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Debt collections, in its various forms, tend to be represented by a human, either the creditor themself or sent by a creditor, demanding payment from the debtor. A landlord knocking on the door demanding rent. A tough guy who is probably connected to the mob that shows up in a driveway to repossess a car. Guys who are definitely in the mob chasing down a hapless store owner who is late paying their weekly “protection fees.” 

These are the kinds of representations typically seen in the media, but something that you may not be seeing on the screen anytime soon is an increasingly popular approach to lending, which is automated lending made possible through artificial intelligence and machine learning. 

AI is more invisible and less threatening than mobbed up repo men, which probably explains its lack of screen appeal, but its practical uses in lending have been drawing the attention of many creditors. Read on for a few examples of how AI is making strides in the field of financial collections. 

Get a Better Picture of What Causes Loan Defaults in Potential Lenders

Can I trust you?

A credit score is a go-to resource for creditors to determine whether someone is lend-worthy or not, but figuring out what factors are the most relevant for predicting whether a default is on the way or not has often been difficult for creditors. 

An AI default prediction tool can analyze scores of data for each individual account and render an accurate prediction based on data such as: 

-Annual income of the lender (typically, self-reported during application for loan)

-Number of years employed

-Type of home ownership

-Number of past delinquencies, if any

-Length (typically, in days) of bad ratings, if any

-Tardiness in payments

A prediction tool’s thorough and inclusive use of these and other points helps identify what to look out for when lending to someone. AI can give us empirical evidence for how, say, employment history impacts a lenders’ potential to loan, and, in the case of individual accounts you want to clear before lending, can give very accurate “early warning” signs for whether a potential lender may default or not. 

Persona Modeling for Individual Accounts and Categorization for Customer Bases

Smart Data Collections

Persona modeling is an AI method of creating “profiles” that represent the actual clients/customers that you work with, and is used in a variety of industries. 

In financial collections, persona modeling can help a lender make sense of broader categories of potential borrowers, such as borrowers in a certain geographic location/area, and find out psychological insights into these customers based on data such as public posts (on social media or elsewhere) combined with the kinds of data points mentioned in the previous section. 

This can answer important questions such as whether a lender can be expected to repay a loan without intervention, or will need to be reached out to/reminded of their dues, which brings us to our next section. 

Automated Intervention and Outreach

Always On Call. 

In the olden days of lending, a phone call was used to do the trick, and it was a bit of a gamble whether or not the borrower would pick up (whether they were intentionally avoiding the call is something the creditor was left to wonder). 

With AI, data from a tool like persona modeling can give creditors a good sense of what is the best way to reach out to a borrower and remind them about an upcoming or past-due payment. 

Some people spend more time on a company’s website and ask a chatbot questions, some like to call ahead and ask questions, others prefer email. This information is crucial for determining the best way to reach out to a borrower, which ensures a timely and friendly response. Certain borrowers who are late on payments may be more inclined to avoid outreach methods from creditors that make them feel they are being hounded, such as multiple emails per week combined with a daily call. 

AI can also take note of subtle aspects of borrower-creditor interaction to offer solutions for better communication, by noting tone shifts from the audio of customer calls and word choice in emails to find out what is working and what is not in these interactions, to ensure that contacting borrowers is as effective as possible. 


More Money, Less Problems

Overall, the big thing that AI offers in the field of financial collections is preventing defaults by offering accurate predictions for which potential borrowers are more likely to default, and how to communicate more effectively with existing borrowers to ensure they keep their payments on time.