- Where Insurance & Technology Meet

High Heels, Insurance Trends, and Predictive Analytics

Can a better understanding of trends in women’s shoe heel height help predict insurance price and market direction?  Beats me, but IBM is testing the use of predictive analytics to understand trends in stilettos which might offer approaches to better understanding directions in a multitude of business, perhaps including insurance.

A recent article in IT World Canada noted that “IBM Corp. has been demonstrating a talent for using big data, specifically social media analytics, to predict trends across industries.”  One of those case studies involves predicting trends in heel height.

By analyzing large volumes of unstructured data coming from social media, specifically Facebook and Twitter,  IBM found trends that differ from the past.  Dr. Trevor Davis, a consumer products expert with IBM Global Business Services said that heel height usually increases in the case of an economic downturn. “This time (however), something different is happening. Perhaps a mood of long-term austerity is evolving among consumers sparking a desire to reduce ostentation in everyday settings,”

So what’s the link to insurance market trends?  At a recent seminar on Big Data experts noted that in a hyper-competitive market (say, insurance), the ability to discern trends and pull out relevant information from mounds of data will define winners.  A recent SAS Institute (Canada) Inc. seminar presented in Toronto, entitled: Conquer Big Data with Big Analytics, featured speakers with concrete examples.  As reported in Canadian Underwriter, Merv Adrian, a research vice president of information management at Gartner advised that the trick for companies is to identify and exploit relevant correlations between data points.  Analytics should be used to discover new insights, not simply to back up whatever is already known.  Such as the contrarian direction of consumers in respect of heel height in the current economic environment.

We have posted on the use of predictive analytics to improve automobile insurance results with Telematics data, and its potential to understsand aggregate risk exposures.  It is also clear that social media use in consumer and professional activity is increasing geometrically.

Putti2012 Technology Conferenceng these trend together suggests the there may be a number of new avenues to take in searching for improved insurance profitability. Being creative and using new data in new ways may well be one of these avenues.  Analytics, and new data sources, including social media, are part of the New Landscape that we will explore at the 2012 Technology Conference  in March.

Hope to see you there.