Navigating the cost-of-living crisis: How advanced analytics can mitigate credit risk

Britain's cost of living crisis isn't up for debate. It's real, and it's biting hard. With the Consumer Prices Index (CPI) surging by 10.1% year-on-year, the squeeze on household finances is undeniable.  Rising inflation, soaring energy costs, and stagnant wages are putting unprecedented pressure on consumers and businesses, with families struggling to cover basics like housing, food, and energy bills. In a volatile economic situation like this, banks and financial institutions must find a way to lend responsibly and inclusively. 

Historically, credit originated in a social system where banks lent to borrowers not just as a financial service but also as a socio-economic responsibility. Credit was seen as a public good, supporting communities, especially in economic hardship. This approach has been somewhat dented in the aftermath of the financial crisis. Banks have become more risk-averse even with products that did not have anything to do with the crash of 2008, in the first place.

Increasing complexity in financially engineered products gives banks avenues to invest capital and higher return instruments. As such, vanilla Loans and mortgage products have become secondary for banks. However, banks don’t exist in isolation. They deal with real people in the real world and are affected by every societal upheaval. The test arises when borrowers struggle to meet basic needs—like putting food on the table. In such challenging times, banks must rethink lending approaches, especially regarding financial inclusion for the underprivileged.

The Role of Technology in Modern Lending

Today's credit scoring system remains central to lending decisions, but technology has significantly expanded its capabilities. While traditional credit assessment relied on structured data like repayment history, advanced analytics now allow banks to process vast amounts of unstructured information. This shift enables more nuanced risk assessment.  For individuals with clean credit, lending is simple. However, those with limited history face barriers, especially underprivileged individuals lacking access to formal financial services.

Challenges with the Credit Scoring System

The crux of the problem lies in the  rigid credit assessment systems. While penalising those without a traditional credit history, they often fail to recognise financial stability outside established norms.

To the structured Data based Credit Scoring apps, a successful Executive relocating to the UK  may be deemed uncreditworthy  due to the absence of a local credit record. Similarly, a student from an underprivileged background securing admission to Oxford or Cambridge may not receive a preferential loan rate. he system is locked in a web of numbers, missing the context of real life.

The solution involves expanding beyond traditional credit scores to include alternative data and social media insights, offering a more inclusive view of financial behaviour.

Data and the Future of Credit Scoring

As banks modernise traditional credit scoring models, which are rigid and often exclusionary, must evolve to consider a broader spectrum of data points—both structured and unstructured. 

This requires moving Credit appraisal processes to cloud-based environments for more scalability, flexibility, and efficiency. Cloud technologies enable modern applications to quickly adapt to new data and risk models. By creating custom platforms, banks can develop more personalised borrower views.