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Jon Hickman, chief executive of Flexys Solutions Energy retail, Generation, Policy & regulation, Strategy & management, Water, Opinion

Jon Hickman, chief executive of Flexys Solutions, explains the benefits of new technology

As consumer debt increases, the utility sector is looking to emerging technologies to help serve customers better and maximise operational efficiency. In debt collection, applying machine learning to extend the value of data and using it to innovate strategy and process is proving to be a game-changer.

The right journey for each customer at a reduced cost

Machine learning provides the best results where there is a business question complex enough to warrant its use. In early collections, that question might be: “How likely is this customer to pay and what is the next best action to make it happen?” At Flexys we have developed a machine learning solution that significantly reduces unnecessary or inappropriate engagements (and their associated costs) and helps to create an elastic capacity so that resources can be targeted more effectively. Meanwhile, customers only experience as much of the collections process as is appropriate, with a lower cost, ‘light touch’ for self-resolving individuals. The objective is to create a ‘segment of one’ decision-making capability that treats each customer as a three-dimensional human being while operating effectively within the resource constraints of the business.


Richard Vennard, Dŵr Cymru Welsh Water, Flexys Refreshing Collections Podcast

There are huge opportunities around technology, we’re trying to do better segmentation, understand customers a little bit better


Augmenting decision-making with context

As collections move into the digital age, machine learning can be used to help fill the gaps in emotional understanding missing from remote contact. Along with existing data, using machine learning to understand and categorise responses and signals in an online journey means that anomalies, difficulties or even potential vulnerability that would otherwise be hidden can be flagged for attention. A strategic decision on the most appropriate way to proceed can then be made based on the organisation’s own policies and practices. This enhanced segmentation makes it easier to treat customers fairly according to their circumstances and avoids creating additional detriment via systems that are not designed with non-average customers in mind.


Richard Vennard, Dŵr Cymru Welsh Water, Flexys Refreshing Collections Podcast

Welsh Water are looking at artificial intelligence and the machine learning pieces to provide a range of different abilities for the customer to interact with us


It’s not the future, it’s now

At Flexys, our specialist R&D team is dedicated to collections-specific applications of machine learning through our modular cognition solution. Our cutting-edge research includes a knowledge transfer partnership with Professor Jim Smith, head of interactive AI, and his team at the University of the West of England.

Our results are impressive and we are keen for more energy and water providers to join our current customers in this exciting and game-changing enterprise.


This Expert View first appeared in Flex, issue 3. Read the full issue of Flex here

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