Today’s consumer is progressively more comfortable using technology in all aspects of their lives.
They research on Google and other search engines, talk to their in-home and in-car devices when creating grocery lists, and scan QR codes at restaurants and events. They see the many benefits that automation brings to them. Time savings, access to multiple options, and the ability to do business from anywhere are just a few of the many human perks of “machine-driven” transacting.
But, service is more than just speed and choice when consumers seek a mortgage or other loan. If you are imagining a metal and plastic futuristic being sitting at a bank desk and dealing with a flesh-and-blood homebuyer, that is probably NOT how automation in lending will evolve (although anything is possible).
That said, here are some of the many ways that AI, machine learning, and robotics will ultimately transform the lending process. Many of these changes have already occurred and are now accessible to all banks, including small institutions and non-traditional lenders.
What Exactly are AI and Robotics?
The dictionary definition of AI (artificial intelligence) is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”
The bank ATM is an excellent example of early-stage AI and robotics. Who would have ever thought 50 years ago that a sophisticated hole in a bank wall could interact with customers, count and dispense currency, and report on the balance — instantly?
Fast forward to the 2020s. AI is being used for various functions by as many as 75 percent of banks today.
Machine learning is the process by which repetition of tasks or data analysis enables computer systems to apply that intelligence to decision-making.
Some applications of AI in financial services today include:
- Identifying and authenticating customers
- Communicating with clients and prospects through chatbots and voice assistants
- Assessing risks
- Making pricing decisions
- Detecting and preventing fraud
- Evaluating its loan portfolio and identifying growth opportunities
- Cross-marketing to existing clients, based on demographic and behavioral data
Why is AI-Informed Lending Better for Institutions and Clients?
Lenders benefit from AI because they work with consistent and accurate data about prospective borrowers and can deliver faster and more personalized answers.
Gathering data from multiple sources also ensures that lenders look at a complete and current picture.
Banks and other lenders can then redeploy professionals to do unique business growth and service work rather than spend days tracking down and sorting paperwork. That can ultimately lead to better internal morale.
So, the myth that machines will ultimately replace humans is not valid. Automation can make work more satisfying, reducing or even eliminating errors and tedious tasks.
At the other end of the transaction, the human doesn’t always know or care about the AI-driven systems behind their loan. They just want to know that the financial institution they’re dealing with delivers the best possible service.
When you can deliver best-in-class service to clients, they will tell their friends. That ultimately builds your brand and reduces your marketing costs.
What’s the Role of the Human?
Although we’ve seen lots of human-like robots in the media and developers are making significant advances in the field (like perfecting facial expressions), borrowers still expect to have some interaction with a flesh-and-blood professional when they’re making big financial decisions.
It no longer needs to be face-to-face. As we’ve all seen during the pandemic, people are more comfortable than ever before with video chats, texting, and other forms of remote communication.
The key is having a point of contact within your organization who can answer complex questions, guide borrowers through the process (if necessary), address any concerns, and (hopefully) personally give them good news upon loan approval.
Because lending is not an exact science, a human may sometimes need to intervene to analyze an AI-driven lending decision and see what factors may have led to a loan decline.
For example, a prospective lender may have a solid long-term relationship with your institution but works as a freelancer now. Based on its pre-programmed algorithm, AI may turn that client down for a loan. But a seasoned loan officer might choose to override the “machine” because they know that the client is a better-than-average risk.
The beauty of machine learning and AI is that it’s constantly evolving. And, as institutions enhance their databases with real-time lending data — at both an individual and institution-wide level, the systems behind loan evaluations become smarter.
Embrace the Bot but Beware the Bot!
We don’t mean that you should run screaming from automation— quite the contrary.
Even if you’re a smaller lender, you can access the same types of AI as large money-center banks. Without incurring your own internal development costs, you can accelerate automation within your organization and utilize best-of-class technology.
Although close to 75 percent of bank executives believe AI will transform their industry, more than 40 percent of institutions have yet to adopt it! Companies like ours have removed many of the barriers to adoption.
What do you have to fear?
Today’s consumer is savvy, and they know when they are talking to a human or an automated entity. As consumers, we all know that asking a complex question via an online chat and getting a repetitive and robotic (literally) response can be irritating and time-consuming. Being sent to search an endless FAQ to answer a highly-personalized query may also turn off high-quality prospective borrowers.
As you automate your business, look for opportunities for greater accuracy, speed, and risk and cost management on your end of the transaction. But also make sure you’re creating systems that make clients feel valued and listened to and responded to and getting answers when they need them.
You often hear the term UX in the digital world, but all that means is that the user (aka a real-life customer with financial needs) is getting the best information and service when they need it.
The basic lending principles — customer service, data gathering, risk management, communication, and loyalty-building — are timeless.
AI should be looked at as a way to deliver all of those faster, more efficiently, and wiser. The intelligence can be artificial, but “smiles and handshakes” are a crucial part of your institution’s brand and should be genuine.
Don’t give up that desk, phone line, and headset to Robolender just yet!
Find out how you can adopt AI while building relationships with Lendsmart.