Large lenders, banks, and investment firms are betting big on AI.

That’s the right idea. Generative AI holds immense potential for enhancing originations, compliance management, customer experience, and loan servicing.

But those large organizations are also sinking time, money, and resources into developing their own tools. 

Smaller, more agile teams are making a smarter play - partnering with fintech companies who have solutions that are built, tested, and ready to deploy. 

Here are the top four places you can lean into generative AI, and what to look for in a partnership. 

1. Originations

One of the first places we saw lenders investing in generative AI was originations, which has turned out to be a smart play, though not without risk.

Led by mortgage and auto finance companies, lenders have uncovered new efficiencies and incredible value from using generative AI during the origination process.

By using multiple forms of artificial intelligence, including generative AI, lenders have been able to scale their processes to manage a greater number of applications, incorporate alternative data for customers who are credit invisible or might have been viewed negatively by traditional sources, and increase financial inclusion without increasing risk.

If you haven’t yet explored generative AI in originations, you’ll find solid foundations here, but it’s not actually the quickest path to ROI. 

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2. Compliance

Instead, if your lending team is looking for the most bang for your proverbial buck, you’d be wise to start with compliance workflows.

The CFPB’s aggressive attention to consumer complaints and regulatory violations has made the already-central task of compliance audits even more important.

In this environment, time- and labor-intensive manual processes that can only cover a miniscule percentage of calls isn’t enough anymore.

Fortunately, compliance is a perfect fit for automation. AI trained on consumer finance can easily tag, flag, and score borrower interactions, cutting processing time to seconds, and increasing coverage to 100%. No more wondering what was missed.

In addition to reaping the benefits of generative AI in automating traditional compliance processes, lending teams are discovering that the same solutions can offer them much more from the same data.

While old-school manual compliance auditing produced nothing more than...well, compliance audits, lenders who invest in generative AI are increasing their ROI by mining that same data for predictive analytics, business intelligence, opportunities to improve training and onboarding processes, and much more.

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3. Borrower experience

The big focus on generative AI in the borrower experience has been on chatbots, both for good and for ill. The CFPB has specifically called out their shortcomings in financial use cases, but new fintech companies have been able to deliver more sophisticated solutions that sidestep some concerns of those first-gen products.

Another easy target where generative AI can deliver major improvements is in repetitive administrative tasks that divert a representative’s attention from where it belongs - the customer.

One example is automating call notes. Asking representatives to keep notes of customer interactions is vital for both customer service and regulatory compliance. But that task means agents are multitasking during calls, distracting them from connecting with the borrower and increasing silent time as they type during the call.

That distracted in-call experience is followed by monotonous after-call work while representatives complete their notes. That duty also hampers productivity, delaying them from helping the next customer.

But generative AI can deliver complete, accurate call notes in seconds, leaving the representative free to improve the borrower’s experience by focusing on their questions and concerns.

And again, there are bigger wins for lending teams here than just the notes themselves. 

Having standardized notes snowballs efficiency, making it easy for the next person in the account to quickly get up to date, and easy for managers to search and analyze across notes to identify opportunities for individual agents and the entire team to improve.

4. Servicing

Following up on the idea of improving the in-call experience for both borrowers and representatives, another place lending teams can get a big ROI on a generative AI investment is in a focus on servicing.

For instance, contact centers can replace outdated call script methods with generative AI solutions trained on consumer finance that understand the context of the conversation. 

These systems follow the path of the interaction, including tone and sentiment, and use machine learning to improve. Rather than following rigid steps, these interactive options guide customer service representatives to the best outcomes to benefit consumers.

With an eye to the CFPB’s attention to consumer complaints, the intelligence in the best real-time representative assistance solutions can even identify and capture complaints, allowing the representative to focus on resolving the borrower’s concerns.

Getting started

These four use cases for generative AI in lending will provide a solid ROI for teams ready to invest.

Forward-thinking teams who are ready to get started right away will benefit from finding the right partner to accelerate the process, rather than starting from scratch.

And the benefits of partnering with fintech go far beyond having out-of-the-box access to solutions other lenders are spending precious time and money DIY-ing. 

The process of making generative AI an indispensable part of your business doesn’t just involve white-labeling ChatGPT, especially in an industry as specific and highly regulated as lending.

So not only will an ideal fintech partner for lenders have usable generative AI, that solution will be built for consumer finance, allowing future-ready lenders to launch without the laborious work of training the system themselves.

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