Actuarial Data Science
We use machine learning techniques along with actuarial methods to build innovative solutions for our clients. Our offerings are backed by strong research based foundations which have also resulted in several publications in international journals.
Machine Learning provides greater ability to identify in-depth patterns in the data that are normally invisible or difficult to identify using other methods. One of the major applications of it is seen in insurance claims fraud detection, which is a classification problem. We have used a combination of actuarial and data science techniques to build fraud detection and prevention models.
We use predictive modeling and machine learning techniques to provide valuable insights that translate to direct business impact. Supplementing actuarial models with predictive analytics for customer acquisition, underwriting and claims modeling can create massive competitive edge for companies.
Actuarial tool development
Spreadsheet modeling forms a majority of our day-to-day work. However, when it comes to processing speed and ability to handle large data, tools like R and Python come very much handy. We help our clients in automation of daily process to improve speed and reduces costs.