AI is not a threat to debt collections team; it’s a helping hand

In certain circles, AI has something of an image problem. Even though it’s a major step forward in technology, making our lives better in so many ways, there are many out there who still believe that AI is going to steal their jobs. Not only that, but many more simply don’t trust the idea of a machine “doing a person’s job”. In fact, 43% of executives surveyed by Deloitte admitted that they have “major concerns” about the potential ‘risks’ of AI.

But AI hasn’t really been replacing people. It’s just been making their jobs easier and more efficient. This is particularly true for debt collections teams. Before the advent of AI, they would spend hours a day on the kind of repetitive tasks that advanced AI can carry out in mere seconds.

We have already explored why AI is the obvious answer to better debt collections. Here, we’ll explore a few common concerns from the perspective of collections teams. 

Is AI good news for debt collections teams?

Absolutely. Delinquencies are rising on everything from student debt to credit card debt and everything in between. So, collectives need to to take action and make some serious changes to their collections practices. 

Why are collections teams so sceptical of AI?

Debt collections has always relied heavily on human interaction. However, most experts agree more generally that the shift in dynamics brought on by AI is going to be more about job displacement than job replacement. The overall, long-term effect? Broadly positive, with millions of jobs expected to be created.

What debt collections problems is AI solving?

Successful collections currently only make up a paltry 20% of total cases. Frankly, collectors can send all of the emails and make all of the calls they like, need a way to focus their efforts. Think of AI like when football teams watch replays of their opponents’ games. If they know the opposition's keeper favours diving in one direction to save a penalty, they might shoot in the other direction. If they know that the other team is prone to scoring on the counter-attack, they need to prevent that counter-attack from materialising.

AI can gather and process customer data that reflects their behaviours and responses, then use that to automatically shift a strategy to drive better results. This makes AI ideal for detecting risks as early as the credit scoring stage of a loan application. It can even draw in data from other sources to help decide whether or not a loan applicant is likely to fall into delinquency. 

This savvy tech can also be used to monitor account activity by using historical data analysis. This can be by suggesting the best way to contact customers (through SMS, WhatsApp or social media, for example), or even automating exactly when and how often to contact a specific debtor. Whatever the application, actions are simplified, automated and personalised to reflect the needs and behaviours of the consumer.

According to Dr. Akli Adjaoute, CEO of Mastercard company Brighterion, AI can be equally as helpful in raising red flags or green lights when it comes to onboarding new customers. It can also be used to prevent delinquency before it begins. He explains: “I believe the prevention of delinquency is more important than efforts to eke out returns on processes that are still steeped in telephone calls and letters.” It can do this by informing collections teams who is most likely to pay, whether nonpayment behaviour is an aberration, and when the best times and methods of contact might be. Context is key, of course, and it’s up to the teams to supply that context.

How will this make life easier for debt collections teams?

Debt collections is a very hands-on process. It’s also an incredibly data-intensive process, riddled with grunt work. AI will free up teams by taking care of much of this work for them. This means they have more time to work on customer-facing roles and improve overall customer service. 

Chatbots are perhaps the one aspect of AI ‘interference’ that most worries collections teams. But this tech is likely to create ‘backup’ agents to help their human counterparts do their jobs more effectively. They could also (rather ironically) help to humanise debt collection by steering well clear of intimidation tactics and learning the psychology of their customers. This is especially valid in a world where one in four consumers contacted by collectors feels threatened.

Chatbots are perhaps the one aspect of AI ‘interference’ that most worries collections teams

These ‘virtual agents’ are theoretically able to interact with customers and autonomously negotiate repayment terms on a 24/7 basis. However, when discussing something as serious as debt, most consumers would still rather deal with a human agent at some point of the process. That’s not to say chatbots that might be able to avoid the uncanny valley are not in development, but for now, they will be used primarily to filter out the conversations and situations that wouldn’t and shouldn’t require a human agent’s assistance.

A perfect example is the AI chatbot launched by UK credit management specialists Intrum last year. Designed by the Norwegian Fintech firm Boost AI, this ‘virtual collector’ could answer over 730 common questions posed by customers and was able to provide answers 90% of the time. The other 10%, it was able to direct customers to human customer support.

A solution; not a threat

AI isn’t a threat; it’s a solution. Ultimately, however, it is just a tool and as with all tools, if it is not properly utilised then it is little more than a nifty trick. For collections teams, the real benefits of AI, moving forward, are going to reveal themselves once they are able to use it as just one crucial part of a solid, customer-focused collections strategy.

In the next five years or so, AI looks set to completely change the face of banking and debt collections, with Microsoft and IDC predicting it will be a major driver of economic growth, increased productivity, cost reduction and customer advocacy. They also predict that 40% of digital transformation initiatives will utilise AI in some way, but we predict that number might actually be far higher.

For debt collections teams, the writing is already on the wall – an AI-powered collections solution that can predict and empower customers to pay their debts will always work more effectively than using outdated systems which are prone to human error. As long as the approach is always customer-focused, AI will always be an asset.

 

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