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Arguably, without this understanding, you have not embedded the Consumer Duty.

Like it or not, understanding the distribution of outcomes requires customer segmentation. This involves grouping customers into clusters and comparing the outcomes across those groups. This includes vulnerability.

There are a variety of approaches to segmentation. Some are better than others.

What should we avoid?

The traditional approach would be to start with fixed hypotheses about what matters for segmentation, and compare the outcomes across these pre-defined clusters.

More often than not, this approach resulted in crude demographic splits. For example, dividing the customer base into a handful of generic ‘life-stages’ with expressive names such as ‘Young Aspirationals’, ‘Working Families’, or ‘Empty Nesters’. You know the sort of thing.

It is safe to say that  this approach rarely uncovered the true distribution of outcomes. It is not granular enough. It does not let the data speak for itself. While useful when defining the target market and for marketing purposes, it is insufficient for embedding the Consumer Duty.

Under the Consumer Duty, the FCA expects firms to do more sophisticated customer segmentation. Not least because of the focus on vulnerable customers in particular.

So, how should we segment the customer base?

• Follow the money. Who are the most profitable customers? What are their demographic characteristics, financial objectives, and observed behaviours? Why are they the most profitable customers?
• Segment by customer behaviour. How does product usage vary? Thinking about behaviour over time can be a useful lens, for example: the length of time spent in overdraft before repaying, the length of time elapsed before making investment withdrawals, or the length of time spent on a standard variable rate.
• Let the data speak for itself. Use data science-led approaches, such as k-means clustering (a form of cluster analysis). These approaches sort the customer base into similar clusters of customers, without requiring you to pre-define the most important factors. Allow yourself to be surprised!

These approaches require the combination of behavioural economics (insights into how consumers think and behave) with data science (the ability to let data speak for itself). If you’re serious about embedding the Consumer Duty, then embedding these twin skills into your organisation might just be the best decision you make.

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