Artificial intelligence will revolutionise telecoms collections
13 December 2018 | Debbie Nolan
Debbie Nolan, commercial director at Arvato Financial Solutions, explains how artificial intelligence (AI) has the potential to help telecoms businesses maximise their collections, tackle bad debt and protect relationships with their most vulnerable customers.
Recovering bad debt is a continuous challenge for the telecoms industry. Recent estimates from risk analysts Neural Technologies show that globally, telecoms operators face a loss of $300 billion annually as a result of uncollected revenue and fraud.
This places significant financial pressure on an industry already grappling with diminishing profits as consumers’ communications habits change. UK telecoms revenues dropped one per cent in 2017 to £35.6 billion due customers spending less on traditional voice calls, favouring internet-based messaging platforms instead. This not only impacts the bottom line, but means the fundamental operations of telecoms businesses themselves, particularly their customer services, must change. As customers demand flexibility across a variety of platforms to solve their queries, telecoms companies must be ready to adopt new solutions to cater for these increasing expectations.
The changing face of customer services
Debt recovery relies on high-quality communications to help safeguard important customer relationships, particularly when working on sensitive or difficult cases. But it is also a repetitive, process-heavy task involving the management of vast amounts of customer data, often collated through multiple platforms. This makes it open to human error, which can negatively impact customer relationships, posing a risk to businesses in a market where switching providers is easier than ever before.
Telecoms companies therefore face a difficult balancing act. They need to be able to recover debt effectively in a way that safeguards relationships and protects the most vulnerable customers, whilst also boosting the availability of different customer service channels to allow customers to interact with them in the way they prefer.
Bots, AI and machine learning
AI is emerging as a key solution to these challenges, enabling providers to create platforms that bring together disparate customer data and provide a snapshot of a customer’s habits, circumstances, outstanding debt and contact history.
This capability is beneficial to advisors handling cases directly, providing them with the information they need instantaneously. This increases efficiency by automating previously routine tasks, enhances customer satisfaction through the provision of a bespoke, tailored service, and reduces the need to press customers for information that they may be uncomfortable to share. Intelligent software can also guide advisors through any decision-making process, boosting productivity while reducing the possibility of human error.
AI can also be integrated into new, intelligent online solutions such as chatbots, which can be the ideal medium for handling some of the most difficult or sensitive customer cases. Stripping away the need for customers to share information directly with an advisor, it can reduce the stigma surrounding collections and allow customers to settle their debts discretely.
In a trial of this technology conducted with a number of telecoms, finance and education businesses in Brazil, we were able to create a fully-personalised, truly omnichannel user experience. The technology, known as NOC.AI, is integrated with eight online messaging platform, such as WeChat, WhatsApp or Facebook Messenger, allowing customers the flexibility to communicate through the channels that are most familiar to them. Customers can send their query as a message, and receive a response from a robot, which will work to identify them and find the correct solution as quickly as possible. And if the robot finds itself unable to answer, a human can jump in at any time.
All data is captured by the NOC.AI platform, which is used as a machine learning resource to improve functionality, and to provide a full picture of a customer’s details to an advisor if they are referred. At the end of the trial, less than 7% of all enquiries received through the platform required direct voice interaction with an advisor, with 68% of all responses automatically generated. Collaboration between robots and representatives also meant that customer queries were dealt with seven times faster than by representatives alone.
Solutions like NOC.AI provide customers with 24-hour access to support and advice, with automated messaging delivering relevant information quickly and accurately. They also provide opportunities for employees to boost their communications skills, with their roles focusing primarily on solving the most complex cases.
Future of collections
AI is very much in its infancy, but it is clear that the shifts in the services that consumers require from telecoms companies must inform the way businesses interact with them. As solutions become more advanced, and able to recognise complex patterns and requests, eventually the industry will be able to fully automate the core elements of the collections process, freeing up time for advisors to handle sensitive or challenging queries.
By integrating artificial intelligence into recovery departments now, telecoms companies can effectively safeguard and futureproof their customer service provision with the best tools for both retaining customers and tackling bad debt.
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