But it can seem a daunting prospect to know where to begin and safely implement what could be a revolutionary change to your business. Identifying where to look and what credible solutions are out there is no mean feat. And the Consumer Duty focus on regulation now places the onus firmly on firms to ensure customers interests are at the heart of all business decisions – which is why having supporting evidence is more crucial than ever.
Futureproof for long term success
With that in mind, Recordsure’s Chief Product and Commercial Officer Garry Evans was joined by Senior Product Manager, Olivia Fahy to explore how RegTech and AI can help firms futureproof their long-term Consumer Duty strategy for sustainable success. Here, we’ve collated the key discussion points into five sections to explain how our AI-powered speech analytics solution can achieve 100% oversight of your customer conversations and help evidence your firm’s Consumer Duty outcomes.
Part 1: role of RegTech to help monitor and evidence Consumer Duty outcomes
RegTech, specifically AI driven RegTech, can review conversations more quickly and more consistently than humans when it’s trained with good data. Recordsure’s ConversationReviewAI does this by analysing verbal communications across a full customer life cycle and completes process adherence checks across that data. But ConversationReviewAI’s purpose is not to replace people – its principle is to complement them – which in turn will help QA teams be more efficient and effective, so they can focus their time and resource on the most needed cases.
Part 2: The power of tech-enabled process adherence checks to evidence Consumer Duty outcomes
Firms can evidence the outcomes of customer conversations in a consistent and sustainable way by moving away from more traditional, less effective review methods such as random sampling. Processes are a fundamental part of an organisation’s governance and it can be the method of how process adherence checks are done which can cause problems. Embracing a risk-based sampling approach like ConversationReviewAI is revolutionary so businesses can score customer conversations before human intervention takes place. Then QA teams can target their review time to where the AI has identified it’s needed most.
Part 3: Utilise speech analytics to process risk in customer conversations
ConversationReviewAI does things differently to other speech analytics tools, by building neural networks to create our AI model trained on thousands of hours of high-quality data from financial services conversations – with an accuracy rate of approx. 96%. Firstly, the Capture module of ConversationReviewAI is the element that records customer conversations – whether that be face to face, on the phone or online. This high-quality record allows compliance teams to ‘be in the room every time’, which in turn allows for broader oversight of every single conversation. The second stage of ConversationReviewAI then transitions to the Classify module, which uses sophisticated speech analytics to visually organise conversations thematically using AI trained on use case specific dialogue, helping to align points of conversations to a QA team’s review checklist. And finally, the Assure module of ConversationReviewAI then uses AI to identify whether your firm’s bespoke processes were followed on a call, issuing a score based on its level of process adherence.
Part 4: Transform your Quality Assurance to innovate beyond random sampling
ChatGPT has been a transformative piece of
AI that has captured the public’s imagination, and so we’re often asked if it’s
incorporated in to ConversationReviewAI. But ChatGPT is generative AI which
creates novel content – were as ConversationReviewAI uses AI to understand
content – not create it – which is a key difference.
And through ConversationReviewAI’s analytical
AI, QA teams can evolve beyond reviewing a random sample of calls to instead
achieve 100% oversight of them all. And because our AI does these reviews
quicker than a human– the Classified module doubles your QA efficiency as it
reduces the amount of time each call takes to review by half.
Part 5: Evaluating, evidencing and improving consumer outcomes
Firms that adopt ConversationReviewAI’s risk-based approach to reviews will in turn be able to deep-dive consumer call conversation data unlike ever before. As well as the Management Information and metrics that are created by virtue of using the product, it also provides a baseline of data to understand the process adherence failures that may deliver poor outcomes for consumers. By having more data of your customer conversations it’s easier to highlight where any issues may lie and a build a thorough picture of your customer journeys – providing the insight to remediate where necessary. ConversationReviewAI can also help with thematic reviews, for example our AI can perform thematic call analysis to identify key risk indicators across large volume of cases with minimal effort. It’s about allowing AI to do the heavy lifting so you can focus your resource on the tasks that require human intervention.
