As the executive director of the Society of Actuaries, Greg Heidrich, told McKinsey: “Actuaries have been around for as long as there have been insurance companies.” But their role has evolved as they navigate a landscape that involves more data, more technology, and perhaps more uncertainty. And it demands faster and better decision-making than ever before.
No wonder actuaries are now on the frontline of unleashing data faster and smarter in the insurance industry. The goal: not just estimating the financial impact of risk but continuously finding new ways to manage it better.
Blending industry know-how, quantitative skills, and a strong knowledge of the regulatory environment, actuaries have to be ready to respond to whatever risks the market throws at them. Covid-19? They have to calculate the consequences. Data explosion? They’ve got to stay on top of it.
Alongside increased modeling complexity, changing algorithms, perils, and risk factors, there is still the push to underwrite quicker, cheaper, and more accurately. That all combines to create a very complicated day job for actuaries.
Thankfully, by adding new technology to their existing knowledge, actuaries can meet – if not surpass – rising expectations. Skeptical about what that new technology looks like? We call it the Celonis Execution Management System (EMS).
Insurers and their actuaries can use the EMS to bring together historical data analytics with specialized actuarial knowledge, machine learning algorithms and automated workflows. The EMS helps manage all market complexities. That unlocks additional, actionable insight that could otherwise be lost in various data sets and risk tools. And it means organizations can manage future events faster, more accurately, and at optimal cost — and take action automatically.
Great news for the company and the customer. There’s also good news for the actuary if we zoom into how the EMS works. By reducing the complexity of data linkage from different tools, the actuary risk team itself can focus more on what it does best: using human judgment and insight to make effective risk decisions. Meanwhile, by tapping into the automation capabilities of the EMS, teams can reduce – if not eliminate – low-value administrative tasks from their day-to-day. That’s the kind of outcome that boosts team morale.
New, emerging risks are also taken care of by the EMS. By normalizing trends from existing data sources, the EMS can generate more accurate risk model simulations for ‘what if’ scenarios around process change. Recent history brings home just how important it is for insurers to be able to confidently answer any and all ‘what if’ questions.