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Are You Capitalizing on Analytics?

Life & Annuity Actuaries and Analytics: Active Partners or Unwitting Adversaries?
By Mark Breading, SMA Partner

The investment industry reveres and recognizes their brilliant quants as engines of growth, while the equally brilliant actuaries in the insurance industry often toil in obscurity. These highly respected, elite professionals have deep training and experience in analyzing data – but, what will their future role be in coming years as insurers expand their use of analytics? In the past, analytics in the insurance industry primarily focused on assessing the probability and cost of risk. Now, insurers are extending this discipline into other areas of the business, including customer-centric, finance-centric, and operations-centric analytics. As this evolution occurs, many insurers are contemplating what the actuarial role and responsibilities could and should be in some of these new areas. Is it smart to link the skills of existing actuarial talent with needs in these new areas? Should more actuaries be hired? Without structure, will actuaries become active partners in capitalizing on analytics for benefit across the enterprise – or is there a risk they could become unwitting adversaries to the spread of the analytics discipline?

Traditional Actuarial Use of Analytics: Actuaries use sophisticated mathematical techniques and models to design products, determine pricing strategies, and calculate loss reserves. In order to understand and calculate the probabilities of specific risks, actuaries gather as much historical data as possible – they are the original Big Data users. Life and annuity product providers need to understand morbidity and mortality risks, using historical information, along with other factors such as the potential impact of new medications, innovative treatment approaches, lifestyle changes, and consumer diet patterns. Although the expertise and models currently being used are extraordinarily sophisticated, the technology that is used for the analytics assessments is frequently custom developed, and in many cases antiquated tools (such as spreadsheets and APL) are still being used.

Applying Actuarial Skills to New Areas: Insurers are now venturing into many new areas of the business where highly sophisticated analytical techniques offer the promise of unique new insights that will empower the business. The question many insurers are addressing is whether actuaries could or should be involved. Might actuaries help to build tools and models to better understand customer behavior, determine where advisors and brokers/agents should be located, identify process-reengineering opportunities, or improve asset management and investment performance? One view is that these new domains lie outside the expertise of actuaries and should be left to experts in customer behavior, insurance company operations, and financial modeling. Another view is that the disciplines and approaches required to manage and analyze data are similar across all of these areas, and that actuaries therefore have an important role to play across the enterprise. Both views have substantial merit, which only complicates the decisions. Insurers need to think carefully about where and how to focus actuarial skills and how they might be effectively leveraged across the enterprise.

Extending Actuarial Skills and Analytics Across the Enterprise: Leading insurers are already selecting actuaries with broad and deep experience to champion analytics efforts across the enterprise. Insurers are also beginning to form data and analytics units with company-wide responsibility. The winning formula for capitalizing on analytics for customer, operations, and finance- oriented areas includes the following actions:

  • Choose an analytics leader: The analytics leader needs to be a good communicator and collaborator. The chief actuary may or may not be the best person to lead an enterprise-wide analytics unit. In some situations, it is imperative that the skills of the chief actuary be focused completely on traditional actuarial areas. In others, the actuarial bench may be deep and the chief actuary may have the personal characteristics and experience to lead efforts in other domains.
  • Build a team and staff creatively: Employ the “best player available” strategy of sports teams for staffing data analytics units. Ideally this unit will have experienced, team players from various business units, the IT department, and actuarial. It is important to blend business acumen, statistical/analytics skills, and expertise in managing data.
  • Develop an analytics technology strategy: Evaluate the current tools and models that are being used for analyzing data by the company. Rather than think of the business problems and the data in terms of separate islands, consider the potential for an integrated view across the enterprise. The strategy should address two fundamental components: data management and analytics technologies. It is critically important to rationalize, enhance, and organize data so that it can be easily provisioned to address countless different business problems. The next vital step is to assess the software tools and models, and then optimize their usage.

In an organization that does not proactively develop an enterprise-wide data and analytics strategy, actuaries can become unwitting adversaries to the spread of analytics. Even if the actuarial department is sometimes reluctant to endorse new technologies and models for analytics, those insurers that consider data and analytics to be a key part of the business strategy can take the proactive steps to empower the organization. They will usually find that actuaries can play an important role as active partners in the expansion of analytics capabilities to many parts of the company.

Strategy Meets Action (SMA) is a research and advisory firm exclusively focused on the insurance industry.


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