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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Economic Outlook

This week I was fortunate to be at the Credit Grantors Association 2012 kick off dinner.

Unfortunately Benjamin Tal could not speak (he is great to listen to), however we had a good replacement with Peter Buchanan.

Generally the graphs pointed towards increasing debt load within the Canadian economy.  However there was less concern expressed on the economic effects of this over the next 12months due to the steady policy of the Bank of Canada.

However there were a couple of factoids that stood out as potential flags to watch.

  • Canadian debt to income ratio (DTI) is now around 165%.  This is now higher than the USA (it was always lower)
  • Although the DTI ratio has declined in the USA this reduction did not happen by more prudent lending or consumers reigning in spending.  2/3 of this reduction was from defaults.

As always… monitoring changes in the situation closely.

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The next ‘big thing’ in modelling

I was lucky enough this week to be able to attend the CSRSA general meeting.

The topic was  “Conceptual frameworks for a future analytic game changer?” by Larry Rosenberger, former CEO of FICO.

His view was that as we move into a world with greater access to information; the role of customer contact and using the data from this customer contact, will become ever more important.

This is critical information, that can represent a competitive advantage for companies if tracked and used in the right way (within the context of models, in this case).

Interestingly, despite being high profile, social network data was not seen as necessarily rich data.  Also information gained from customer care and collections processes whilst useful is expensive to collect.

This pointed to a sweet spot in between where targeting and asking the right questions to the right people at the right time, could yield very rich data helping target offers, and actions to best match the customer needs.

The design of this process to gather information will be crucial and may indeed represent a larger challenge than the modelling itself…..this is the new frontier.

For me I was left thinking about chaos theory and the linkage to modelling. The more you drill down the more complex it becomes, however all of this seeming chaos is driven by the interaction of a few simple parameters, highly sensitive to initial starting conditions.

Understand those and you can attempt understand the system itself…..

…..a thought provoking talk.

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