In its mission to push for financial inclusion, Union Bank of the Philippines (UnionBank) now uses Machine Learning and Artificial Intelligence based scoring models to determine eligible loan applicants.
Banks have traditionally determined loan eligibility to micro, small and medium enterprises based on their credit history, collaterals and other financial information. This has meant that other factors were usually not taken into consideration when making loans available.
Using Artificial Intelligence and Machine Learning based scoring models, the bank has been able to include other means of determining the risk levels of loan applicants and thus make it possible for them to qualify when compared to just looking at traditional factors. The AI and ML based scoring models leverage on the patterns of customer behaviour by using alternative data points such as geographical metadata, socio, macro-economic and other publicly available data from the government.
“We are walking the talk. Everyone talks about financial inclusion but when it comes down to assessing eligibility, the measures used are the traditional one - thereby still excluding the same people we wish to include,” said Chief Mass Market and Financial Inclusion Executive Manuel Santiago.
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