GiniMachine is an AI-based decision-making platform that utilizes advanced machine learning algorithms and the company's historical data to build high-performing scoring models. It can be used for application scoring, credit scoring, collection scoring, marketing purposes (churn prediction to create personalized offers), and sales activities (cross-selling and upselling opportunities). GiniMachine adds value to banking, finance, telecom, and other businesses able to provide large datasets for analysis. The system uses a custom implementation of the decision tree ensemble method strengthened with a set of heuristics for preliminary data processing and preparation. Key benefits of the solution are: Fast, fully autonomous, and automated model building process. With a prepared dataset, it takes only 2-10 minutes to build and validate a scoring model. Thus, it saves hundreds of hours of manual work for risk officers and data analysts. High performance and predictive power of a model. Typically, up to 15 points of the Gini Index compared to traditional models based on logistic regression (logit). Ease of use — no special training required to build a model. Built-in scoring model evaluation and validation tools. Ability to use unstructured and big data, handle imperfect and missing data, find hidden dependencies. Proven economic efficiency — fewer NPLs, better performance of a loan portfolio, higher acceptance rate, etc. Besides, GiniMachine is a great data analysis tool for risk managers. It provides valuable insights into lender’s data and serves perfectly well for exploratory analysis.