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.
Case studies
All case studiesRelated projects
Insurance · Machine Learning
Telematics-based driver scoring for usage-based insurance
Per tripdriving score and personal discount
A deep learning model that analyses telematic data from drivers’ phones to detect driving behaviour, score each trip and calculate personalised discounts and safe-driving recommendations.
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Credit scoring model for an SME lending company
800+ features from 14 data sources
A machine learning model that predicts borrower default and fully automates underwriting, improving loan portfolio quality and cutting decision time from hours to a fraction of a minute.
Risk estimation model for a medical insurance company
Outperformed statistical baseline models
A neural network model, trained on five consecutive years of historical medical data, that estimates the risk of economic loss so a niche health insurer can optimise its pricing policies.
Player churn prediction for an online gaming platform
11.3% churn rate after new retention strategies
A machine learning model that learns player behaviour during the game and predicts the probability of churn over a given time horizon, so the platform can apply the most relevant retention strategy.
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