Case Study: a dental insurance startup achieves 95% fraud detection accuracy with ScienceSoft's AI algorithms

a dental insurance startup achieves 95% fraud detection accuracy with ScienceSoft

The customer, a dental insurance startup, needed to develop a software product that used computer vision to detect errors and fraud in dental insurance claims. They required robust data science skills to build ML algorithms for analyzing dental X-rays and required a trusted vendor to accelerate their time-to-market. They engaged ScienceSoft for its ML implementation and medical image analysis expertise.

ScienceSoft allocated a senior data scientist who collaborated with the customer's team to develop algorithms for identifying tooth types, detecting dental problems, and validating the authenticity of X-rays to spot duplicates and alterations. The solution, developed with Python and PyTorch, achieved a 95% accuracy rate in detecting inconsistencies, resulting in a market-ready MVP for the startup's fraud detection product.