Insurance
We help insurance companies fight fraud, calculate the number of losses and different probabilities.
Сustomize the formation of the optimal cost of the mortgage insurance product
Dynamic pricing for insurance business
Automatic Document Recognition
Creating a program that recognizes certain types of documents (passport, driver's license, vehicle registration certificate, etc.)
Identifying and preventing fraud in insurance
A service that effectively detects and predicts fraud at the contracting stage.
Insurance portfolio audit
Multivariate portfolio analysis, identification of positive and negative aspects
Using Geodata in Predictive Insurance Models
Algorithms for constructing forecast values of frequency and the average loss in insurance.
Insurance company scoring
Models to predict customer loss, loss size, and the likelihood of buying and renewing a policy.
Patients death prediction for hospital
- build model's death prediction (XGBoost, LGBM, optuna, XGBSE, pycox)
- helps to make life longer
Graph analytics for insurance company
- graph in python networks
- fraudulent customers were found in graph
- results transferred to neo4j
- neo4j was developed to production mode
- graphSage was part of the project
SQL and OLAP cubes development
- we have built SQL databases and OLAP cubes
- developed analytics based on OLAP technology (insurance portfolio audit, price change suggestions, analytic reports)
Detector, segmentator and set of rules for determining damage
A model for searching for structural damage on a small volume of images
Data science You Tube channel
More than 50 research videos (data science, front-end, back-end, product management)
Training course for students and interns of the company
- developed and launched the educational course “Machine Learning in Business”
- trained over 150 students
