We help life insurance companies modernize their actuarial functions by identifying the skills, competencies, and resources that can help them achieve their strategic objectives and quickly respond to changing regulatory, investor, and internal demands. We work directly with our accounting and consulting specialists on the holistic transformation of administration and finance functions, as well as risk systems and processes.
Insurers are eager to take advantage of technology as a way to break the logjam of spreadsheets and manual processes, especially as an insurance company’s long-term profitability and capital strength depends on having an effective actuarial organization that deliveries timely and insightful information.
However, modernizing actuarial systems and processes is a significant task, especially in organizations and regulatory environments where change is constant. To be successful, re-engineering projects need to be carefully planned and understood in a larger context that includes people, processes, and technology as well as holistically as far as the involvement of not only actuarial, but also finance, risk, marketing and distribution, and IT.
Developing a modernization strategy that provides a path to real change involves visualizing a compelling future state, articulating and communicating expectations, defining a roadmap with achievable aims, and avoiding overreach during the implementation.
Actuarial modernization of any insurance company will involve deep and critical coordination between both actuarial and IT units, and will require alignment with the larger business objectives of management and the company. The multiple workstreams that are anticipated in any modernization effort demand thorough oversight and robust project management to ensure effective implementation of systems as well as an approach that addresses aspects of human capital, reporting, and organizational structure.
Access to timely, accurate, and consistent data is essential for valuation purposes, setting best estimate assumptions, and developing management information. Companies are struggling with establishing the “single source of the truth” and managing their growing data requirements in the face of numerous external (e.g., the Fed, Bloomberg) and internal (e.g., policy administration and claims systems) information sources, driving the need to enhance not only the clarity of source information but also the accuracy of attendant modeling and reporting based on it.
Inaccurate or delayed data can lead to conflicting data sets and critical errors in reporting, may undermine the accuracy of product pricing, and can compromise overall controls and modeling results. Such potential ramifications have insurers focusing on the quality of their data and how to obtain data with business value more quickly than ever before.
Setting assumptions is one of the most critical steps in the valuation process and insurers understand that adequate assumptions will produce appropriate product pricing and valuation, increasing the competitiveness and financial health of the company. However, while the consistent and accurate reflection of the company experience is essential for management to better assess and manage the company, it is sometimes a neglected function. Identifying reliable sources, assessing the credibility of assumptions, and determining the appropriate margins − and doing so in a timely manner − requires special skills, objectivity, and care.
With timely and insightful data analysis, companies can manage market competition and policyholder behavior through proactive business decisions, which will differentiate the management team from the competition, making regular review and assessment of assumption settings imperative for insurers.
Companies are replacing legacy valuation systems and older projection modeling platforms in an effort to reverse the trend of historic underinvestment in technology as well as to position themselves for a more dynamic and volatile marketplace. Faced with escalating business demands, a quickening pace of change in regulatory requirements, and increased competition, companies are demanding more sophisticated actuarial systems that integrate well with their IT infrastructure and allow them to address pending regulatory and reporting changes as well as respond to market opportunities, competitive threats, economic pressures, and stakeholder expectations. Choosing the right system and completing an efficient conversion are crucial.
Financial, risk, and regulatory capital measures are requiring increasingly complex calculations and insurers are realizing that ineffective model development or validation can have a number of adverse consequences, including mistakes in critical business decisions, underestimation of risks, and large financial misstatements.
In response, many insurers are evaluating techniques for assessing model effectiveness and incorporating these into the model design and monitoring phases, especially as they consider system upgrades and maintenance as well how to establish ongoing, effective monitoring and respond quickly to maintenance needs.
Transformation of actuarial systems will be central to companies’ finance and risk transformations as insurers have recognized that gaps in business intelligence synthesis can inhibit an actuary’s ability to provide timely, relevant, and reliable reports to management, limit the amount of data processed and the depth of analysis, and potentially increase stress on taxed IT departments as greater resources are required to generate results of declining quality and relevance to the business.
Ensuring that the actuarial infrastructure is comprehensive and consistent, and integrated with larger IT systems, to produce meaningful reporting is crucial to ultimate implementation success, and an assessment of actuarial systems and reporting procedures and services may not only mitigate the risk of limited business intelligence, but enhance reporting quality and data management.
Actuarial models and processes are becoming more complex and for insurers whose data feeds are manual or who rely on spreadsheet processes, there is operational risk and the possibility of human error. Combined with an absence of strong governance of actuarial models and processes, management’s ability to judge the balance between risk and reward can be compromised. This, combined with corporate governance and regulatory requirements that require that actuarial models and processes be well controlled and independently validated, mean that insurers must focus on coordination between their risk, finance, compliance, and actuarial functions and validate and document their control procedures. Such validation requires the involvement of data, actuarial, regulatory, and control specialists to attest to the model’s integrity.
Actuarial processes and systems are complex and intimidating subjects to understand, from the benefits they offer to the costly and disruptive risks they can present. An important task of any actuarial team, therefore, is to explain in understandable terms the role that certain actuarial processes and systems perform, their importance, and the associated risk. As companies struggle with resource needs and training for existing staff, ensuring that an actuarial team has the requisite knowledge, combined with appropriate systems and processes, to meet this task becomes critical to overall actuarial excellence, and understanding what constitutes a successful organization and how to develop one can be a challenge.
Insurers are addressing such concerns through clearly articulated standards and behavioral norms to set the tone for organizational excellence.