Artificial Intelligence in Insurance

Practical experience and theoretical background allow us to properly represent various types of heterogeneous data into ready to use machine learning data sets. We perfect the art of feature engineering for time-series data, financial transactions, spatiotemporal information, behavioral patterns and many more. A high-quality risk scoring model is one of the key success factors in risk management. Our PhD level data scientists in Machine Learning can train and properly validate a Risk Scoring Model that will have a comprehensive view of the insured.

Are you looking for a higher number of customers and are ready to take more risk or rather to stay risk-averse and optimize the profitability with other means e.g. increasing the premium? All these relevant questions for Underwriting, Finance and Marketing can be answered with the help of Data Science by optimization algorithm to further improve the Unit Economics of your Business.

Due to a high number of variables and complexity behind modern machine learning algorithms, it is hard to interpret the reasoning and decisions made by machine learning models. AI Superior can help to overcome this issue. We can provide a tool that gives an explanation either over the whole population or for an individual customer. We work with a wide variety of methods to name a few: Neural Networks, Gradient Boosting, Random Forest.

To understand your customers behavioral patterns and risks associated with them, AI Superior offers a behavioral analysis package. Based on sophisticated machine learning models it allows you to get deeper insights into your customers behavior, segment them based on their assignment to a particular risk group and take relevant actions. A typical example of application of such an analysis is a driving style scoring where the behavior of every driver is analyzed in order to obtain driving profiles and risk of an accident associated with them. Such analysis requires telematic data obtained from an installed sensor or a smartphone. Alternatively,…

AI Superior helps to improve the predictive power of your models by providing Data Enrichment Services. It includes data enrichment and data fusion modules allowing to collect, fuse and streamline various heterogeneous data to your AI applications. This enables many use cases such as: Geospatial-based risk indices generation to explore districts and regions on the map and consume demographics, governmental statistics, public information and infrastructure-related insights Satellite imagery-based data for hazard assessment of property e.g. fallen trees or flood prediction, crises prediction and others.