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Adapting to the Next Frontier in Lending:

AI-Driven Credit Decisioning in Uncertain Times

Economic uncertainty has prevailed into 2024 with rising defaults and inflationary pressures. However, AI has the potential to help credit unions successfully navigate these headwinds. 

Despite high interest rates, the American consumer is increasingly turning to personal loans to help manage their rising monthly household expenses; according to Transunion, unsecured personal loan balances grew 9 percent year-over-year in Q1 2024.1 To help lend safely in this challenging environment, credit unions can harness AI to help deliver the funds consumers need in this inflationary environment while meeting higher return and lower loss targets. 

AI and machine learning (ML) enable unprecedented advancements, particularly in the realm of consumer lending. Upstart has been at the forefront of using AI to improve consumer lending for both credit unions and their members. Over ten years, Upstart has facilitated nearly $40B2 in loans for its lending partners to over 3 million3 American consumers, showcasing how AI and ML can reshape underwriting for the better.

How Upstart drives positive change for borrowers:

  1. Better risk assessment: At the core of Upstart’s mission is a desire to expand access to affordable credit by enhancing underwriting using the power of AI. By using vast datasets, Upstart’s models separate risk 3-6x better than traditional methods.4 Unlike conventional approaches that rely on summarizing credit data, Upstart’s AI uses over 1,600 variables trained on 65 million repayment events and factors in market conditions, giving credit unions improved accuracy to safely approve creditworthy borrowers. 
  2. Faster decisions and funding: Speed is another benefit of AI-driven lending. With loan decisions rendered in seconds and funds distributed to borrowers within the same or next day, Upstart delivers an experience akin to the experience consumers expect from their everyday providers like Amazon and Uber. This rapid service not only meets but exceeds consumer expectations, enabling lenders to set the standards for efficiency in the industry.
  3. Cost savings: AI enables credit unions to offer loans at a fraction of the cost compared to traditional methods. By automating processes and minimizing human intervention, Upstart achieves high cost efficiencies. In fact, 90 percent of Upstart-powered loans are processed without human intervention, showcasing the potential of AI to streamline operations.5 
  4. More inclusive decisions: Upstart's AI models also enable credit unions to lend more inclusively while employing more accurate risk assessment. Upstart approves 101 percent more applicants than traditional methods, also extending 38 percent lower APRs to qualified individuals, contributing to greater economic empowerment and bridging existing gaps to credit access.6 

Compliance excellence is the core of success

The integration of AI into lending, however, necessitates rigorous compliance measures to safeguard against potential biases or discriminatory outcomes. Upstart developed a Fair Lending Testing Program alongside the Consumer Finance Protection Bureau (CFPB) to meet the highest testing standards and ensure ethical and equitable lending practices. Each new model Upstart introduces undergoes rigorous fair lending testing before being introduced to lending partners.  

Upstart is committed to enabling its credit union partners with robust risk management protocols and helping them best prepare for regulatory examinations. Upstart has introduced the Upstart Program Certification, which includes modules that equip its lending partners to effectively explain the Upstart program and navigate regulatory examinations with confidence and competence.

Serve existing members in uncertain times

In today’s uncertain economic landscape, credit union leaders want to focus on retaining, serving and lending to their existing members. To help credit unions retain and deepen these existing relationships, Upstart developed Recognized Customer Personalization (RCP). With RCP, Upstart can identify when an existing member of a credit union is applying for a loan on Upstart.com. For partner credit unions, Upstart can ensure that the credit union is able to provide their members a compelling offer of credit. This enables credit unions to further tailor loan offerings, strengthening relationships and fostering long-term member loyalty. 

Then, once the credit union is ready to grow its membership, it can add a configuration to the program to extend offers to new members applying at Upstart.com, using the same or modified credit criteria. From there, Upstart can help the credit union cross-sell and further cultivate these new member relationships for long-term growth. 

Embracing a future where AI creates better lending outcomes

After 8 years of partnering with over 1007 banks and credit unions alike, Upstart has learned that starting small and gradually scaling operations allows for a more manageable transition–in essence, a "crawl, walk, run" approach. By leveraging AI responsibly and ethically, credit unions can usher in more innovation, efficiency and accessibility in their lending practices, ultimately driving positive economic change and financial inclusion for all.  

 

[i]  TransUnion. Q1 2024 Quarterly Credit Industry Insights Report (CIIR). May 2024.
[ii]  As of 4/30/2024.
[iii]  As of 4/18/2024.
[iv] Based on Upstart internal performance data as of March 12, 2024. Consists of all originations from the Upstart Platform made 2018-Jan to 2024-Feb vintages.
[v]  In Q1 2024. Percentage of Loans Fully Automated is defined as the total number of loans in a given period originated end-to-end (from initial rate request to final funding for personal loans and small dollar loans, and from initial rate request to signing of the loan agreement for auto loans) with no human involvement required divided by the Transaction Volume, Number of Loans in the same period.
[vi] As of publication in June 2024, and based on a comparison between the Upstart model and a hypothetical traditional model using Upstart data from Jan - Dec 2023. For more information on the methodology behind this study, please see Upstart’s Annual Access to Credit results here.
[vii] As of 4/30/2024.

 


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