3 Ways AI Can Change Debt Collection

23 Oct 2017
Ai

Just a few weeks ago, Google launched its series of ‘A.I. first’ hardware - from earphones that carry out real-time translation to a smart camera that capture images based on algorithms, Google is going full throttle on its mission to launch and lead a future world where artificial intelligence manages our day to day lives.

Artificial intelligence has been the buzzword for a few years now, as it is the driving force of the technological changes that we have been experiencing in a digitally motivated world. In various industries around the world, game changers have caught on that the key to disrupt conventions and create new orders is through the application of artificial intelligence in business processes.

In the last year, we have seen many exciting industry breakthroughs in the forms of bots, robots and automated systems. In San Francisco, a barista robot has been serving quality artisanal coffee at low costs to happy customers. Who would have thought that artificial intelligence would be able to wriggle its way into a food service industry that prioritizes interpersonal connections and efficiencies?

In businesses that have been traditionally human-centric, some professions are increasingly forced to reconsider the structure and validity of their jobs. For instance, the legal industry has seen a rise of ‘robo-lawyers’ that carry out tasks such as legal research, predict lawsuit outcomes, and even chatbot lawyers that can help challenge parking tickets and demand compensations. The healthcare industry is also seeing a fresh crop of startups that aim to use technology to aid, prepare, or even replace medical workers.

What do all these new innovations and changes mean for the debt collection industry? Conventionally, debt collectors rely heavily on manpower to call debtors and carry out skip tracing. Despite understanding the importance of artificial intelligence, most of the industry players have stuck to tried and tested methods to achieve debt recovery. In the rare cases of attempts to incorporate digital means, debt collectors have tried to reach debtors through social media channels and gained a bad reputation for it instead. Suffice to say, the debt collection industry is due for some reform, and we believe that it is possible to experience the exciting changes our peers in the health, legal and finance industries are undergoing. InDebted believes in the same goals as those that have forged ahead, and that is: ‘to leverage new technology to fix an old industry.’

How then, should artificial intelligence be incorporated in debt collection processes? Broadly speaking, the business application of artificial intelligence can be streamlined into three directions.

Assisted Intelligence

Assisted Intelligence focuses on improving human processes with clearly defined rules. Basically, the system is trained to carry out tasks that humans can achieve in a faster and more efficient manner. This is perhaps the type of A.I. that we are most used to, as we employ it to carry out tasks such as sorting emails and organizing schedules.

Yet, its potential has not been maximized in debt collection processes. For instance, assisted intelligence could be employed to automate the customization and delivery of various communications to reach debtors in a shorter time frame and in a faster manner. Schedulers could be created to ensure that these communications adhere to the compliances set in a 90-day window. All these developments will be able to optimize the time and effort spent on debt recovery processes.

Augmented Intelligence

Augmented Intelligence, on the other hand, focuses on carrying out tasks that are impossible for humans. One often cited example is Netflix’s content suggestion feature, which provides customers video suggestions based on their profiles and demographics. Another relevant example that could be a good reference for debt collection services is DialogTech, a startup that uses machine-learning algorithms to analyze phone calls and caller behaviors to predict outcomes of customer calls. While many worry that technology might eradicate the human factor out of our daily lives, we should instead use technology to improve human interactions and customer services. In this case, if debt collection agents could obtain real time analysis on how best to maneuver a conversation with a debtor, it could greatly reduce possible friction between reluctant debtors and improve productivity.

Another way big data and analytics could come into play is to have algorithms that scan debtor profiles for inconsistencies and to rank debtors by chance of returns. Predictive models can be developed to optimize the decision-making process of debt collection agents. Debt collection agents can then work their way from debtors that are more willing to those that might be reluctant, thus optimizing the effort and cost of a day’s work. Not only that, insights on how debtors may respond to different approaches can be generated to ensure a smoother debt recovery process. In this sense, augmented intelligence is the area where most disruptions of conventions can occur, with the right amount of creativity and expertise, debt collection processes can be innovated.

Autonomous Intelligence

Autonomous Intelligence is a direction that is still largely under development, but it aims to have machines that act on their own without human interferences. Some of the examples that we can look forward to seeing are self-driving cars and automatic translators. Nonetheless, we do not see autonomous intelligence as a possible replacement for debt collection. This is because debt collection processes often involve negotiation and sometimes, interactions with debtors who are facing difficulties require a certain degree of empathy and sensitivity that artificial intelligence cannot yet provide.

How autonomous intelligence may be incorporated is to have artificial intelligence carry out and follow through a debt collections life cycle, with an added feedback mechanism that can always include input from specialized collections agents. In short, effective products of artificial intelligence require a human feedback loop to ensure that it is always updated and effective, and this should be taken into consideration in every step of A.I. integration.

It is evident that there is no way technology can replace all the human factors involved in debt collection. However, there is much potential for technological innovation and application to simplify and rejuvenate the debt collection industry, and ultimately, it is our aim to bring about the change that is much needed in this business.