21 Nov, 2018· read

Risk Profiling with a major UK building society

XpertRule was approached by a major UK Building Society who manages over 500,000 mortgage accounts.

They were looking for a better way to manage their customers who were falling into mortgage arrears. They recognised that being able to predict mortgage arrears is preferable, to both them and their customers, then waiting for actual problems to occur - so we set about to help with that.

Risk Mortgage Arrears

The challenge

Having already adopted the most effective credit scoring techniques to identify lending risk from the outset, they needed a system that could predict any change in circumstance once a mortgage had been approved e.g. changes to employment and marital status.

The challenge set was to profile such circumstances so action could be taken to help customers manage potential debt more effectively, stopping an arrears situation progressing to a repossession.

The solution

Using machine learning we were able to profile the characteristics of the mortgage accounts that had already encountered problems. Analysis of the data meant we were able to unearth patterns very quickly, some patterns were to be expected, such as high loan to value ratios but also the unexpected, such as “high earners” - this is because our software has no prejudiced opinions and/or no preconceived ideas to influence the correlations that are made.

Risk models could then be applied to all other mortgage accounts to manage the risk of mortgage arrears more effectively.

The benefits

The result of working with this UK building society meant they now have the tools to recognise the circumstances leading to mortgage arrears and stop the process early in the pipeline, keeping customers in their homes and helping them manage their repayments more effectively.

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