rethink everything

    Psychometric testing can change finance forever

    RE-Wave3_AuthorsWeb-Lumley.png   By James Lumley, Business Writer for the South China Morning Post,
    the Irish Independent, the Sydney Morning Herald

    When data giant Nielsen bought London-based audience data business VisualDNA in December 2016, it was investing in technology that has been quietly revolutionising banking in emerging markets.

    That's because VisualDNA is one of the world leaders in psychometric testing, a method that is being used to assess the creditworthiness of individuals and businesses with no debt history.

    It is enabling lenders to access previously untouched markets in Asia, Africa and Latin America.

    As an investment, backing one of the many psychometric testing firms operating right now ticks many interesting boxes

    It is an investment in fintech, banking, big data and emerging markets, to name a few categories. But on top of that, it is also an investment in a technology that is improving financial inclusion in the developing world, and giving emerging market entrepreneurs access to vital credit for the first time.

    As such, it fits Bill Gates' definition of "creative capitalism" namely "an approach where governments, businesses and nonprofits work together to stretch the reach of market forces so that more people can make a profit, or gain recognition, doing a work that eases the world's inequalities."

    But what is it?

    Psychometric testing is a scientific method of judging character by using quizzes. Typically, companies that produce them use a mixture of questions and pictures to rate individuals' characteristics.

    There are no obvious answers, which is supposed to make them impossible to "game", and extensive cross-referencing identifies cheats. A well-designed test can assess, for example, how reliable, honest and risk-taking a person is.

    And lenders can use this information to decide whether the person being tested is a suitable candidate for a loan. A good example of one can be found on VisualDNA's website.

    The tests are complicated to produce and have to be minutely tweaked for different cultures. Like many of the most cutting-edge technology firms, the companies that produce them are often university spin-outs.

    Entrepreneurial Finance Lab (EFL), another market leader, started off as a research initiative at Harvard University, while rival Creditinfo was developed with help from the University of Cambridge.

    It is, therefore, clear that these sort of tests bear no relationship whatsoever to the sort of "Which Game of Thrones Character Are You?" quizzes that litter social media.


    The reason why they are so useful is because, in the previously-un-banked developing world, whole populations have absolutely no credit history. The only way creditworthiness can be assessed is through demographics.

    Statistical analysis is a powerful tool. But few lenders will extend credit to a customer solely based on the fact that people in that customer's position tend, on average, to be reliable.

    Psychometric testing, however, personalises the process. It fills a vital information gap, allowing the lender to judge with much greater accuracy that customer's likelihood of default

    But does it work?

    It is not a surprise that the World Bank, which was set up to use capitalism to fight poverty, is very interested in the use of psychometric testing in the developing world.

    The bank decided to test the method's effectiveness. To do this, they worked with a large bank in Peru to scrutinise the usefulness of EFL's tool designed to reduce the risk of lending to small and medium sized enterprises.

    They used Peru because the presence of private credit bureaus in the country means that every citizen has a credit score. At the same time, many citizens haven't taken out credit before, so lenders tend to use demographics to assess credit risk.

    This means that the World Bank was able to compare data from customers granted loans using a traditional credit score against those granted loans based on psychometrics.

    After a year, 27% of applicants who had been granted a loan based solely on their traditional credit score found themselves in arrears.

    However, only 15% of applicants who had been rated with help of the EFL tool were behind in their payments.

    "The results illustrate that psychometric credit scoring is a viable tool, both to reduce risk on applicants with a credit history, and to reach applicants without a credit history in a way that does not lead to an increase in credit risk," the Bank said in its report.1

    The theoretical attractiveness of tapping the potential of emerging markets needs little explanation. New markets mean new profits, but they also mean new risks.

    According to The Economist magazine, only 7% of Africans and 13% of South Asians are covered by private credit bureaus, which means that most of them would be generally ineligible for credit based on traditional concepts of risk.

    By providing reliable behavioural data, psychometrics, therefore, bridges the gap between investment opportunity and investment risk

    Even so, not all psychometric tests are created equal. Clearly, some providers will be better than others. There are clear market leaders today, but who knows who will be in pole position tomorrow?

    One thing is clear: investing in a company that creates psychometric testing is an investment in which big data, fintech and emerging markets intersect to create a product that aids financial inclusion, and helps alleviate poverty.

    On that basis, it is probably worthy of consideration.


    Important information

    This document is issued by Bank Lombard Odier & Co Ltd or an entity of the Group (hereinafter “Lombard Odier”). It is not intended for distribution, publication, or use in any jurisdiction where such distribution, publication, or use would be unlawful, nor is it aimed at any person or entity to whom it would be unlawful to address such a document. This document was not prepared by the Financial Research Department of Lombard Odier.

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