As many as 63% of customers never complete their loan applications. There are numerous causes for these high drop-off rates, but one, in particular, irritates digital lenders: convoluted journeys.
Borrowers are frequently taken off guard and misled into believing that the digital loan journey will take place exclusively on their mobile phones. However, they are left scrambling for financial statements and bank information that aren’t easily available.
In a world where buy-now, pay-later (BNPL) and immediate credit guarantee cheap financing, this presents a significant challenge for lenders. In actuality, the underwriting process, which should take two minutes and end with a few clicks, might take many hours or even days. This contradicts the promise of quick digital credit.
On the other hand, assistance is on its way. Enabling dynamic onboarding is now possible for digital lenders thanks to the development of alternate data underwriting and the Account Aggregator architecture. This has made it possible for digital lenders to construct onboarding and underwriting funnels that are extremely quick.
Combining the robustness of alternative underwriting with the speed of rapid confirmation provided by AA’s formally organised and encrypted data is one way to achieve this goal. What do we get in the end? Your BNPL account or credit line account can be activated in fewer than three minutes at your request.
Let’s have a look at how this works behind the scenes by getting into the details.
Credit Underwriting’s Two Pillars
If financial data can help determine the ability to pay, credit history can help determine intent. Manual underwriting, which tackles the ability question, and traditional credit bureau ratings, which show a customer’s intent to repay, have been mostly phased out of digital lending.
Alternative Data and Information
Traditional credit scores only consider a few behavioural factors. They take into account four or five criteria, such as payment history, credit history length, number of hard inquiries, amount owing, and credit mix. This effectively excludes new-to-credit or thin-file customers, resulting in a limited underwriting view.
FinTechs are perfecting the first part – determining the ability to pay – by supplementing bureau ratings with alternative data underwriting. In-device risk engines, such as Whatso DeviceConnect, enable lenders to search for indicators of borrowers’ financial health, such as cash flows, spending patterns, social and internet behaviour, and the types of apps installed on their smartphones.
Lenders have also created sophisticated technologies for analysing financial records digitally. They can parse PDFs, pictures, or handwritten text using technology such as optical character recognition. Artificial intelligence and machine learning models are also assisting in the acceleration and scalability of alternative data underwriting.
Prior financial behaviour and credit history can also be used to assess payment intent. However, until now, borrowers’ credit histories have been derived from agency scores or manually uploaded financial data. While the former is notorious for being discriminatory and insufficient, the latter exposes leaks in otherwise flawless application journeys.
The Account Aggregator framework can improve underwriting clarity and precision in terms of payment intent and capabilities. Account Aggregator financial data can be used to cross-check alternate data collected from the device. During the loan journey, lenders can obtain additional data points from a variety of financial information providers (FIPs) such as mutual funds, insurance providers, tax and GST platforms, and banks.
End-to-end encryption of data as it travels from the FIP to the account aggregator to the FIU eliminates the possibility of document tampering. Lenders can reduce the likelihood of fraud and minimise adverse selection by directly sourcing information from a number of financial entities.
For example, a borrower’s bank statement may be manipulated to appear to have solid investments, yet data from their mutual fund may suggest missed SIP payments. With this information, lenders can properly price the loan or even reject the application early in the financing process.
Underwriting is a crucial component of the lending process. It provides assistance to lenders in the process of selecting loan principal amounts, interest rates, risk pricing, and collection strategies. On the other hand, the capabilities of alternative data and Account Aggregator, when combined, considerably improve the experience that the customer has.
Improve Confidence Scores
Access to a broader, new-to-credit customer base provides lenders with massive business potential. At the same time, it departs from typical banks’ one-track lending flow. In the absence of adequate bureau data for new borrowers, lenders turn to a variety of other sources. This allows you to increase the number of checks for each instance until an acceptable confidence score is created in accordance with the lender’s requirements.
Underwriting, for example, can begin with a simple credit score check. If the results are unacceptable, the lender can look into alternative device data. If the applicant still falls short, bank statement and Account Aggregator data can be obtained. If the borrower is looking for a larger loan, lenders can boost confidence by incorporating procedures such as video KYC and physical verification.
Journeys That Are Adaptable
The powerful combination of alternative data and Account Aggregator provides the necessary checks and balances for lending in new-to-credit markets. However, it can also improve the user experience. Platforms can create adaptable onboarding experiences for a variety of risk profiles. They can keep good borrowers (who won’t have to jump through hoops during onboarding) while filtering out problematic borrowers (who are likely to do whatever it takes to get a loan) from the start.
For example, at the time of checkout, platform data is used to prequalify two borrowers for a loan. Both apply, but preliminary data such as platform activity and credit score indicate that one has a better credit history than the other. The lender only uses Account Aggregator checks and video KYC for the initial borrower. The second borrower, who has a less than stellar credit history, is subjected to AA, video KYC, and physical verification.
Underwriting That Will Be Fully Operational In The Future
The early years of digital lending facilitated a transition from loans requiring a lot of paper to loans that did not require any paper at all. The alliance of alternative data-account aggregators is now in a position to guide digital lending into the next phase of its evolution, which is one in which speed, accuracy, and usability take precedence. The following is the procedure:
- Increasing both the confidence and precision of underwriting through the utilisation of a variety of alternative data types. The process of cross-referencing this data with formal financial data sources is something that account aggregators may help with.
- Create flexible application pathways for loans, complete with individualised checkpoints, in order to provide a superior user experience.
- Lowering the cost of underwriting by eliminating the need to build workflows or funnels for the manual or automated review of manually supplied bank statements
- Enhancing the spread of products such as BNPL outside of metropolitan regions by providing access to credit for borrowers in the hinterlands who have thin credit files or are just starting out in the credit world.
- Increasing the collection efficiency by utilising alternative data-based intelligence to send a real-time warning signal on borrowers who are already delinquent or who may become delinquent in the future.
We at Ignosis have developed a new-age tech stack for the digital lending ecosystem. Our mission is to democratise digital lending and make it efficient and accessible across the entire digital ecosystem.