Summary
What this article covers in 30 seconds
- Random sampling has two problems – it’s random, and it’s a sample – leaving a large proportion of consumer data un-analysed and real issues hard to find.
- Our client evidence suggests that using Conversation Intelligence doubles team productivity, giving QA teams 100% oversight without a dramatic increase in resource.
- Keyword-based speech analytics often achieve one true positive for every five false positives; Recordsure’s neural network solution achieves accuracy around the 90% mark.
- Calls are captured via a telephony API or an audio capture app, then transcribed, classified into topics and risk points, and grouped by level of risk.
- The model is trained on thousands of hours of transcription and annotation to analyse organic, unstructured conversation, and the mortgage market can literally plug in and go.
Video insight
In recent weeks, we brought together Consumer Duty experts, in partnership with the BSA, to consider all things Consumer Duty and what it means for the mortgage market.
In our concluding webinar of the three-part series, Garry Evans, Recordsure’s Chief Product Officer, and Olivia Fahy, Recordsure’s Senior Product Manager, considered how the sector can use RegTech to effectively support Consumer Duty compliance and provide evidence for the FCA’s “show me, don’t tell me” approach.
Here we take a whistle-stop tour of the webinar’s highlights, including a closer look at the role that tech and AI can play in helping get the mortgage market ready for the new Duty.
A better method of oversight than random samples
To put it succinctly, there are two problems with random sampling – the method currently used by many mortgage Quality Assurance teams: it’s random, and it’s a sample.
By reviewing just a small sample of customer interactions, a large proportion of consumer data is left un-analysed, which can make it difficult to paint a true picture of where real issues may lie.
There is often a myth that upscaling to review 100% of all customer calls requires a dramatic increase in resource. This scenario may certainly be true if relying on human resource alone, but utilising the right kind of intelligent technology will mitigate this need – and actually give QA teams 100% oversight of customer interactions. In turn, their focus can be on the calls that need most attention.
Our client evidence suggests that using Conversation Intelligence doubles team productivity.
Speech analytics with a difference
Ensuring good, consistent consumer outcomes will be more important than ever under the FCA’s new Consumer Duty. And that’s where Recordsure’s Conversation Intelligence can transform how QA teams achieve call quality assurance whilst gaining full oversight of customer interactions.
The Conversation Intelligence model draws on machine learning and thousands of hours of manual training by our in-house linguistic analysts. The analysts meticulously examine customer calls and teach our model to understand the context around the language used in conversations.
And Recordsure’s unique ‘neural network’ solution goes beyond speech analytics that rely on identifying key words and phrases. Such models often achieve only one true positive for every five false positives. Recordsure’s solution goes way beyond this, with accuracy around the 90% mark.
Effectively oversee 100% of customer calls
Recordsure can capture your firm’s customer interactions in one of two ways:
- An API straight through to your company’s telephony systems
- An audio capture app, which can be used in face-to-face or remote customer conversations
The captured audio is converted to a transcript for analysis and then visually classified by our Conversation Intelligence model, with results visible on the Recordsure portal. The AI breaks the call down into key topics, so it’s easy to see what has been discussed when and where. From here, QA reviewers can select from classified topics to align with their checklist and systematically jump to the relevantly themed parts of the audio. The transcript aligns to the selected section so that reviewers can read, as well as hear, their chosen topic and area.
Classifications and beyond
Our AI goes one step further than classification. Conversation Intelligence will break your audio’s classifications down into further individual risk points, so it’s even simpler for the reviewer to check associated areas with the most relevant content.
As 100% of customer calls are reviewed, our model will scale and group calls based on their level of risk, meaning reviewers can spend the majority of their time looking at the most problematic calls. This gives invaluable oversight and also flags high-risk areas, whilst allowing a deep dive into specific cases.
This kind of analysis would not be possible via random sampling alone. Conversation Intelligence’s scope to find trends and themes in interactions gives you the tools to address the root cause of problem areas, so continuous improvement can be made across your customer journeys.
AI and tech’s role for the mortgage sector
- Catching the errors: With mortgage teams under increasing pressure, being able to evidence the information supplied to customers for both remediation and regulation purposes is key. Taking proactive action now to gain a deeper understanding of all the advice being given to customers will prove invaluable in the future.
- Complying with the Consumer Duty: The step-change in regulation that the Consumer Duty will bring should not be underestimated. More and more, the FCA talks about firms embracing AI and using data to gain greater oversight of customer interactions. Having this level of oversight is no longer a pipe dream and is achievable, so the FCA will be keen to see this in practice.
Breaking down barriers
Conversation Intelligence’s sophisticated system supports natural language. The best customer conversations can’t be scripted, and our contingent model is trained to analyse just that. It’s designed specifically to analyse organic, unstructured conversation – the model’s ‘engine’ has been taught from thousands of hours of transcription and annotation.
As Recordsure is used by a number of high street banks and mortgage associations, we have created a ready-made model that the mortgage market can literally plug in and go. This means no lengthy induction process, upfront investment or leaps of faith from firms.
Frequently asked questions
It’s random, and it’s a sample. Reviewing only a small sample of customer interactions leaves a large proportion of consumer data un-analysed, making it difficult to paint a true picture of where real issues may lie.
Only if you rely on human resource alone. The right kind of intelligent technology gives QA teams 100% oversight of customer interactions, and our client evidence suggests that using Conversation Intelligence doubles team productivity.
Models that rely on identifying key words and phrases often achieve only one true positive for every five false positives. Our neural network solution, trained by in-house linguistic analysts to understand the context of language, achieves accuracy around the 90% mark.
Through an API straight through to your telephony systems, or an audio capture app for face-to-face or remote conversations. The audio is transcribed and classified into key topics and individual risk points on the Recordsure portal, and calls are grouped by level of risk.
The FCA increasingly talks about firms embracing AI and using data to gain greater oversight of customer interactions, and will be keen to see this in practice. Firms also need to evidence the information supplied to customers for both remediation and regulation purposes.