A Qualitative Design Approach to Digital Loan Products can Reduce Indebtedness in Kenya

Disclaimer: This article is not sponsored by any financial services provider. It should not be taken as an endorsement to mentioned services. Examples have been used at the writers discretion.

The Digital Credit scene in Kenya is heating up. There are more than 25 products currently in operation. In the past two months, market leaders Tala and Branch, have closed huge funding rounds while the relatively new Okash by Opera has become one of the most downloaded apps on Google Play Store. As we celebrate how fast short-term liquidity has become valuable, there’s growing concern regarding indebtedness and poverty exacerbation.

One major factor that has been associated with misuse of credit leading to indebtedness is lack of transparency in the cost of credit and the general low literacy on financial management. While a debate on regulatory framework rages on, I have wondered how the credit providers can use available data in their design approaches to tame such adverse effects.

Digital credit products take great pride in the speed at which applications are made, approved and dispatched to mobile money wallets. Don’t get me wrong, this is a good thing. It’s where traditional credit has failed with long processes, paperwork and evaluation. However, the prime value that has been placed on speed and access may have inadvertently trivialised customer decision making thus promoting impulsive borrowing and spending. The user experience does not promote credit discipline or make loan requests a deliberate decision making process.

A big part of it is through presentation of confirmation prompts, full disclosure of cost of credit and Terms & Conditions to ensure the consumer is fully aware of their obligations. For many of these apps, such information is tucked away on a web page that requires the user to leave the app and pore over long winded prose full of legal jargon. It’s almost as though it was designed never to be read. Presenting such vital information in a way and form that’s palatable to the customer base while prompting for confirmations can implore a degree of deliberate decision making and weed-out credit misuse.

In addition, financial literacy and credit management education can be weaved into the application process. A user may have to read a credit tip or answer a question before completing the process. This would also be a good stage for product managers to test for the effectiveness of such a feature by contrasting credit scores and repayments of those who read the tips and those who consistently skip them. A literate consumer base translates into sustainability in the long term.

A good case in point is Loop by Commercial Bank of Africa (CBA). Granted they are not just about digital credit, but they have invested a lot in design to improve customer interaction and the general utility of the product. As an example, Loop sends a code to your email when you request for a loan with a loan amortisation schedule attached. The user must type the loan code back into the app for the transaction to go through. To many this may sound as a feature that would reduce conversion both by presenting potentially disheartening financial obligations upfront and by making the application process lengthy and slightly tedious. However, when someone wants credit, they want credit and you would rather have them know exactly what they are getting into and make the choice to accept or decline the offer. Eventually, your loan portfolio may perform better with fewer well informed decisive subscribers than thousands happy go lucky impulsive consumers.

We can go on and on about design changes digital credit providers can employ to remove inherent risks built into their products, reduce multiple serial borrowing and even offer different approval processes to defaulters or various credit score classes. However, the first hurdle is to recognise how qualitative decision making through data driven design approaches can impact the product. So far the market response validates the need for digital credit, but it’s long-term effectiveness and impact on financial inclusion will depend on responses to such emerging issues being observed from consumer data and market research.