MegaFon: Machine Learning Cuts Bank’s Loan Loss
6 September 2016 (12:52)
UrBC, Yekaterinburg, September 6, 2016. AI Machine Learning options offered by the telecommunications provider MegaFon allowed the Ural Bank for Reconstruction & Development to reduce its expected loan loss by as much as 8%, MegaFon’s press service reports.
MegaFon and UBRD Group first announced they were going to work together at the Innoprom 2016 International Exhibition in July. MegaFon’s service is now available to two of the Group’s leading institutions, VUZ-Bank and UBRD, and is used to ensure a better estimate of a borrower’s paying capacity and more efficient repayment risk management. Machine Learning also helps to prevent fraud.
‘MegaFon’s new service improved our borrower’s paying capacity evaluation procedure immensely. The entire thing still takes the same amount of time as before, but relying on artificial intelligence means we can know with much more certainty whether a loan applicant will be able to repay the loan. The system assesses both the probability of default on a debt by the borrowing party and the probability of fraudulent behavior,’ says UBRD Credit Risk Analysis Director Alexander Trofimov.
MegaFon and UBRD Group first announced they were going to work together at the Innoprom 2016 International Exhibition in July. MegaFon’s service is now available to two of the Group’s leading institutions, VUZ-Bank and UBRD, and is used to ensure a better estimate of a borrower’s paying capacity and more efficient repayment risk management. Machine Learning also helps to prevent fraud.
‘MegaFon’s new service improved our borrower’s paying capacity evaluation procedure immensely. The entire thing still takes the same amount of time as before, but relying on artificial intelligence means we can know with much more certainty whether a loan applicant will be able to repay the loan. The system assesses both the probability of default on a debt by the borrowing party and the probability of fraudulent behavior,’ says UBRD Credit Risk Analysis Director Alexander Trofimov.
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