In my previous article titled “What is the reality of the Chief Data Officer role within the insurance sector?”, I was joined by leading Chief Data Officers and Chief Analytics Officers who provided their thoughts on the status of data and analytics leadership and transformation within this industry. In the report, I touched upon the role of the Actuary and their business in calculating risk through stringent statistical and mathematical processes, however, we did not explore their obscure relationship with Data Scientists. The foundations of actuarial science can be dated back to the 17th century, whilst the term “actuary” was first coined by Equitable Life for its chief executive officer in 1762. The Society of Actuaries (SOA) defines this position as “a business professional who analyses the financial consequences of risk. Actuaries use mathematics, statistics and financial theory to study uncertain future events, especially those of concern to insurance and pension programs.”
The emergence of data science has been in direct response to the rise of Big Data, but of course data is useless without the ability to transform it into actionable insights. Insurers now have access to a plethora of structured and unstructured data sources churned up by telematics, wearable technology, social media and the Internet of Things. It is evident that both Actuaries and Data Scientists wish to effectively predict future outcomes. However, the methodology by which each party accomplishes this feat is rather different as well as the context by which the role operates.
Once again, we conducted a survey with the Chief Data Officer Forum, Insurance speaker faculty to better understand their thoughts on the relationship between these two critical roles.
How do you view the relationship between the more traditional Actuaries and Data Scientists and/or CDOs?
Eric Huls, Chief Data Scientist, Allstate
The two roles complement each other. Actuaries have a deep understanding of the insurance business as well as the statistical knowledge and skills to provide foundational analytic capabilities that every insurance company should have. Analytic capabilities only proliferate when you add data scientists into the mix. Data scientists often bring a unique crop of methods and techniques that advances analytics across all business areas. The fact that you see both roles in our industry is a testament to the value insurance companies are placing in analytics.
TJ Houk, Chief Data Officer, Trupanion
There are a wide range of relationships. In many cases, they are totally separate, they get no synergies from each other, and they actually compete. At Trupanion, the actuaries and data scientists sit on the same team, collaborate, and build each other’s skills. Both parties will be more effective if they collaborate, and that will ultimately lead to competitive advantages for teams that achieve that.
Data Scientists have to collaborate with traditional Actuaries in order to make meaningful business decisions. Most executives in insurance are trained actuaries.
Meghan Anzelc, VP, Predictive Analytics Program Lead, Zurich North America
There is some overlap between traditional actuarial roles and the roles of data scientists. Where analytics is used in areas such as pricing, often the actuaries and data scientists work closely together. Typically the data scientists have more experience and skill in manipulating large data sources, dealing with unstructured data, and using more sophisticated statistical or machine learning techniques. The actuaries typically have deeper insurance knowledge, knowledge of internal system data, and understanding of the concerns and constraints the business is facing. Each group complements each other and together can create better solutions to the business problems at hand.
Heather Avery, Director, Business Analytics, Aflac
The relationship between the more traditional Actuaries and Data Scientists and/or CDOs is still maturing. The culture of an organization will play a major role in ensuring that these functions identify distinct roles and responsibilities – and work together to achieve success. The relationship has to be viewed as a partnership, as both roles can contribute unique perspectives and actionable insights to drive value for an organization.
Brahmen Rajendra, AVP, Data Warehouse and Business Intelligence, Endurance
The relationship here is one of mutual benefit as the Actuaries understand in detail their line of business whereas the CDO/CAO is the bridge to harnessing the analytical industry.
It is clear that the majority of respondents are in agreement that although the relationship between Data Scientists and actuaries is in its infancy, it is critical that both parties cooperate in order to maximise the potential value of the raw materials that are leveraged to create actionable insights. Although Data Scientists are gaining great traction for their use of rigorous data and analytics processes, this is rendered almost useless without strong business acumen and context. Actuaries can provide this knowledge, backed up with centuries of refined familiarity with the insurance business model.
However, centuries of legacy processes can breed stagnation and great company inertia. Thus, actuaries should be agile and embrace data science and innovation or we may see the two roles at odds, competing for relevance.
By Andrew Odong
Andrew Odong is the Content Director for the Inaugural Chief Data Officer Forum, Insurance 2016. For more insights into the relationship between Data Scientists and Actuaries in insurance, join us on September 15th in Chicago.