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Where Lenders See Opportunities and Challenges in Adopting More Automation for their Operations

Auto lenders for both prime and subprime audiences recognize the need and importance advanced data technology has on their overall operations, as well as in the accuracy of managing portfolios. Since the pandemic, the integration of artificial intelligence (AI) and advanced data technology has emerged as a competitive strategy for many leading lenders. In fact, many are increasingly recognizing the importance of leveraging these technologies to enhance efficiency, mitigate risks, and deliver superior customer experiences, especially as they inject more automation into their process.

Auto lending has undergone significant evolution over the years, propelled by technological advancements and changing consumer preferences. Traditional lending processes involve manual tasks, lengthy approval procedures, and a high degree of human intervention. However, in today’s digital era, borrowers demand seamless experiences, quicker approvals, and personalized services.

AI and data technology offer auto lenders a myriad of opportunities to streamline operations and optimize decision-making. By harnessing the power of AI algorithms and big data analytics, lenders and subprime lenders especially can gain deeper insights into borrower behavior, assess credit risk more accurately, and automate various stages of the lending lifecycle.

However, automation has been a challenge for some lenders to adopt into their workflows and processes. We know this because of several key areas lender executives have spoken about recently – topics that extend beyond challenges implementing automation, to economic trends and even compliance issues.

Issues that concern lenders today
Many lender executives have said GAP refunds (25.3%), regulatory compliance (22%), delinquencies (21%), and fair lending (21%) were most concerning to them entering 2024. Nearly half of respondents (44%) said they haven’t incorporated AI into their lending because their C-Suite still hasn’t fully bought into the idea, and another 30% said they still aren’t operating in a fully digital environment1.

Much of this concern is driven by their need to create a smoother adoption of digital deal jackets, which can reduce loan defects. Thirty-one percent of lenders said they want to improve dealer satisfaction as a reason to adopt more automation or AI tools for deal jackets; followed by 26% saying they want to compete more aggressively with other lenders. What’s more, employer mismatch (26.3%), income mismatch (24.2%), and missing signatures (23.2%) represent the biggest challenges when it comes to documentation defects today1.

Furthermore, the majority of respondents (44%) said that less than 10% of their deal jackets had defects in 2023; roughly a quarter of respondents said 30% of their deal jackets. While this may not sound like a large number of lenders, consider that another 44% said errors in their deal jackets in 2023 cost them an estimated $1 million in 2023; Nearly a third (30%) said deal jacket errors cost them between $1M- $5M in 20231.

When it comes to accuracy, 46% of lenders said they are most concerned about increasing the number of staff hours to scrutinize accuracy and/or rectify errors.

Building more automation into the lending process
Lenders understand the need for efficiencies that streamline the lending process. Automation is not just a convenience; it’s a strategic imperative in today’s fast-paced environment. By incorporating advanced automation into lending procedures, lenders make more informed and timely decisions, reduce operational costs, and, most importantly, provide an unparalleled experience for their customers.

The reasons for adopting more automation are numerous. Twenty-one percent of lenders recently said automation reduced fraud in their lending process; following by 19% who said it increased speed. Regarding the measurement of success of automation, most lenders (32%) said it improved customer satisfaction; followed by 30% saying it reduced turnaround time. While 41% of lenders indicated budget concerns, another 35% said they are concerned about the lack of knowledge or expertise in making additional implementations1.

AI-powered automation revolutionizes the loan origination process by reducing manual interventions and streamlining workflows. From application intake to document verification and underwriting, automation expedites the entire process, leading to faster approvals and improved operational efficiency. Moreover, AI-driven chatbots and virtual assistants can enhance customer interactions, providing instant support and guidance throughout the application process.

While lenders remain concerned about key areas of their business, it is clear they want to implement data technology and automation to improve their overall operations. By embracing automation, lenders enhance operational efficiency, mitigate risks, and deliver superior customer experiences. As technology advances, the strategic adoption of AI and data technology will differentiate market leaders from laggards in the auto lending industry.

1 Industry Survey Shows Where Improvements Are Taking Place In Leveraging Automation And AI For Lender Operational Efficiency; March 2024

Adine Deford
Adine Deford
Adine Deford is vice president of marketing at Informed.IQ, an AI fintech serving the financial services industry that uses machine learning models to classify, analyze, and extract data from documents used in consumer lending, credit cards, and bank account openings. For more information, please contact [email protected].
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