Product overview: CreditAIApproved is a smart AI-driven banking app, which provides in-depth analysis of a potential borrower’s credit-worthiness and executes accurate credit decisions.

Issues: We had to make that app that could properly cope with the continuous and rapid evaluation of large amounts of data the credit department of the banking institution had to deal with. From the first sight, it should look rather simple and easy to use, still, at its backend, it had to be a very robust system that was capable to process huge amounts of data and accurately analyze it. We collected and development AI specific algorithms, including fingerprint detection, face recognition & voice recognition so that the CreditAIApproved app could work properly. Here how it should work: the app validates a person’s identity (this prevents fraud and misuse of the banking facility, money laundering, and scams), approves his or her social & biometric data, performs credit risks evaluation to quantify the risk of first-time borrowers. If the person has already had credits, the app checks the person’s credit history, makes AI-based predictions based on the received and analyzed data. Then the CreditAIApproved app should form the auto-generated summaries of the defined data variables and approve or disapprove the credit issue for the particular person. Since it is a banking app, CreditAIApproved should be of premium security. Finally, it should be a self-learning AI application.

Technologies used: Python and Django on the server side and JavaScript on the browser side, for the AI part we used Tensorflow and C/C++.

Result: CreditAIApproved is a high-performance and intelligent automation app, which can in a snap conduct numerous large-scale analyses banking institution had to deal with and execute accurate credit decisions.

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