Artificial Intelligence Means Better Customer Retention for Lenders

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Cracking open multiple data sources can also help lenders spot would-be borrowers worth lending to, even if they have scant credit histories.

When you think about it, the key to customer retention is the “Golden Rule,” a maxim found in cultures around the world stretching clean back to ancient Sumer. In modern English, the saying goes “Treat others as you would have them to treat you” — which seems harder to do in today’s fast-paced urbanized world than it was when most people were farmers and everyone knew their neighbors.

But artificial intelligence or AI is changing that and revolutionizing how lenders and borrowers interact. Likening repeat customers to “old friends who improve with time,” Boris Teplitskiy, risk chief at loan-servicing software maker TurnKey Lender, says the best way to keep them coming back is to demonstrate appreciation and precise insight by “making the right offers to the right customers at the right moment using the right communication channels.” 

Customer Retention is a Function of Big Data, Properly Analyzed

That’s a simple-sounding formulation for bringing the Golden Rule to customer service. But Teplitskiy warns providing such value across large customer bases calls for analyzing vast datasets, and deploying relevant outputs using AI, either according to pre-set “rules” or by letting the AI identify patterns across a host of variables.

Meanwhile, the world isn’t waiting for lenders to catch up. Technology analysts at Gartner say that by 2022, 20% of global customer service will be handled by AI-powered “conversational agents,” better known as chatbots. For one AI trade publication, this prediction “should send shocks up the spines of product managers who are not already actively engaged in either implementing or considering rolling out a conversational AI strategy within the next six months.”

Building Blocks for a Successful AI-Powered Retention Program 

Practically speaking, retaining clients through AI presupposes having a number of elements in place, including:

  • Improved customer service
  • Automated customer interactions
  • Personalized pricing plans
  • A system for tracking customer satisfaction

But these things can’t be optimized without a deep and digitized understanding of customers, drawn from a range of big-data sources beyond credit scores. Among them are: 

  • Transactional data
  • Survey results
  • Phone and chat transcripts
  • Loyalty programs
  • Social media
  • Demographics

Cracking open multiple data sources can also help lenders spot would-be borrowers worth lending to, even if they have scant credit histories. As it happens, entire regional markets fall broadly into this category, including China and sub-Saharan Africa.

Let’s drill down on some ways AI contributes to better customer service and as a result better good-customer retention, for lenders.

Consumer Behavior as a Window on Creditworthiness

As we just mentioned, a customer’s purchasing history is a vital input for AI. Knowing how much a customer has spent, how often, on what, whether credit was extended, and how promptly loans were paid off can inform loan structures, incentives, customer-service recommendations as well as e-prompts and other intra-contract touchpoints. Customers respond favorably to services and rewards that speak to their needs and habits — and repay this satisfaction with loyalty to brands that address their (sometimes unspoken) specifications and preferences.

Giving Customers (Relevant) Things to Play With

The personalization potential of AI goes even deeper. A lending site or app can help companies connect with customers on an ongoing basis — by, for example, letting them run various repayment scenarios showing how they could save on interest, or offering personally relevant tips on credit management and budgeting. By tailoring such outreach to customers whose browsing histories have demonstrated interest in similar information, AI can help keep customers informed, engaged, and more receptive to new transactions.

Turning Social-Media “Noise” into a Precision Tool for Lenders 

Because AI can take data derived from social media and provide deep insight on what customers worry and complain about in their interactions with companies, lenders can take action to fix issues before trouble starts. Beyond troubleshooting, AI can match customers’ social-media habits to matters of specific interest to lenders. It may be found, for instance, that people who peruse Twitter before 8 am and, let’s say, rarely do so after supper, are more likely than the average borrower to pay their loans off before the contract is up. Or that people who post photographs of cats on Instagram are more prone to making late payments than dog-pic posters. AI-fueled social-media analysis can also help direct marketing campaigns, in terms both of content and placement on platforms — Facebook, say, or Tumblr — your customers use most.

Making Chatbots “Smart” Enough to Handle Entire Interactions

AI can also help lenders interact with customers through the website- or app-based “intelligent” chatbots. Increasingly, these interfaces, backed by a host of big-data insights informing what-if scenarios, can solve issues for customers without human intervention — at least on the lender side of such conversations. Chatbots can also tell customer-service personnel when their algorithms don’t fit the situation, and it’s time to take over. 

AI is the Key to Customer Retention

How would you like to be treated by the company you want to borrow money from? 

You would like to be treated fairly, right? — but also with some indication the treatment is informed by an understanding of you, your needs and your preferences. And you’d probably like this treatment to extend through the life of the transaction, from application to settlement. 

This kind of treatment is now possible, and at scale, because of AI’s ability to sort through, prioritize and prompt responses from vast data inputs, drawing on sources as diverse as loan-application forms and minutia culled from the farthest reaches of the “internet of everything.” 

The effect of getting at such information and making sense of it is to create an environment where treating customers as you would like to be treated is an emerging reality — and it’s one that will only increase in its responsiveness and ability to foster customer retention as AI continues to evolve.

Interested in speaking to an expert in artificial intelligence who can help you implement the above? Book a time here.

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