“(Lenders) just don’t know where that is going to go, how higher it is going to go, where it’s going to stop, so it makes it very difficult to know where to price their mortgages,” mortgage expert Ray Boulger told BBC Radio a few weeks ago, commenting on the steep rise in UK government bond yields that had spooked mortgage lenders and borrowers alike. In late September, Reuters reported, a whopping 935 mortgage products were pulled from the market overnight, with Virgin Money and Skipton Building Society temporarily withdrawing entire product ranges. That’s twice as many as the previous record of 462 in the wake of pandemic lockdowns.

But that’s not the only difference between the current global economic outlook and the pandemic-induced recession of 2020. Back then, Pew Research Center pointed out, inflation was mostly an afterthought. Today, it’s a major worry for governments across the globe. In May, the US inflation rate climbed to 8.6%, its highest level since 1981. In 37 of the 44 advanced economies examined by the nonpartisan fact tank, the average annual inflation rate in the first quarter of 2022 was double what it was two years prior. In 16 of them, it was more than four times the 2020 level. Turkey saw the highest inflation rate at a staggering 54.8%.

Central banks: reaching for the old inflation playbook, heaping on new pains

In a bid to ease inflationary pressure, central banks have been raising interest rates with a degree of synchronicity not seen over the past five decades, according to a fresh study by the World Bank. And they’re not done yet. In their continued efforts to beat down inflation, they may need to raise interest rates by another 2 percentage points. This, on top of the sharpest slowdown after a post-recession recovery since 1970, dwindling consumer confidence and stalling US, Chinese and European economies, paints a gloomy outlook – and casts further dark clouds over banks and their customers.

In the UK, for example, annual mortgage payments could shoot up by £5,100 between now and the end of 2024 in over five million households, the Resolution Foundation predicts. According to the independent British think tank, almost half of borrowers are about to see their family budgets shrink by at least 5% as a result of higher housing costs. Some 1.2 million of them with variable-rate mortgages will immediately feel the bite of base rate changes, followed in a few years’ time by the 85% of homeowners who are currently on a fixed-rate contract. Meanwhile, new borrowers are looking at the highest rates on two-year fixed deals since the 2008 financial crash.

Based on their drastic reaction to gilt market volatility, lenders aren’t exactly well-prepared to navigate the current economic climate. “Banks have been caught with products on offer that are just bad business after the surge in funding costs,” explained The Financial Times columnist Helen Thomas. “Business that looked decent very recently is now uneconomic, particularly for those with the keenest pricing in the market.” Not to mention risky, with default rates on mortgages set to rise between October and December, along with defaults on credit cards and other unsecured loans.

Banks have plenty to gain if they play their cards right – here’s how

So how can lenders return to the market with competitively priced products that can help them maintain a healthy level of asset quality in their mortgage portfolios?

Two words: data analytics. Now you’re probably thinking, “Hasn’t creditworthiness always been assessed based on data?” Yes, it has. Just not necessarily the right kind of data. When credit reference agencies determine potential borrowers’ creditworthiness, they typically zoom in on a single factor: credit history. Meaning they look at the amounts, terms and types of loans taken out, payment records, credit searches, defaults and so on. This may be fair, but not the whole story by a long chalk. 

Over the past few years, a bevy of new data sources and technology solutions have become available for banks to get a more accurate and intimate look into people’s financial standing. 

Open banking data and AI- and ML-powered analytics tools can reveal consumers’ income and expense lines, spending behaviours and everything in between. Advanced customer profiling capabilities can lead to better risk management and compliance outcomes, helping lenders keep their non-performing assets at bay. Even more so when used to proactively target existing customers with pre-approved loan products. 

Financial institutions can greatly benefit from these solutions, whether or not another base rate increase, or a full-blown credit crunch, is around the corner. But during periods of uncertainty, such capabilities might just separate the leaders from the also-rans in the race for customers. 

Using income and expense analysis, members of the former group will not only be able to figure out people’s creditworthiness based on past borrowing and financial behaviour but also foresee if they could still make payments should their disposable income drop by, say, 30%. Or categorise outgoing transactions to see how much money an applicant spends on essential purchases – and if they can afford another loan should living costs continue to rise. 

Intrigued? Explore Finshape’s real-time and predictive analytics solutions and how they can transform data into high-value insights and meaningful interactions between banks and customers.


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