Data & Innovation • Financial Services
Anomaly detection through Data Lake and Fraud Detector
An important insurance company in Mexico detects anomalies and prevents actions with a probability of being fraudulent.
About the client
An insurance company providing 24/7 assistance solutions, offering users assistance for unexpected events in their homes, vehicles, bicycles, or accompanying their pets.
Founded in Mexico in 1988, it already has a presence in Argentina, Brazil, and Colombia, and is in the process of expanding to other countries in the region.
Needs
The client is looking to implement a solution to detect fraudulent transactions, reduce false positives, and minimize the risk impact by automating the process and providing dashboards and KPIs for decision-making, with the goal of generating a single source of truth and analysis.
Solution
The proposed solution involves implementing a Data Lake and the Fraud Detector product developed and refined by Nubiral.
The tool is a model created with Machine Learning, using both supervised and unsupervised learning.
The solution learns from the data and helps companies be efficient in their operations, detecting anomalous behaviors and fraudulent transactions
Results
The solution aimed to detect anomalies in real-time based on the criteria provided by the insurance company's team, visualized on dashboards, and integrated with their transactional systems to prevent the completion of operations with a high probability of being fraudulent.
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