This article originally appeared on Analytics Insights.

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Credit was an art. The emphasis being on was. It used to be based on how trustworthy a person was in the past, which other trustworthy people could vouch for them, and the art of reading a person based on no hard facts. Yes, credit was a very subjective form of art that could sway in any direction.

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With time this evolved. We moved to a more quantitative way of giving loans. Credit bureaus flooded the market with numbers tagged to each person based on various data – sometimes accurate, sometimes not- available from different sources. The science behind credit was taking shape but was far from perfectly predicting the creditworthiness of the applicants. Lenders still rejected applicants based on redlining, and other prejudiced, subjective factors.

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But today, things have changed. Every minute we take 2.3 million photos, we send 16 million text messages and 156 million emails. We place 154,200 calls on Skype and take 45,788 Uber rides. In the last two years alone, we generated 90% of the data in the world and we have left more digital footprints than ever before. That’s a lot of data on me and you. Enough for anyone with access to the right algorithm to convert my digital footprint to a behavioural score that can predict exactly how trustworthy I am.

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CredoLab is doing exactly that. We use machine learning algorithms to convert the metadata of the smartphone device of the applicant into highly predictable, reliable, behavioural score. This gives the power to each and every individual out there who do not have the credit history, in the traditional sense, to fulfil any other personal aspiration of theirs.

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With the boom of technology using AI, we can now pull the plug on all the unfair vagueness that traditional credit scored was plagued with and open the credit industry to a wider pool of people who are just as creditworthy (if not more).

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