It’s been more than 10 years since I had the first conversation about automating processes in the debt relief industry and while artificial intelligence (AI) has not made the magical inroads that has always been promised, it’s coming.
If you subtract out the telemarketers from the debt relief process what you are left with is a simple problem and process structure that can largely be addressed using inexpensive technology. A significant number of debt related situations could be resolved using an automated process.
Companies have been quietly working on artificial intelligence solutions for other industries like the legal field and they’ve made significant progress. IBM’s Watson computer system is making small work out of complicated tasks that involve data. It has proven its ability to review data, make good decisions, and act on it.
With some backing and experience in the debt relief industry, any dolt like myself, could easily draw together technology available now to create a category killing solution. Wells Fargo has thought about this since at least 2012.
Over the past year I’ve had four or so conversations with outside investments firms from the technology side of the world. They are interested in the debt relief space. And companies that already specialize in financial transactions like banks and mortgage companies see opportunities in the debt relief industry as well. The regulatory compliance issues don’t faze them.
While debt relief players complain about regulations, some financial verticals already operate in highly regulated markets and that’s easily manageable for them.
You may be saying it will never happen. maybe you think automation can’t replace what you do as a debt relief company its already making significant change in the legal profession.
Consider the experience of Luis Salazar as reported.
In Miami, Luis Salazar, a partner in a five-lawyer firm, began using software from the start-up Ross Intelligence in November in his bankruptcy practice. Ask for the case most similar to the one you have and the Ross program, which taps some of IBM’s Watson artificial intelligence technology, reads through thousands of cases and delivers a ranked list of the most relevant ones, Mr. Salazar said.
Skeptical at first, he tested Ross against himself. After 10 hours of searching online legal databases, he found a case whose facts nearly mirrored the one he was working on. Ross found that case almost instantly.
Mr. Salazar has been particularly impressed by a legal memo service that Ross is developing. Type in a legal question and Ross replies a day later with a few paragraphs summarizing the answer and a two-page explanatory memo.
The results, he said, are indistinguishable from a memo written by a lawyer. “That blew me away,” Mr. Salazar said. “It’s kind of scary. If it gets better, a lot of people could lose their jobs.”
I’m also aware of attorneys now who are working with such artificial intelligence companies to create better solutions for student loan discharge opportunities. And there are already systems out there when it comes to business debt settlement that learn from previous transactions and predict the optimum settlements based on creditor, balance, time, and current status.
So let’s look at the individual debt relief niches to see where the AI opportunities lie.
The Debt Management Plan (DMP) portion of the credit counseling world is the perfect example of a process already well automated and seasoned. With a bit more front end work you could cut the human counselor entirely out of the process. The counseling part of the debt management process is already structured in the bankruptcy counseling offered by counseling agencies. The entrance of a budget by the consumer can be completed online and the verification of income and comparing it to credit report entries is an easy technology solution today. Automated processes already are in use for counseling agencies to submit and receive accepted DMP proposals and make payments electronically. Most of these components have been in place for a decade.
In the future there will actually no longer be a need for local credit counseling offices. Even the National Foundation for Consumer Credit could deliver nationwide DMPs using AI technology, automated chat bots, and electronically managed DMPs. This approach would trim the cost per client and eliminate the need to pay for local brick and mortar offices or costly employees. Creditors who fund credit counseling will love this solution.
The debt settlement industry has tried and failed so far with mass automated solutions to automate the process. But it’s coming. Just look at U.S. Patent 9,665,859 by Apollo Enterprise Solutions that was recently granted. This patent covers:
“A method for the online modification, submission and approval processing of a future payment request to afford a user the ability to renegotiate established loan agreement debt terms in which network communications are established between a user, such as a debtor, and a computing device, such as a server or server arrangement, is presented. The method comprises receiving information, at the computing device, regarding the loan agreement debt terms, presenting received information to a debtor, providing an interactive environment enabling a debtor to modify existing terms, submitting modified terms, processing data from the available information using a rules based engine, and processing a future payment request based on at least one decision made by the rules based engine. While online, the user/debtor may engage in revising a rejected future payment request in an attempt to reach a satisfactory renegotiation of debt terms.”
Even the debt collection industry is pursuing this niche. Take that recent patent by Collections Marketing Center as an example. Their U.S. Patent 9,659,326 is for a, “method for gathering information pertinent to a debt for purposes of compiling a transaction settlement offer set of a plurality of offers for settling and resolving the debt, the method performed using a computing device and comprising: collecting credit information including information about a user’s current financial condition using a server for use in compiling the transaction settlement offer set according to a set of predetermined offer set rules, the transaction settlement offer set comprising a plurality of individually selectable monetary offers each comprising different decisioned monetary settlement terms specifically determined for the user based on the set of predetermined offer set rules and collected credit information including available information about the user’s current financial condition and further determined to facilitate settlement of the debt by modifying existing terms of the debt without providing a new debt instrument to the user using terms of one individually selectable monetary offer selected by the user…”
The debt validation niche could be combined with the Fair Debt Collection Practices Act (FDCPA) segment. Both segments are a request or watch niche where timelines and triggers can generate an alert or automated response. In the case of FDCPA reported claims it can easily trigger a quick automated case by an attorney who is licensed to file such a case. A client smartphone app tied to an AI solution could manage call interactions and create an automated collection tracking system to bolster an FDCPA claim.
Patents already exist for automated handling of credit disputes. Look at U.S. Patent 9,406,085 which is for, “Systems and methods are provided for credit dispute processing, resolution, and reporting. Credit dispute resolution requests may be received, processed, and sent to a credit bureau for submission to creditors. Status of credit dispute resolutions may be reported to consumers. If a creditor’s response time is longer than its average response time or if a creditor does not respond to a credit dispute resolution request within a regulatory response period, alerts and reports may be sent to consumers to provide consumers with further options.”
But What About Current Efforts?
There have been current efforts by companies like Morgan Drexen that claimed to offer a back office technology solution but it was crudely designed and failed the regulatory test spectacularly.
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Rather than just a technology solution, Morgan Drexen attempted to have their cake and eat it too. Rather than create a technology solution alone, like Ross Intelligence is doing in the legal space, Morgan Drexen tried to be clever and stick attorneys on as a necessary evil while Morgan Drexen ran the show.
If Morgan Drexen had just been the technology platform and had not run the ads, didn’t do the sales, and didn’t treat the attorneys like cheap signers then they would still be around today.
Rather than giant leaps forward, the debt relief space has taken small shuffle steps but it’s is coming as AI prices and solutions become less expensive. There is no longer a doubt if it will happen but when it will happen.
But There is Opportunity
The future opportunity is going to be in the need for talented debt professionals who are knowledgeable about the field in general and can assist with custom solutions for non-standard situations.
The field will need experienced professional debt experts who can impart judgment based on a learned and educated set of experiences and training to provide a solution that takes into account the current situation of the debtor, their future needs and goals, and their emotional decision making at the present moment. Think about the future professional debt expert as a debt doctor giving a diagnosis and treatment plan and not a used car salesperson.
Many consumers struggling with debt will instead love an automated AI system where they can resolve their debts in silence and make payments without human intervention. Even if a proposed repayment is not the best payment available, the ability to resolve their financial conflict without human intervention will have some value and make the process easier.
And for companies who want to try and compete mass market with future AI debt relief solutions, good luck. The AI solutions will drive prices for services down to a level where human stocked companies will not be able to compete through price. An AI debt settlement system operating a 5% of savings is doable, can be automated, and is massively scaleable.
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