Risk Management: Analytically Based, Data Driven

Timothy L. Coomer, Ph.D.

A few months ago, we conducted a survey concerning the utilization of analytics in the retention decision process.  As I continue through the PhD program at Oklahoma State University my prospective dissertation topic continues to move toward the study of analytical capabilities within an organization and its correlation with organizational performance.

While the risk management department, and specifically the risk retention decision, are just one part of a network of potential “analytically based, data-driven” decisions within an organization, it is perhaps indicative of the entire state of analytics within a business.  From my research, I think it can be reasonably suggested that within the next few years there will be a dramatic increase in the use of analytics in most business decisions and processes.  In fact, MIT Sloan's article, "From Value to Vision:  Reimagining the Possible with Data Analytics" states that, since 2010, 30% more companies are using data analytics to gain a competitive advantage.  Among other things, they use this new found advantage to, "act more quickly:  to deliver faster results, to make real-time decisions and to accelerate the development of products or services."

The survey had a multiple-choice section with four questions followed by an open comment section.  The responses that I received were numerous, thoughtful, and greatly appreciated.  In today's entry, I will attempt to glean some insight from these responses and make recommendations based on the feedback.  First, the response questions and graph of the responses are shown below:


survey results

Finally, the comments at the end of the survey reflect several consistent themes:

The analytical sophistication of the client typically corresponds to the size of the organization.  Smaller companies, although making important financial decisions, tend to use a simplified decision method that looks at guaranteed cost premium vs. some estimated cost maximum at one or two given retention levels. Because this decision to consider retention is typically an effort to lower overall costs, there is resistance to pay for any type of analysis, even though the analysis is designed to support a wise decision.

Most survey respondents see an increasing trend in the use of analytics in the retention decision process but still feel it is significantly underutilized.  Some brokers have indicated that they will not work with clients that are not willing to follow the rigorous decision process that the brokers offer.  This was interesting to me – it was not clear if this was to limit E&O exposure or simply to filter out clients that are probably price shopping and will not be profitable long term.  I like this assertive posture, however, and have known several firms around the country that have been successful with this attitude.

Some respondents noted the lack of sufficient analytical expertise (enough staff that are experienced with these types of analyses) within brokerage firms to offer sophisticated analytics to all that might benefit from it.  Sometimes, this resource is limited and is made available only to the largest clients.  As a result, the analytical work is occasionally obtained from the carrier – perhaps not the most unbiased source.  There are a number of ways to alleviate this issue, but perhaps the most cost-effective option is the education of those involved in handling the analysis.  If a broker can utilize literature or video training to improve their own understanding of how to use analytics in a retention decision (and elsewhere), they can move forward with the confidence that the organization as a whole is taking the maximum effectiveness from an analysis.

A couple of areas of vulnerability were noted for clients that fail to employ analytics during the decision process.  First, the stacking effect of collateral (see this blog: Strategy Beyond Buzzwords and associated graphic) and the downstream costs of retro plans and other loss sensitive plans can create some nasty surprises (and in our experience often do) if not anticipated and analytically modeled.



I will conclude with specific recommendations for brokerage firms:

1. Brokers need to define and communicate the analytical based, data-driven process they offer their clients.

2. Brokers should design a one-page outline that summarizes the retention decision process and that brokerage firm’s unique methodology.

3. Brokerage firms should embrace the utilization of analytics as a differentiator and use the topic of “big data” and analytics as a sales point with CFOs.  This recognizes the pressure that CFOs are under to push analytics into ever aspect of the business.

4. Brokerage firms should develop in-house analytical talent that can produce analytics and interface with outside actuarial firms.

While the topic of “big data” is all over the news, the more important topic is the utilization of analytics to make better business decisions.  I am certain that this is going to be the core competitive advantage across most industries in the next 10 years. The risk management department, due to its proximity to the CFO, will quickly feel the pressure to “prove” that decisions were analytically based and data-driven.  It is your role and opportunity as the broker to deliver those analytical capabilities.  And, if I can put in one shameless plug for SIGMA, we are here to help!

As always, feel free to email me directly with your comments at TLC@SIGMAactuary.com. Also, register for our free resource portal at www.SIGMAactuary.com/resources.

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