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Credit scoring model uses online data to assess borrowers’ affordability

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  • 25/01/2016
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Credit scoring model uses online data to assess borrowers’ affordability
Credit assessment company Big Data Scoring has released a cloud-based model that collects online data about potential borrowers in order to assess their affordability.

Public information about a mortgage applicant is taken from a variety of websites, including social media pages, blogs, online auction pages and government sites to create a credit score indicating the likelihood of default.

Data considered includes basic information such as employment status, as well as online behaviour, such as how often a borrower uses social media during working hours, or what type of gadgets they use.

The model can help lenders assess the affordability of borrowers like millennials or non-UK nationals, who do not have much credit history, to avoid them offering either too little or too much credit. The provider said this will improve the quality of the lending and reduce risks, while making sure borrowers are not saddled with debt they cannot afford.

“Too much credit is a consequence of the current failings when it comes to credit scoring young people and highlights the need for action to ensure people are given what they need but also what they can afford,” said Erki Kert, CEO at Big Data Scoring.

“Young people have come into adulthood with an almost immediate online presence, unlike previous generations. We have seen this can be as much, sometimes more, of a barometer of their creditworthiness as the traditional approach applied to older people.”

He said banks are increasingly using this method to support their credit checking, and that it should eventually become an industry standard.

Kert argued that banks and lenders have a duty to lend responsibly and sensibly, but that they cannot always do so because many still rely on outdated credit scoring systems.

 

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