Life insurers’ annual experience study process is a consistent source of dread. As the process currently exists, it’s an enormous drain on actuarial resource and under delivers in terms of value to the business. Because it is slow, manual, and costly, it is difficult for insurers to focus on much more than simply getting it done.
But this compulsory process is an opportunity for insurers to deeply examine the data they’ve collected on claims and lapse rates. Done properly, it can help them both reduce cost and generate deeper customer insights to improve value. In order for this to happen, the existing process needs to change dramatically.
The existing experience study process demands much and delivers little
Inefficient tools make the existing experience study process highly manual, driving up demand and strain on valuable actuarial resources in a workflow that can be completely automated.
This stems from the way life insurers think about the process. Experience study is treated as a necessary evil. It’s driven by regulatory and compliance requirements and disconnected from strategic value drivers. Life insurers haven’t yet reimagined the way it could be leveraged or improved through technology and automation.
The existing experience study process has two key consequences for life insurers.
1: It requires a ridiculous amount of actuarial resource to complete
Many insurers use tools which aren’t designed for the process (Excel, and inflexible statistical software packages) and don’t begin organizing the required data until the deadline rolls around. What follows is an inefficient, expensive process of cleaning the data, wrangling it into unsuitable models and operating environments, and finally performing the analysis - usually a whole two months later.
This is a massive, wasteful drain on actuarial resources, which are under significant pressure already. With the right AI-driven and cloud-based tools, this entire process can be automated.
2: The insights are outdated and disconnected from the operational side of the business
The study is performed only yearly, meaning the insights become outdated quickly, and provide little value at an operational level. Without the ability to run the process closer to real time, life insurers’ are unable to gain much from the information it derives.
The experience study is also coordinated through the finance function or pricing team, and is typically siloed from the operational teams which could leverage the data and insights. Even if they did link, the lapse and claims experiences are often run through financial models and resulting insights don’t provide enough granularity at the customer or distributor level to be operationally useful for customer facing teams.
The siloed nature of this process means insurers lose useful insights the analysis could generate, preventing life insurers from exploiting potential gains. So how do life insurers take the experience study out of its existing silos and gain a strategic advantage from these insights?
Reimagining experience investigation through automation
There are better ways for life insurers to approach the experience study process, ways which meet both regulatory requirements and business objectives. Because this yearly study is required, why not find opportunities to leverage it strategically?
By automating the process of gathering, cleaning, and analyzing the data, insurers avoid the traditional, preliminary tasks which drag the process out. Automation enables insurers to easily run and monitor experience analysis monthly, and deliver invaluable insights. Life insurers gain a deeper understanding of customer and business drivers, and can easily and efficiently address and track them.
This means, for example, if an insurer sees an increasing lapse trend in a particular distributor segment, operating teams can work to understand where it’s coming from, adjust the existing strategy, and monitor the results.
The added benefit of conducting this cycle monthly is the data is automatically prepared for the end of year, regulatory driven experience study, reducing the time, resources, and costs of conducting that required annual study.