The changing role of actuaries

The proliferation of analytics across the insurance industry has created an army of amateur data scientists, many of whom believe they have discovered the next big variable or data set that can enhance, or even replace, actuarial tables.

This reality has created a new series of dynamics for actuaries, changing the nature of the work they perform, oftentimes for the better. As more people become comfortable with analytics, actuaries are being given more opportunities to positively impact an insurer’s book of business and more directly affect the end-result of their efforts.

From spreadsheets to solutions

Platforms and solutions are becoming more common across the insurance landscape. These offerings mirror many sustaining technology trends such as SaaS (Software as a Service), PaaS (Platform and a Service) and IaaS (Infrastructure as a Service). Salesforce with its CRM solution and Amazon with its web services are among the most obvious examples.

As insurers become more comfortable with these approaches, they’re beginning to require their actuarial firms to adopt the same approach. This means a shift away from simply providing actuarial tables and offering underwriters guidelines on how to use them, and toward consultation and collaboration. In very real terms, actuaries are becoming everything from educators to advocates, helping employees at all levels of insurance operations more easily understand the science behind the data. This new approach isn’t limited to external resources, as many in-house actuaries are facing the same pressures.

Aligning actuarial science with business goals

Whether internal resource or outsourced ‘hired gun,’ the end result insurers expect is exactly the same: Actuaries are now being required to align their work with the business goals of the carriers that employ them. This means the actuarial community must become far more collaborative and transparent. From interactions with the C-level executives that are driving business strategy through cooperation with underwriters at a far earlier phase, actuaries are finding themselves in the middle of more discussions with more stakeholders than ever before.

One thing actuaries can do in order to be more effective in this role is rely more heavily on underwriters. While there has historically been a feud between the groups (more than half of insurers see friction between the two professions), underwriters have tremendous front-line knowledge that can help actuaries be more effective in aligning business goals. This is especially true when leadership has decided to grow into new classes or geographies; underwriters will be able to explain how they’ve used data to stay within the confines of an insurer’s risk appetite, and this is almost always based on information that’s unavailable to an actuary.

Here are four new roles actuaries must now consider as part of their job description, while they attempt to align their workflow with business needs, and how they can take advantage of the new opportunities.

Data science and modeling

In order to align science with business goals, actuaries are required to incorporate elements of other data sciences, taking into account a number of variables to identify “good risks” throughout individual classes. This means looking at thousands of variables, eliminating those with the least value, and performing an analysis on those that have the biggest value.

Take commercial auto, for example. The traditional actuary might recognize the overall poor performance of the line and create tables that limit an underwriter’s ability to write commercial auto business. Today, however, actuaries are being instructed to be far more granular in their approach, looking at identifying classes and policies that may carry less risk.

Data governance

Another new role that actuaries are undertaking is data governance, which is critical for the short and long term success of data initiatives. Generally speaking, data is being created and pushed out from legacy systems, which were unlikely to have been designed with a well-functioning API architecture. This has required IT teams to be creative in how they export and share data across systems; it’s not uncommon for files to be exported in excel and then imported to another system from there. These manual approaches leave something to be desired in terms of security, but also in terms of accuracy. There is a tremendous opportunity for human error. It’s also incredibly important for actuaries to work with IT to implement version control and accurate logs. Very few individuals in an insurance company should have access to make changes at the database level, and those changes should be cataloged and capable of being easily reverted.

Actuaries must now be cognizant of the shortfalls of legacy systems, and ensure that data is being transferred accurately on a regular basis. Without accurate and up-to-date information, it is impossible for actuaries to build models and tables on the most relevant information. Essentially, they are now becoming responsible for the quality of the data that they’re using.

Work with regulators

Data governance comes with the additional responsibility of working with regulators. Insurance companies can not simply build machine learning initiatives in a black box, because this wouldn’t gain approval from regulatory bodies. Instead, actuaries can utilize the version control, data modeling techniques and well-governed data to explain why they are making certain assumptions and taking certain approaches.

In short, properly governed data makes it possible to expedite regulatory approvals, and overcome questions from regulators. This is particularly important for insurers that are writing business in multiple states since each state has its own requirements.

Measuring and optimizing results

If the new roles for actuaries are focused on aligning their data with the business goals, it makes sense that their work is more regularly examined. C-level executives are utilizing big data initiatives and external consultants to track the results of their actuarial efforts. In fact, there are software solutions that allow executives to examine a book of business, on a real-time policy-by-policy basis, to understand exactly what their risks are. This level of information allows executives to optimize their business to their risk appetite.

While it may seem daunting, these new levels of responsibility are creating tremendous opportunities for actuaries, making it easier to identify and reward top performers. They’re also creating more opportunities for actuaries to increase their impact on the overall health of a book of business.

Kirstin Marr (kirstin.marr@valen.com) is president of Valen Analytics. These opinions are her own.

Also by Kirstin Marr:

• Assembling the ‘Justice League’ for predictive analytics
• How data consortiums impact the accuracy of predictive analytics