The State of AI in the Commercial Collections Industry
Everyone knows that for the last year, the hot buzzword has been “AI” and its impact on the world, business, and how we live every day. There are a lot of articles, blogs, and white papers out there about how the consumer collections industry is using it. However, if you Google “how are commercial collections firms using AI?”....results are limited. As an industry veteran of 25+ years in Accounts Receivable Management I thought it was time to weigh in.
The average debt collection firm in the US uses an average of 6.7 different tools. For many businesses, one of those tools is AI. The main way they are using it includes (source: FINTECH WEEKLY):
Quality and compliance monitoring (47%)
Chat or written communication (47%)
Scoring and treatment strategies (45%)
Voice communication (44%)
Negotiation support (42%)
Using a tool like AI to augment internal processes can present both benefits and challenges. Especially when it comes to commercial collections, what works in consumer collections may not work the same. Let’s dive a little deeper to understand.
When it comes to the day-to-day running of your business, AI can absolutely improve efficiency. It will reduce the volume of manual tasks, sharpen your existing workflows, and help your team operate with more precision. For example, when it comes to collection planning, AI can spot potential defaulters, sort your debts, and handle customer segmentation. It can also optimize your collection processes, including tracking response rates, recoveries, and losses as they happen.
For consumer collections, this is a powerful resource because the balances are straightforward, disputes are more identifiably addressed, and the work is high volume and rule-based. This is why AI performs so well, because the path to payment is predictable. For commercial collections, it is not. Managing your A/R requires negotiation, escalation, documentation, and is relationship-driven. It cannot be solely solved via AI alone.
I recently read a study by Yale Professor James Choi. He ran a test where he assigned small debts to AI callers and large delinquent debts to humans, and compared the performance. He found that “The data show that AI callers are less able than humans to extract verbal promises to repay from borrowers, and promises that are made to AI are broken more frequently” (Source: Yale Insights). The message that I took from this is one that I also experience every day at NCS Companies: “Humans are more prone to trust real human interaction”.
This becomes more applicable when you consider the lifecycle of an account. When you are attempting to collect on an account that is 30-60-90 days old, AI can be very helpful. For accounts that are 150+ days old, it requires peer-to-peer engagement. You are required to understand the terms and status of the account, ask hard questions, and put together a specialized subjective strategy that AI is not capable of.
A true collection partner will represent its clients' brand with tact and precision. To do this, they need to take the time to understand a client's specific terms and conditions and then enforce them with professional peer-to-peer interaction. Through my 25+ year career in the industry, I have seen this approach deliver reliable, precise, and effective results with the most complex aged accounts.