud targets identity fraud, our solution uses data from our auto lender partners to predict and find all types of fraud in a single integrated fraud score. The alerts enable business owners to prioritize the highest-risk transactions for approval by avoiding: identity and income forgery, straw lenders, merchants, and collateral fraud.
Retail Credit Applications
Our data scientists use machine learning techniques combined with unique retail data to minimize application risk, and ensure an optimal customer experience at the point of sale. Our analytics model is highly predictive and helps retailers identify high-risk applicants who are more likely to fail due to application fraud.
SME fraud loans are increasing dramatically. The challenge is how to limit fraud exposure and contain the impact of customer attrition. Our model is based on data enrichment and accurate fraud scoring meaning every decision is based on facts, not assumptions.
Carrefour Banque & Assurance
DIAC, Mobilize Group
Payment Fraud, Synthetic Identity Fraud
Behavioral Biometrics, Machine Learning, Rules Engine