EUCI conference

Was able to present at the EUCI Credit and Collections conference this year.
Some interesting speakers and good discussion, especially around the use of modelling within a structured, regulated, public utility infrastructure.

What was interesting was, although there are differences the dynamics around risk operations and collections is very much the same, although the speed of change is significantly influenced by constraints on funding.
This is especially driven by the fact this is largely supported by tax payer dollars and they are trying to maximize tax payer value and value to the community they work in.

However the theme was clear.
Many of the same techniques will work well in this space and the industry is evolving on similar lines.
A robust Risk Operations process is a good way to yield investment dollars. This is funding on the balance sheet that can be released.

Another thought provoking discussion was how behavioral modelling can be beneficial from a legal point of view.
This was a linkage I had not really thought about before, and comes into play when you are providing a service that is a viewed as a necessity.

If you capture the right information upfront, this info can be built into the model and hence the treatment strategy.  This allows the strategy to be consistent and customized for the customers situation.
Importantly is also allows the treatment to be standard and really objective.  (it is about being fair and consistent)

All in all a great discussion, with a good group who are really working hard to do the right thing.

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Standardised Risk Operations Strategy

More interesting discussions this week around a standardized approach for Risk Operations Strategy.

This really is a opportunity and clearly applicable across multiple industries and business segments.  Each are at varying stages of evolution and there is potential for a significant benefit in some sectors.

Food for thought.

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How much segmentation is too much segmentation?

In the world of risk management and modelling much revolves around the segmentation of data.

New customer segments, new attributes for segmentation, segment performance and reporting.

Indeed, much of the new development – ‘the edge’ – is also around this approach.
Obtaining new data, more detail to be able better segment, understand and hopefully model (future) predicted performance.
With the explosion of computing power, ready availability of data this has become ever more popular, with new, great tools on the market every day.

However we need to step back and ask the question, how much segmentation is too much segmentation?

For example.

  • Replicating what is applicable in financial services, maybe a little too much segmentation in Telecommunications, and way too much in Utilities
  • In a larger business, using 10, 100 or more segments may work well, but in smaller businesses the population in each segment maybe so small to be fairly meaningless statistically, and certainly hard to manage.

There is a cost to all this complexity.

It is certainly exciting, interesting and even fun to explore the data in ever more detail, however is it critical to manage, to ensure the level of detail and segmentation is relevant to the business and industry at hand.

Sometimes getting the basics right, with less segmentation can yield higher value.

Getting this balance right is in fact the tricky part..!

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