Credit decisioning needs a new approach

It is no longer pure complexity of the scorecard. Processes, models, and methods need to be created to manage the loss of historical data’s predictive power, and to adapt to new business models and customer behaviours.

Lenders need to assess different impacts of events on industry sub-sectors in conjunction with forward looking economic views and financial performance and cashflow assessment and projection.

And use a decision infrastructure designed to work with any event or sequence of volatility, like a cost-of-living inflationary event.

Unprecedented events have driven volatility and unpredictability

The 2008 financial crisis, was just that; financial, with impacts from financial and credit drivers where traditional risk measurement could assess and explain. Current conditions are driven by the global pandemic and Russia's Invasion of Ukraine; non-financial drivers, which consequently renders historical credit data less meaningful. Advances in decision science and machine learning are useful but, without a different outlook, merely allow us to come to sub-optimal decisions in quicker and better ways.

The new world requires a shift in credit decisioning ideology or principle.

Five impacts for UK lenders:

1. Polluted data - Historic performance data is obfuscated by government intervention (e.g furlough, payment holidays, BBILS) and outcomes are not driven by historical credit performance. Affordability assessment relying upon historical trends is flawed
2. New business models - Changes in shipping and logistics, remote working, and a shift to digital-first businesses have changed the behaviour of SME's and customers.  
3. Altered spending habits - Supply driven inflation drives new behaviors, seen at the industry subsector level (e.g. choices of holiday, entertainment, food, etc.) This again is different from historic demand side inflation managed by monetary policy.  
4. Shifted risk characteristics - Inflation as a characteristic has not been powerful in recent history, therefore has not historically been built with weight into risk models
5. Constrained supply - Bank balance sheets are saturated with Covid support loans and future operational capacity will be consumed with management and recovery

Next generation decisioning with Abel

We have built decision model suites, proprietary cashflow affordability models, and monitoring frameworks, which bring together:

• Economic forecasts
• Industry subsector segmentations
• Climate data
• Subsector economic growth expectations
• Transactional Data, including open banking

With financial and credit performance, we make better decisions that better reflect the current context.