In the economy where one in three Americans have a debt in collection, it is essential to collect debt to avoid passing the losses on to paying customers. While debt collection is essential for financial responsibility, the trick is to collect debt without alienating the customer, reduce complaints and avoid lawsuits. I say reduce complaints because they are inherent.
Debt collection is an area for constant complaints and has been, long before the CFPB permitted the posting of every complaint, legitimate or not. (The CFPB handled over 1.08 million consumer complaints by January 1, 2017.) Whenever I say I am editor for a magazine about debt collection technology and receive a negative response, I realize I am talking with one of the 35% of people who got behind on a debt and received a communication from a collection expert. Right away, we are on the defensive. We want to protect our honor, to say we are financially responsible. At the same time, who wants to pay a debt not owed? I know I don’t, but I have. I know people who pay the IRS just to stop fighting them and get back to work.
A scrutiny of debt collection complaints explains this notso complicated predicament. The complaints fall into four major categories: debt already paid, debt not owed, debt amount not verified and the wrong amount collected as debt. In many cases the financial professionals in banking created the problem and the financial professional in receivables catches the complaint. Data coordination is needed to enable debt collected by agencies to have a first-hand account of the facts. Companies contracting agencies need seamless technology to ensure accurate facts are passed on.
Technology becomes the hero in debt collection again. Data coordination is necessary between big data analytics, predictive analytics, process automation, mobile technology and social media.
Big data analytics segregates data to answer key questions about a consumer: What is her intent to pay? What is her ability to pay? What will change her ability to pay and over what period? What is the likelihood of the change? Demographic data combined with the time of the day a consumer will respond to a call increase rightparty- contacts and talk-offs for debt collection agencies, the group we refer to as accounts receivable financial professionals (ARFP).
Big data opens up possibilities like speech analytics on every debt collection call. Advanced language-recognition programs track keywords during phone conversations and identify emotions of debtors and collection agents. If emotions rise and cursing begins, prompts steer conversations back on track. Supervisors see color-coded boxes on call-center computer monitors. A box turns red and expands when a call contains expletives. If there are long silences a supervisor can take over the call or whisper in the agent’s side of the call.
Small green boxes represent routine conversations when agents are reciting mandatory “mini-Miranda” statements. Ideally the program guides the agent to express appropriate empathy and then provides phrases to produce payments. The end result is a score to rank ARFPs (top collectors).
Predictive analytics uses data mining, machine learning, artificial intelligence and statistical modeling to predict future events to gain reported increases of 50% in three months. Process Automation in debt collection replaces manual tasks with an automated process or a self-service portal. Efficiencies are gained by automating skip tracing, payment follow up and lining up the right phone numbers at the right time of day for a call.
Decision automation is gaining strides by teaching a machine to think, plan and act like an agent. While data science builds models based on past history of debt collection automated agents learn how to interact, follow up and close pending collections with debtors. Using email, SMS and chat the channels provide private, one-on-one discretion. The ubiquitous mobile phone permits debt collectors to reach debtors wherever they are while technology determines which calls are permission based and not on the Do Not Dial list. Mobile phone payment apps surpassed other forms of payment this past Black Friday.
Social media is used to trace and prioritize customers for collection through their Facebook and Twitter accounts. While a debt collector must have considerable empathy and persuasive skills, technology can make the process faster and more accurate. Systems that cut down human intervention in the process these are merely tools at the financial professional’s disposal. The “art” of debt collection comes into play when these tools are utilized in concert to achieve the ultimate result, account paid.
A compliant call resulting in account paid or a payment plan puts the consumer on the road to restore financial responsibility and credit worthiness needed to make the next significant purchase of goods or services.