Team Aureus beat over a dozen data sciences players to win the coveted prize of INR 1,00,000 at Datameet 6. Organized jointly by a large BFSI company, Zone Startups and DataMeet Mumbai, the hackathon was a 2 day event which was held at the Bombay Stock Exchange office of Zone Startups.
Each team was given 80GB of real transaction data from which they had to glean insights using any tools they were comfortable with.
The organizers of hackathon had kept the problem statement open and gave the freedom to explore various aspects from the data. Team Aureus focused on building a topnotch claims rejection predictive model with a very strong predictive power. Along with the given structured health claims data, the team created intelligent predictor variables using text mining techniques on unstructured claims data.
Combining the direct and derived intelligent variables, the team developed high performing models using advanced machine learning algorithms such as Random Forest and Generalized Additive Methods. Further, detailed insights were generated using the prediction models and text mining techniques. High impact predictor variables and their complex risk patterns were also identified.
By identifying inter variable correlations, the team could deep dive into the data records to identify diseases for which most claims were filed, the rejection rates, etc…The team also demonstrated that the model could be specialized to a disease-specific models.
Together, the team provided insights with high business value and top-class prediction models for optimizing operations and resource allocation.Such a model would go a long way in helping optimize operations by improving claims review time and plan claims cash flow.