Fintech
Is fintech the key to improving debt collection?
The phone calls and letters are still going strong debt collectionbut the spread via digital channels such as text messages and emails is gradually increasing.
The same goes for using artificial intelligence and machine learning to reach consumers in a more attractive way.
Several fintechs operating as digital-first or tech-enabled debt collection agencies, including TrueAccordJanuary and InDebted, use data-driven models to optimize their outreach to defaulting borrowers on debt based on how they interact with text messages and emails, personalizing the content and timing of their communications and targeting consumers self-service portals. Proponents of these methods say it is more convenient than talking to a human on the phone, and point out that digital messages or chatbot responses can be programmed to achieve the right tone of encouragement.
Anonymity can also be a blessing.
“There are many misconceptions about people who have debt, especially outside national borders medical debt” said Ariana Michele Moore, a consultant at Datos Insights. “Most consumers want to pay their bills.”
The question of how to effectively collect debt is especially relevant as consumer debt levels increase. A 2024 report by Datos Insights that surveyed more than 200 third-party debt collection professionals found that letters and telephones are by far the most popular communication channels used to contact consumers, at 98% and 93% of those interviewed. But 69% use email and 40% send text messages. Nearly a third of respondents are considering adding text as a method in the next two years. The banks were too rely on digital dissemination in the last few years.
“For many years, debt collection has been very archaic,” said Joann Needleman, who leads the consumer financial services regulatory and compliance group at law firm Clark Hill. But Consumer Financial Protection Bureau Regulation F, which released in 2020, enabled communications via voicemail, email, and text messages for the first time. The pandemic has also pushed the industry in a more digital direction, as collection agency call centers have emptied for security reasons, but lenders have raised data security concerns about allowing agents to make debt collection calls from home.
There is also data to suggest that consumers would welcome this change. A Datos Insights survey of 2,005 respondents in 2023 found that 77% of consumers who pay bills handled by debt collection companies are at least somewhat interested in the “contact us” option via SMS if they have a question regarding the bill , while 38% are “very interested.
“When Regulation F came out, consumer advocates were very concerned that consumers would be bombarded with emails and texts,” said Needleman, who led the National Creditors Bar Association’s response to the Consumer’s Advance Notice of Proposal Financial Protection Bureau. regulation F regulation in 2013. “That hasn’t happened. The industry is finally meeting consumers where they are and using technology to do so.”
Integration of AI and ML in debt collection
Companies like TrueAccord, January, and InDebted typically receive data files from their customers, which can include banks, credit unions, credit card issuers, fintech lenders, buy now/pay later suppliersand debt buyers. Their models or engines then analyze some combination of consumer engagement data, such as when they opened an email; characteristics of the debt, such as whether the debt is a buy now/pay later loan for a small amount or a personal loan for a large amount; or anonymized historical data. This helps determine which channels each consumer prefers, such as SMS, email, voicemail or telephone; when they are most likely to respond; what a message should say depending on the consumer’s reimbursement level; or what a refund offer should entail. The platforms will direct users to a self-service portal where they can pay off their debts or set up a payment plan.
TrueAccord is widely credited with paving the way for other digital debt collection agencies when it started in 2013.
“They have done a lot of favors in making the industry comfortable with digital self-service collections,” Tyler Gillies, vice president of operations and business development, said in January.
TrueAccord’s engine, called HeartBeat, uses machine learning to determine the correct channel, time and message content for each consumer. Contains a compliance check filter to ensure outreach complies with the Fair Debt Collection Practices Act, Regulation F, and state or local laws.
“If you make contact at 10 a.m., 1 p.m., or 4:35 p.m., that makes a big difference in terms of engagement and response,” said Steve Carlson, president of TrueML, TrueAccord’s parent company. “We will work to optimize it.”
