Can digital footprint eliminate credit worthiness doubts?

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Most developed nations use a credit scoring system of some sort, and others are following suit, adopting alternative traditional methods of establishing credit worthiness – income stability, default history, etc.

In China, for example, a social credit score assesses every aspect of an individual’s life, while France still doesn’t use a structured credit scoring system. For its part, Germany’s Frankfurt School of Finance & Management (FSFM) claims that information left by an individual simply by accessing or registering on a website can be used to predict his/her probability of default. But, what about individuals with no credit history? An estimated two billion adults worldwide have no access to credit. Can a digital footprint be used as a yardstick in such cases?

The FSFM study investigates out how relevant an individual’s digital behavior would be in establishing his/her credit worthiness and how that compares with traditional credit bureau recommendations. It emphasizes that a digital footprint is a very important index for screening individuals seeking consumer loads. In the study, (read it here) the researchers use various digital behavioral traits, such as the time of the day an online purchase is made, which channel the user is coming from, what kind device is used (iOS or Android), etc. It even considers whether an individual used an email address that is consistent with his/her name or something that looks more like a fake one. Ultimately, the study establishes that benchmarking certain digital traits in the context of credit risk is consistent with the recommendations of credit scoring models.

My focus is to discuss the viability of incorporating such a dimension in evaluating credit worthiness. It’s a great advantage for credit providers, specially the new-age digital banks that mostly (or solely) focus on digital channels for direct banking. It is also understandable that the more digital footprints are accumulated and analyzed the better the profiling of target customers can be, and the better the predictions that would result. This makes it possible to target populations with little or no credit history, younger participants who are active on digital channels, including social media, but don’t necessarily have a credit history), or migrants, some of whom can be quite creditworthy.

The FSFM study is based on a German e-commerce company that works on a pay-on-delivery model. Let’s try to extend this setup. Amazon gathers tremendous amounts of data from consumer and retailer from daily transactions. Today they extend point of sale credit to buyers by offering no cost EMIs for purchases. At the same time, they extend business credits to Amazon sellers. While I don’t exactly know how they establish creditworthy sellers, some of the determinants must surely depend on the sellers’ history established through their transactions – sales volume, customer rating and products sold, etc.

Perhaps in some not-so-distant future, Amazon will expand into the retail consumption loans business. Some factors to consider then would include purchase history, on-time payment, number of returns, kinds of products purchased (one could argue that someone buying expensive books online is more creditworthy than someone ordering cheap cellphone covers). These are the behavioral aspects essentially established through our digital footprint on Amazon. A retail giant such as IKEA can also leverage their customers’/suppliers’ digital footprint to evaluate credit scores and extend loans via their retail bank Ikano.

There are several banking subsidiaries of telcos worldwide and there are partnerships. These operators can leverage the scores customer data gathered through telecommunications services in evaluating financial status/stability by evaluating the digital footprint.

So, all credit players in the market either providing complete digital solutions or prioritizing digital services some way or another consider prospects’ digital behavior. Entities with access to online customer data are at an advantage here. Is it possible that eventually payers such as Amazon will start selling digital credit scores (evaluating credit worthiness based on digital behavior) to banks, credit institutions, etc.?

Privacy concerns

This promises tremendous opportunities to get more loans business and increase market share. But establishing digital footprint analysis as a standard approach in credit evaluation is still far-fetched due to privacy concerns. Depending on the country or region-specific restrictions, the possibility of leveraging customer data may be limited. The downside is that considering a digital footprint in credit scoring can affect everyday life. Potential consumers must constantly consider these footprints, usually left without serious thought.

This subject is prominently manifested by China’s social credit system. The system aims to understand and evaluate citizens’ and business’ economic and social reputation. There is a lot of literature on this topic (read more here) and I won’t elaborate in this blog other than to point out the potential impact it has – jaywalking repeatedly may affect one’s credit score. This kind of surveillance mechanism won’t fly in most of the societies worldwide, for obvious reasons.

What is the least we can do with digital footprint analysis?

We discussed both the potential of leveraging digital data in credit analysis and the dark sides of doing so. While we are still far from establishing this aspect as a standard mechanism or policy led by regulators; social or digital behavior can be used to identify the credit risk factors to begin with. Wherever there is enough information available, it can be used to determine whether a person poses a high risk of default. This would help in eliminating such cases quickly from the process. To be clear, I’m not saying that the lack of a digital footprint should be treated as a bad digital record. Rather, in cases where there is enough information about a prospect’s online behavior for a credit organization to make an informed decision, it should be used. In the case of Amazon, if a supplier’s products have been repeatedly returned due to quality issues or missed delivery deadlines, extending a loan to that business may not be worthwhile.

It remains to be seen how and when this dimension is broadly included as part of credit evaluation process and how well marketers react to that. For now, as consumers and users of the internet, we need to move prudently to remain prospects worthy of credit.

Views and examples of work being done on this topic elsewhere is highly welcome and appreciated.

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