Coremetrix shows how Fintech can lift people out of poverty
CreditInfo spin-off Coremetrix is launching a new service that could lift many of the ‘unbanked’ of developing nations out of poverty through an alternative method of credit assessment.
The new system compliments or provides an alternative to traditional credit checking methods which too easily write certain people off as an ‘unacceptable risk’, due to the inflexibility of the assessment methods. Many banking ‘have-nots’ are not a bad credit risk at all but simply lack the opportunity to establish themselves.
The new alternative approach taken by Coremetrix uses psychometric scoring which is based on reactions to visual prompts. The system is now being used to establish creditworthiness in several countries including the UK, by Admiral, and South Africa, by Compuscan.
At present, there are 2.5 billion adults don’t use banks or microfinance institutions to save or borrow money. Nearly 2.2 billion of these unserved adults live in Africa, Asia, Latin America, and the Middle East, according to research by McKinsey, March 2010
Financial exclusion also affects a notable European population, with roughly one-fifth of the populations of Romania, Poland and Italy currently classified as uncreditworthy.
According to the World Bank, previous initiatives to bring the ‘unbanked’ into the fold, through mobile banking apps, have helped to ‘lift’ large sections of the population out of poverty. According to the World Bank’s figures, the rise in the number of people who have bank accounts and access to credit (700 million) led to a fall in the number of people it categorised as below the poverty line.
Possession of credit and banking facilities makes the user more attractive to an employer, helps them find better paid jobs and to find homes. Having a fixed address, in turn, makes them likely to find work.
The Coremetrix technique for credit assessment uses an alternative personality-based data set. When lenders have ‘thin files’ on people, such as those with two or less traditional credit records, it then seeks alternative data. If you’re new to the UK, you might be able to open a bank account, but cannot access credit due to lack of credit records.
The system of assessment is based on psychoanalytic traits. For example it can see how conscientious a person is and how they plan for the future, whether they are organised and if they are likely to re-pay. There are 27 traits taken into consideration by the machine.
“Understanding these elements of a person’s personality can really give you an indication as to whether or not they are going to repay,” says Joe Bowerbank, business development director at Coremetrix.