Audience
Organizations interested in an AI-based solution for automated decision making
About GiniMachine
GiniMachine is an AI-based solution for automated decision making. It utilizes advanced machine learning algorithms and company's historical data to build high-performing scoring models. It can be used for credit scoring, collection scoring, application scoring, and expanding marketing (churn prediction), and sales (cross-sell and upsell) opportunities. The system uses a custom implementation of the decision tree ensemble method strengthened with a set of heuristics for preliminary data processing and preparation. The models that are built and provided by GiniMachine are fully compliant with BASEL requirements. The ability of the software to work with massive amounts of data can simplify the application scoring by identifying creditworthy borrowers in various industries. Using historical data of your business, GiniMachine can increase the returns in online loans, auto finance, POS lending, and more.
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"Credit Scoring for Online PayDay Loan Company" Posted 2021-04-06
Pros: Functional and affordable software for AI/ML decision-making in lending. Requires no complicated training. Implementation and onboarding are super fast.
Cons: The software requires quite a large amount of data for reliable predictive analytics. We had enough, but some customers may not have enough data (1000+ loans issued).
Overall: Our company purchased GiniMachine for credit scoring when providing online payday loans. We are a fintech company located in Central America. Daily we deal with a great number of loan applications, so our goal was to speed up the credit scoring and decisioning. We found GiniMachine AI, reliable software for automated credit scoring that takes into consideration traditional and alternative credit data. It uploads the array of historical data and builds scoring models in a few seconds. It helps us manage risks, shorten the time for decision-making and approve more loan applications, thus increasing profit at medium risk.
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