There has never been a better time for insurers to consider Actuarial Automation and what it might mean for their actuaries’ productivity.
In addition to the demand for actuaries expected to skyrocket by 25 percent within the next ten years, a combination of retiring professionals and the inability to replace them with overseas talent is stretching existing actuarial teams thin. At a time when many life insurers’ actuaries are buried in regulatory related work around IFRS17, LDTI, and model consolidations, many insurers are considering ways to free up actuarial resources through automation.
Automating the experience study workflow does just that, while producing transparent, auditable calculations and ‘single source of truth’ insights for valuation and commercial teams to leverage across the business. Automating the experience study workflow can be achieved within a couple of months, in part because the process requires less governance than other actuarial workflows. This effectively reduces the required actuarial effort by 70 to 80 percent immediately, making experience study an easy place to begin the Actuarial Automation journey.
Why automating experience study is an easy choice
Beyond its lack of appeal for the actuaries tasked with completing the manual, time intensive work, the experience study workflow has many features which are suited for automation. It also doesn’t touch the valuation model, though automating experience studies can help non-valuation teams gain advantages from the outputs of the analysis, which is traditionally geared primarily towards valuation teams.
There are also significant benefits to automating experience studies, the least of which is that actuarial teams will no longer waste months preparing and manipulating data. Instead, actuaries can begin analysis on day one.
Benefits to automating the experience study workflow include:
- Reduce the time taken to prepare and validate data from months to days, allowing for real-time results and comparative analyses
- Adjust the process for new customers, new information, changes in market and competitor data
- Generate ‘single source of truth’ insights for both valuation and non-valuation teams to leverage across pricing, product development, claims, compliance, sales, etc.
- Eliminate the wasteful need for non-valuation teams to conduct their own experience study
- Free up months worth of time and actuarial resource, which can be reapplied to higher value actuarial work
- Remove information and data silos, making it easier for non-valuation teams to be consistent with valuation
Case Study: Montoux assists a leading global life insurer to automate the experience study process
Montoux worked with one of the world’s largest life and health insurance companies to transform the experience study process from an annual process to a near-real time activity, updated with new data and information on a monthly basis.
Our customer's experience study workflow took roughly three months, required significant actuarial resources, and produced insights which lacked concrete business value.
Working with the life insurer’s team, Montoux:
- Automatically ingests data monthly in a clear and structured format
- Leveraged the processing speed of the AWS cloud to generate flexible, granular analysis
- Created intuitive visualizations designed for use throughout the business
- Integrated outputs into existing financial models and reporting
After working with Montoux, our customer experienced:
- Substantial reduction in time and actuarial resource effort required to complete the experience study process.
- Transparent, auditable calculations
- Move from annual to monthly experience study, providing the business with timely insights and enabling actuaries to monitor and manage expectations on experience gains / losses
- Data automatically refreshes allowing trends to be monitored throughout the year.
- Lapse and claims rates can be viewed across various lenses and easily sliced and diced for different analysis
- Greater alignment between the actuarial and product teams
View the full case study here.