In May 2021, the Financial Conduct Authority released a consultation paper on the new Consumer Duty in an effort to “set higher expectations for the standard of care that firms provide to consumers.” In reality this means protecting customers in four specific areas:
- Information provided to customers to enable them to make informed decisions.
- Fair value pricing.
- Quality of customer service.
- Ensuring products are designed appropriately for the target market and work as expected.
As FT advisor pointed out, when reporting on How to start preparing for the new consumer duty, a cost-benefit analysis estimates somewhere in the region of £3.6bn to be spent on implementing and embedding cultures and technologies into organisations to meet the demands of the regulations set to be published by July 2022. This cost comes as no surprise given that the FCA handed out £568m of fines in 2021.
No doubt organisations will look to technology to aid in their compliance with the new regulations. Speech analytics, driven by artificial intelligence, is likely to be employed by a number of companies, not only to mitigate the risk of fines and bad press for not being compliant with FCA guidance, but more to the point to help companies set themselves apart from competitors by improving customer service and driving customer loyalty.
Of the four areas outlined by the FCA in their consultation paper, speech analytics offers the opportunity to ensure information provided to customers is relevant, enabling them to make informed decisions and that organisations offer a good quality of customer service. It is worth noting that whilst speech analytics has clear benefits within the new regulatory framework, its effects reach far beyond this. It will drive improvements in products, services, sales, marketing, customer experience and many other areas of business. Arguably, its most important asset is the insight into what customers truly value and deem as ‘quality’ as well as surfacing trends across different customer populations so companies can be more proactive in meeting emerging needs.
One of the focuses of the pending FCA regulations is on the information provided to customers to enable them to make informed decisions. The challenge for organisations lies in monitoring employees’ interactions with consumers to ensure that the information being provided to them is correct, understandable and relevant. Speech analytics provides a solution to all three of these stumbling blocks. Key word and phrase identification gives managers the opportunity to monitor exactly what their teams are saying to consumers. For example, if agents are using too much technical jargon, making it hard for the customer to understand what is being sold to them, or if the prices the agent is offering are the right ones.
Prior to speech analytics software this would have had to have been done by human assessors, who typically only cover 1-3% of all consumer interactions. Automatic, machine analysis of consumer interactions gives management 100% coverage, presenting a number of upsides. Namely that of risk mitigation. Misinformation can be identified quickly and addressed enabling customers to make informed decisions. Another benefit of great coverage is the ease with which organisations can identify vulnerable customers and make sure that the information given to them is relevant. This is hugely important as it aligns with the forthcoming regulations and FG21/1, the fair and consistent treatment of vulnerable customers.
Speech analytics is likely to have its greatest impact in ensuring a high quality of customer service is provided at all times. Currently, organisations have low coverage across quality assurance functions as monitoring customer interactions using humans is labour intensive, highly inefficient, expensive and often doesn’t surface interactions that provide good learning and development opportunities. The outcome of this is that staff retention is poor at call centres and new staff are often unengaged. This all culminates in a poor customer experience. Speech analytics can combat this, providing coverage at a fraction of the human cost and in far less time.
Using artificial intelligence, models can be trained to identify specific sections of interactions, complete sentiment analysis (based on the tone, speed and language used) and evaluate advisors’ overall soft skill abilities through a range of metrics (number of interruptions, talk time %, call duration, complaint identification). These metrics can then be used to implement data driven learning and development programmes that drive positive in the quality of customer service. For example, interactions with particularly positive outcomes for both the customer and the company can be identified and analysed to see what constitutes an excellent interaction. Consequently, these calls can be used as coaching benchmarks for the rest of the team, raising overall performance.
The benefits of speech analytics in creating a more transparent and higher standard of customer care are evident. Early adopters of this technology have the opportunity to mould it into a product that best suits them and their customers with regard to the new consumer duty guidance. From day one, organisations can achieve up to six times greater efficiency in their quality assurance process, but in a year they could achieve far greater gains. Furthermore, the nature of machine learning means that the more the technology is used, the more valuable it becomes as the model learns the language and structure of interactions. This means insights into agent performance and customer experience will be vastly more effective as time goes on. It should come as no surprise if we see speech analytics take off in the next few years as organisations try to implement technologies and cultures that align with the pending legislation.
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