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Leveraging PSD2 for credit scoring and lending

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With PSD2 around the corner, both banks and aspiring third parties are preparing for what seems to be a new dawn for financial services. However, the discussions so far have been revolving around on potential loss of transaction revenues and the battle for the customer relationship.

PSD2 will surely raise the stakes for keeping the customer relationship and challenge transaction revenues when payments transition from traditional schemes to account-to-account payments. However, at the end of the day, the majority of bank revenues are from loans, and how will PSD2 impact lending?

As of today, banks are depending on credit rating agencies like Bisnode and Experian to calculate the creditworthiness of new customers based on historical data such as whether you pay your bills on time, and outstanding credit. To enrich this approach, banks may supplement this with a personal assessment to get a holistic view of the customer, but this is a manual and cost-inefficient process. A more scalable approach is to utilize transaction data to analyze spending habits and get an impression of the overall financial health and ultimately get a more precise probability of default.

In a time where everyone is looking for data-driven business models, transaction data is the gold standard of behavioral data.

The challenge with this approach is that the availability of transaction data is limited to existing customers, resulting in banks offering very few unsecured personal loans to new customers. Fintechs have also tried to circumvent the lack of access to transactional data by looking for alternative credit scoring models, but apart from some honorable exceptions such as Klarna and Kreditech, this has in many cases resulted in unnecessary complexity and increased errors.

With the implementation of the XS2A-rule under PSD2, banks will soon be able to access this data from other financial institutions through standardized APIs as well, thus have the ability to determine risk for new customers with much better precision.

This represents several benefits as banks who are able to leverage this opportunity by not only expanding the addressable market but also improve conversion rates from loan applicants to approvals. In addition, this will contribute to an overall better customer experience, as banks will be able to provide better customer feedback by having access to better data. A digital-only approach to lending based on available data through open APIs will shorten provide approvals in mere seconds and lower processing cost through scalable processes.

This opportunity surely favors born-digital challengers and new entrants with limited legacy and an appetite for growth who now will be able to enter a more level playing field when facing incumbent banks when challenging their core business.

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