Ortec Finance: Insurers have room to improve their ALM
Ortec Finance’s head of research, Hens Steehouwer, discusses the major concerns for insurers in the current environment. He also explains why insurance asset liability management (ALM) modelling can be improved
What are the biggest concerns for insurers now?
Concerns of course differ across insurers, but there are some important general themes. Environmental, social and governance (ESG) factors are one issue, and in particular, climate risk.
The latest IPCC report, as well as recent natural disasters across the globe, clearly demonstrate the large and fast-moving impact of climate change on the world that we live in and in which insurers run their businesses.
We are seeing more and more requests from insurance clients for climate solutions, and I think insurers are catching up with the pensions industry in that space.
Another concern for insurers is how to provide decent returns to stakeholders in the future given (a) continued consolidation and increasing market transparency that depresses insurance product margins; and (b) the low interest rate environment, which is likely to continue for quite a while.
One way to deal with this challenge is for insurers to see how they can improve the risk-return profile of their investment strategy.
What broad insurance technology trends does Ortec Finance see in the market now?
One trend is the increasing volumes of available data and artificial intelligence that are becoming available, and how one can make sense of that data and to increase business efficiency and success.
Areas of data that are particularly relevant for insurers are ESG-type information and data for credit risk.
A second trend is the growth of cloud-native software development, which is very important. This is an approach to software development built on the benefits of cloud computing in which software is split up into smaller manageable units that work together. This allows for fast deployment of high-impact improvements.
Are you seeing any innovation in insurance and capital modelling?
Yes. In general, we see quite a lot of room for improvement in the field of ALM modelling for insurers. Traditionally, a lot of effort goes into assessing the current balance sheet and corresponding short-term capital requirements. These are very important of course.
But another question is how to get insights into the potential future developments of the balance sheet under a wide range of scenarios, and how this is impacted by both the insurance product, as well as the investment strategy.
One could call this “dynamic ALM” compared with traditional more short-term static interpretations of ALM. Several insurance companies around the world are now picking up on the benefits of this dynamic ALM approach. The required technology is readily available, but does not have widespread use yet in the insurance industry.
Within stochastic scenario modelling, the level of detail for modelling credit risk is rising. We have been increasing and improving that area quite significantly too, such as how companies’ ratings can change over time.
We also offer insurers the ability to do alternative risk and return assumptions at the push of a button, which makes it much easier to perform sensitivity analysis and stress-tests.
There is also a very interesting development happening in terms of combining scenario models and AI, and especially reinforcement learning, which is a specific version of AI.
We are in the research phase of combining the power of dynamic ALM models, powered by stochastic scenario engines, with that of AI technology, to optimise dynamic investment strategies. This provides a better trade-off between risk and return for stakeholders.
Why should insurers choose Ortec Finance’s technology solutions?
There are lots of reasons. In the first place, we have 40 years of experience in building and applying ready-to-use dynamic ALM models and stochastic scenario engines.
Our technology is always modular and flexible to integrate into insurance technology infrastructures.
Thirdly, our proprietary frequency domain scenario modelling methodology enables all economies, asset classes and investment horizons to be covered with one single calibration. This provides efficiency and consistency for insurers’ enterprise risk management.
Finally, our climate and ESG solutions, which are also modular, can be integrated into traditional investment and risk management frameworks. We have a dedicated team of climate and ESG experts to support insurers in this journey.
