The Consumer Duty is a hot topic in our industry — not least because Financial Conduct Authority chief executive Nikhil Rathi announced at the UK Finance annual dinner that the deadline for implementation would not move again.
He also said the industry was on track to implement the regulatory framework by July 2023.
That wasn’t a surprise, but what came next was revealing. Rathi said the FCA wanted to “work closely with the industry so that the Consumer Duty can help shape the framework for the use of artificial intelligence [AI] and other new technologies”.
The question is: who will be first to utilise the data to take mortgage lending into the future?
Rathi gave an example of a Japanese insurance firm, Sompo, which had recently said the data it used could predict the weather and foresee natural disasters. For consumers, it could spot early signs of dementia, which he suggested could be used to pay out on insurance policies at the first signs; or even use the data to encourage customers to change their lifestyle to stave off its onset.
Rathi seemed suitably impressed with the technology developed by Sompo and its “god like” ability to predict the future, and this seems to be firmly where the FCA has its eye. And why not? The technology is out there and being utilised in other sectors with remarkable results.
Perhaps the best of them are those where you don’t even notice it’s being used but instead it seamlessly enhances your user experience of a certain product or service. An obvious one is Netflix starting to recommend the kinds of film and programme it knows you will like, with the actors that you like.
One could use this information in the future to predict the outcome of a case that met similar parameters
In the financial sector, we already have the likes of American Express using historical data in transactions and employing predictive models in place of traditional intelligence-based hindsight reporting, enabling it to forecast potential churn and customer loyalty more accurately.
So, where can AI and machine learning take the mortgage industry?
Lending criteria
Take mortgage-lending criteria — seemingly a small and overlooked area until we entered the market in 2017. Until that time, this was written in books, entered onto Excel spreadsheets or kept in people’s heads.
It was impossible to derive any kind of data from those sources, leaving anecdotal evidence as the only available option for lenders to understand what kinds of cases brokers were looking to place (and there was often a big difference between what customers were looking for and what they ended up with!).
This seems to be firmly where the FCA has its eye. And why not?
Fast-forward to 2022 and, working with more than 100,000 data points and almost four million searches — all done by brokers with a case to place — we can use this data to better inform lenders in so many ways.
Lenders are employing it to develop products and policy; to understand the potential market size of a change to criteria.
They can also appreciate which tweaks to criteria could bring in incremental business based on what they’ve missed out on. The list goes on….
Huge scope
Now let’s imagine we could take this data one step further; for example, where a view had been taken by an underwriter on a case that fell outside usual criteria but where the case was one the lender would be happy to accept. One could use this information in the future to predict the outcome of a case that met similar parameters, but modelled against the lender’s appetite for risk at that time.
And how about being able to develop products and criteria specific to each case, given what a lender can know upfront about that individual customer? Understanding how they manage their money, their working patterns and career or business prospects, how often they’re likely to move and to where — all of that could easily feed in to this.
The technology is being utilised in other sectors with remarkable results
The bottom line is that we’re all more predictable in our behaviour than we’d like to think. So it’s not going to take rocket science to use this information to enable more people to be accepted for mortgages and to obtain products that are tailor made for them.
The question is: who will be first to utilise the data to take mortgage lending into the future?
That’s one small step for a mortgage lender… but one giant leap for mortgage-kind.
Nicola Firth is chief executive at Knowledge Bank
This article featured in the December 2022/January 2023 edition of MS.
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