How Lenders Can Score and Approve More Applicants While Managing Risk
How Lenders Can Score and Approve More Applicants While Managing Risk
The nation鈥檚 consumers are becoming even more financially diverse. Think about young consumers and the growing number of immigrants who have little to no credit history. Plus, there are millions of credit-rebuilding consumers that may turn to nontraditional sources for their financial needs.
This can present a challenge for credit card, consumer finance, and auto lenders who want to drive responsible portfolio growth. These lenders want to bring in more new customers for their loan products, yet are relying on credit-based decisioning models. While traditional credit reports remain a strong indicator of credit history and past financial behaviors, lenders could be missing out on these diverse audiences-- especially if they aren鈥檛 able to score and approve them using traditional risk models. And, lenders could be missing out on additional pockets of risk that could be surfaced by considering behaviors that lie in sources beyond the traditional credit file.
That鈥檚 why lenders can benefit from 鈥 a multi-data credit score that can help lenders gain a broader view of consumers鈥 creditworthiness for offers. It鈥檚 a single score, yet it incorporates multiple alternative consumer financial datasets 鈥 including telco, pay TV and utility account payment history, specialty finance data, and trended credit data.
This is the type of data that lenders need to better understand consumers鈥 payment behaviors and financial habits. Almost all consumers have a utility or cell phone bill. Plus, 80 million use specialty finance services. Lenders can use this data to consider many more consumers for their offers than they would otherwise. Read more about the foundation of OneScore in our previous article.
Use a single score to boost financial inclusion
Financial inclusion is an important tenet for many lenders. Especially lenders that want to expand their customer-base beyond the prime segment. To help accomplish this goal, lenders can use OneScore to both score more consumers and to determine if they present higher risk.
One prime and near prime lender that is focused on financial inclusion wanted to explore solutions to better serve thin file, subprime, and credit invisible consumers. An analysis showed that the lender could use OneScore to enhance its origination decisioning and expect to:
Score over 3% more applications per year (compared to a traditional credit score alone)
Gain a 20% lift in predicting delinquency for thin file and near prime segments (again compared to a traditional credit score)
Achieve up to 5x incremental risk separation within the same risk score range (by supplementing a traditional credit score with alternative data in OneScore)
This last concept of risk separation is especially important. What this means for lenders is that they can use OneScore to segment consumers within a designated risk score range to:
Identify hidden opportunity amongst applicants that are less likely to go delinquent (in the same risk score range), and
Avoid future losses by differentiating applicants that are more likely to go delinquent (in the same risk score range)
Fuel AltFi and FinTech lending decisions with a broader view of consumer finances
Services provided by alternative finance (AltFi) and Financial Technology (FinTech) lenders are often marketed to younger generations and subprime consumers. However, these audiences may be lacking a comprehensive credit file which can limit effective decisioning. With a single risk score that includes alternative datasets, AltFi and FinTech lenders can gain expanded insight on how consumers manage bill payment and other financial habits. Then, they can make more informed decisions about whether an applicant has the desired financial characteristics for a new lending product.
Here鈥檚 a good example of how this can apply to a Buy Now Pay Later (BNPL) FinTech lender. The company offers point of sale installment loans, but was struggling with unexpected high delinquencies from its credit-based risk model. By incorporating a broader view of consumers鈥 finances with a score that combines both traditional credit data and alternative data (such as OneScore) into its decisioning, the lender is much more likely to:
Say 鈥測es鈥 to more by approving 12% more applications without incurring additional risk
Address possible future losses by achieving a 57% lift in predicting delinquency
With a more robust picture of consumers who are actively seeking new financial services, lenders can more confidently:
inform loan decisioning
expand their customer-base
better provide appropriate terms
鈥 all of which could translate into millions in new revenue, while managing risk. Learn more about how your firm can score more consumers, better by exploring the OneScore and video.
Ready to see how your organization might benefit from OneScore? Contact our team to request a validation.