Don't look now, but AI is already making its impact in the lending space. Look closely at the prevailing trends involving AI and the lending industry, and you'll get a better idea of what role AI will play in the lending operations of the future. These industry insiders have witnessed and studied those trends. Here's what they have to say about their relative significance:
1. Jeff Silberman, Counsel in Reed Smith’s Financial Industry Group
“Supervised machine learning to digitize documents in the loan underwriting process is a trend I’ve seen grow considerably this year. Document digitization using solely AI have seen process improvements, but my understanding is that the historical accuracy for AI by itself for those processes is around 85%. The limits of AI-based computer vision mean that even the most advanced solutions will still encounter data points that are challenging for machines to recognize and read purely by themselves.
However, it seems that supervised machine learning solves this problem in two core ways. First, there are companies that now embed hyper-efficient human review into the process to supplement when the machine cannot recognize or read the data on its own. It’s my understanding that these platforms can now guarantee 99+% data accuracy for all analyzed documents with supervised machine learning models. Second, the validated data is then fed back into the system in a machine learning feedback loop, allowing the AI to learn the data points it missed. With each analysis, the machine improves its performance, relying less on human validation and increasing speed as time goes on. If successful, the move to supervised machine learning to capture the increased efficiency would be a trend I’d expect to continue.”
2. Douglas Merrill, CEO and founder of ZestFinance
“Washington’s interest in exploring ways to regulate AI/ML in financial services. Recently, the Office of the Comptroller of the Currency explicitly called out the use of AI and machine learning in credit in its semi-annual report on the key issues facing the national banking system. This is the first time a federal banking regulator has made a formal statement about the responsible use of AI/ML in lending, and highlights the growing use of AI/ML in banks and lenders of all sizes. We’re big fans of regulation that ensures banks and lenders are using AI and ML safely and responsibly to widen access to credit for people who deserve it while ensuring the health of the credit system.”
3. Dr. Marlene Wolfgruber, Director of Product Marketing at ABBYY
“The number one trend is the increased demand of mobile phones for onboarding. Practically everyone has a smartphone in their pocket, and by 2025 millennials will make up 75% of the workforce and spending power. They expect to access everything in a mobile-friendly
way – which includes applying for loans.
Bank industry studies show 40 percent of consumers abandon applications after initiating the process, with a major pain point being the need to download a native app for submitting supporting documents like proof of address or pay stubs. Lenders can use mobile web-based data capture to avoid that pain point and provide a consistent digital onboarding process.
For financial institutions that already have wide app adoption, providing more built-in services for document and data exchange can speed up onboarding by allowing customers to instantly take photos of necessary documents for opening accounts or applying for loan applications, while auto-filling details such as name, address, date of birth, etc.”
4. Steve Comer, Director of Financial Services at Hyland
“The trends shaping AI are the same trends that are shaping banking in general. The industry is being driven by customer experience and cost reduction. Those who are rising to the forefront are doing so through embracing technological advancements that are happening (seemingly) daily. Technologies that allow lenders to offer more and/or faster channels to business, improve the customer experience and simultaneously drive down costs are on everyone's must-have list. Two of the modern technologies at the top of that list are AI and Machine Learning applications.”
5. R.J. Talyor, founder and CEO of Pattern89
“Those of us working in AI find ourselves focusing on ethics lately. We often have to reflect and ask ourselves if the decisions we're making to inform our AI are the right decisions to make.
Developing ethical AI isn't just a trend or hot topic though. It's a critical part of this technology's evolution. Engineers, scientists, and thought leaders must always be asking… What do our decisions mean for our customers and our company? What will happen if we misstep? Could there legal or ethical issues with what we're creating? And what does our company stand for in an AI-driven future?”
6. Joshua Jones, CEO of StrategyWise
“Natural Language Processing (NLP) is allowing banks to scan thousands of pages of documents in minutes compared to weeks. This has tremendous implications for audits, reviews, and opportunity identification.”
7. Anis Uzzaman, CEO of Pegasus Tech Ventures
“We would say that the #1 game-changing trend we are aware of this year is the ability to use data to identify viral trends at or near inception. Specifically, investment firms of technology companies have an advantage with deal flow in that they are able to leverage data from their core businesses to identify new consumer and business trends, and startup companies addressing those trends.
Using AI to identify new seed-stage companies and validate existing is probably the first main instance of the technology that is being looked at for broad adoption in processes across the investment industry.”
8. Dan Raviv, CTO and co-founder of Lendbuzz
“In recent years, algorithms shifted from traditional machine learning to big data analysis based on deep neural networks and this practice has reached the lending industry as well. The ability to move from old methods into the new ones is important, and we will capture more data, making lending platforms stronger.”
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