As companies seek to drive profitable growth, both short term and long term, increasing the demands on the actuarial department, actuaries must re-evaluate the current actuarial operating model relating to people, process, data and technology to address current needs and be prepared for future needs of the business.

This is the first part of three written by EY that explores the elements of a successful actuarial transformation.

The business and competitive environment for insurers is challenging. For companies to succeed now and in the future — to find profitable growth while managing risk and capital — they need integrated, high-performing actuarial functions. Insurers continue to face challenges and should be prepared for the changing face of insurance, new products and exposures, increased data and big data, technology advances, ongoing regulatory change, scrutiny around documentation and controls and greater competition.

The actuarial function within many property and casualty (P&C) insurers has historically remained constant, but the rising pressures and challenges have led to greater demands. The actuary's work is growing more complicated; companies expect results and additional insights sooner to enable faster action.

Shifting landscape

Actuaries are asked to be better aligned with the company's finance and risk organizations and to play a bigger role in business decisions with a stronger commitment to advanced analytics and big data. As a result, insurance leaders are driven to refocus the actuarial team on higher analytics while also improving efficiency, responsiveness and transparency.

This shifting landscape has given rise to a changing actuarial role within the company. The new role requires an actuarial transformation, which is a top-down assessment, redesign and deployment of a new actuarial operating model to enable companies to succeed now and in the future.

Current state

Actuaries are involved in many of the company's competencies, including reserving, pricing, product development, price monitoring, risk management and IT. Within each of these areas, the actuarial team is integral to the technical process and performs such functions as data preparation, assumption setting and analyses, as well as making company leaders aware of important financial indicators. However, business decisions are sometimes left in the hands of others.

For example, management relies on actuarial reserve estimates to determine recorded reserves. In pricing, underwriters base their decisions partially on actuarial pricing analyses. In both cases, actuaries are constantly pushed to provide results more quickly, with more insights and diagnostics, to drive better-informed business decisions.

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Many companies currently face deficiencies that hinder the actuary's ability to meet these growing demands:

Data: Companies may have multiple, isolated or antiquated data architectures and systems, sometimes with incomplete history, which cause actuaries to spend a disproportionate amount of time on data preparation and reconciliations.

Systems: Actuarial analyses are often spreadsheet-driven without proper governance, increasing the likelihood of manual errors and delayed completion time, as well as limiting the flexibility to conduct scenario tests, address unplanned requests and perform more sophisticated and insightful analyses, such as predictive modeling, pricing monitoring and competitor analyses.

Actuarial utilization: Actuaries spend a significant amount of time on manual tasks, such as updating spreadsheets. They also spend considerable time on operational activities and routine reporting to fulfill a compliance or regulatory requirement, limiting their availability to perform advanced analyses and strategic activities. In addition, there is sometimes a misalignment of actuarial reports to business objectives and operational needs.

Resources: Actuarial departments face resource challenges, which intensify demands on the individual actuary's time, cause improper alignment of actuarial staff and increase key person risk.

Communication and interaction: Some actuaries have only limited interactions with other departments, and the interaction that does occur seldom leads to actionable tasks. For example, an actuary's limited formal interaction with claims processors, along with the context of and information provided in the discussions that they do have, don't allow the claims activity to be reflected in the actuarial analyses. Additionally, limited interaction with business unit managers keeps actuaries from fully understanding management's need for valuable diagnostics in making informed business decisions. This communication gap has caused frustration and a lack of transparency into the actuarial process.

Controls: Due to inadequate tools and the time needed for proper documentation, actuarial analyses don't always include complete records of the way the results were reached. The analyses may also lack formalized controls around the analytical methodology and assumptions to meet the scrutiny of auditors, regulators and the Internal Revenue Service.

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Current and emerging themes

As insurance companies become more automated, the transformation of the actuarial role within the company is leading to a process that's more responsive and efficient, enables better use of data and incorporates more thorough governance:

Responsiveness: A responsive process may permit advanced analytics that can enhance business decisions. This includes timely and insightful management reporting, integration of pricing and reserving, more sensitivity analyses, stress testing and decision support and greater leverage of actuarial and analytical talent across the enterprise.

Efficiency: A more efficient process may result in more timely results, better controls and a reduction in expenses. This includes more appropriate alignment of skills to the work, such as an actuarial focus on technical activities and IT or shared-services function focus on data management. This also includes using technology to standardize and automate routine processes and reports.

Data: More complete, accurate, organized and consistent data and data processes, capturing and using both internal and external data, may allow the actuarial group to do more — for example, predictive analytics and scenario testing — in a timely fashion. Self-service business intelligence tools like data visualization enable more insight into the company's data, such as exposure changes and data trends.

Governance: A better-governed process would enable the actuaries to meet the growing demands for better controls within the actuarial functions and systems, with well-documented procedures, assumptions and risks. For example, the reserve-setting process between the "actuarial central estimate" and "management's best estimate" can be better documented.

The views expressed herein are those of the authors and do not necessarily reflect the views of Ernst & Young LLP or the global EY organization.

Jay Votta is a principal in the Insurance and Actuarial Advisory Services practice within Ernst & Young LLP in New York. He can be reached at jay.votta@ey.com.

Ian Sterling is a senior manager in the Insurance and Actuarial Advisory Services practice within Ernst & Young LLP in Philadelphia. He can be reached at ian.sterling@ey.com.

Anthony Katz is a manager in the Insurance and Actuarial Advisory Services practice within Ernst & Young LLP in New York. He can be reached at anthony.katz@ey.com.

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