TrueAccord paid $500,000 earlier this year to the state of Colorado as part of a settlement with the attorney general’s office after investigators found that between 2017 and 2022, TrueAccord collected or attempted to collect approximately 29,000 consumers defaulted on loans issued by tribal lending entities. These loans often carried interest rates above the 500% annual percentage rate, which consumers are not obligated to pay under Colorado’s rate cap of 12% for unlicensed loans. TrueAccord told consumers they owed the entire loan balance.
In response, TrueAccord said it recently entered into discontinuity insurance with the state of Colorado regarding lenders affiliated with federally recognized Native American tribes following a 2019 standard collection agency audit.
“TrueAccord denies that any of our practices have violated Colorado statutes,” the company said in a statement. “As a result of the settlement, Colorado is compensating consumers who made payments to these accounts. None of the agreed-upon terms will impact TrueAccord’s provision of collection services to our customers and consumers.”
January, whose name is meant to evoke a new beginning or resolution, maps its clients’ borrowers into four quadrants depending on their ability, or inability, and willingness, or unwillingness, to pay. “The most important quadrant we look for is willingness and ability to pay,” Gillies said. “If we can truly optimize for those who are willing and able to pay and approach them with compassion, we are already off to a better start.”
The language used in the texts and emails tries to convey that “we want to find an agreement that is comfortable for you and we are truly here to help you,” Gillies said.
InDebted, which is based in Australia, expanded to the United States in 2021. It works similarly to the others, with proprietary machine learning models that use historical and real-time engagement data. Each communication includes a link to the self-service portal, Resolve, where users can manage their accounts.
“Digital engagement sends out a lot of signals,” said Josh Foreman, founder and CEO of InDebted. “Have you opened your email? Are you on our site? What offers are you looking at? Do you want to settle the bill by paying in full or set up a deal?” For example, if a consumer logs in far from where he lives, it could be a clue that travel is the reason he hasn’t repaid his debt.
Equabli is a self-styled end-to-end collection and recovery center for customers, which include financial institutions, fintech lenders and debt buyers. “We don’t interact” with customers, said Cody Owens, Equabli’s CEO who co-founded the company in 2020. “We’re the technology and analytics provider.” But this also shows how machine learning is entering the debt collection industry.
Equabli will use its APIs to acquire information and documentation from its customers about delinquent customers and accounts that they will need to collect debts and manage the collection process. Equabli’s system uses machine learning and predictive analytics to classify customers based on their propensity or ability to repay and will automatically monitor compliance with debt collection regulations, for example by reporting if a third-party agency has exceeded the limit maximum of seven calls in seven days. The system also allows its clients to interact with customers through digital means, such as personalized messages and emails, and provide them with options for self-service.
While only 11% of debt collection professionals surveyed by Datos use third-party solutions that incorporate artificial intelligence and machine learning, 40% are in the process of implementing such solutions or considering them. The top three uses for those who have or are implementing it are to predict payment outcomes, segment and profile customers for various workflows, and enhance the self-service platform.
Make sure the message gets through
These companies must prove up front that they are legitimate and do not send spam.
“This is something we work against,” Carlson said. “A lot of people know that I asked for a loan from so-and-so. It’s more, do I really want to work with these people? Or do I want to run away from them because I know I’ll get harassed?”
Companies typically initiate communication via email. Regulation F requires that the initial written notice contain the balance owed, the creditor to whom the debt is owed, the consumer’s name and address, and clear instructions to the consumer on how to dispute the debt.
Foreman said that when emails are opened, unopened or marked as spam, all of that information is fed into InDebted’s model to indicate whether or not this is a good channel for a particular consumer.
“When we send a message or make a phone call, we will be sure to send content that reflects that we understand they have marked that email as spam, we can understand why that might be the case, but this isn’t, and here’s some more information about their account, to help validate authenticity,” he said.
Gillies notes that all communications from January contain information about his relationship with the account holder and the debt in question. The company has also invested in its consumer-facing branding to ensure January’s online image is credible and up-to-date.
“The moment a consumer opts out of receiving text communications, that benefit is basically dead,” Moore said. “With a text message you only have one chance to say who you are.”