Meeting Complex Insurance Client Needs with Custom Technology

Colin Dowdall: Since 2018, Loomis Sayles has built a thriving insurance solutions business with $23 billion under management for 55 clients.¹ John, how has technology contributed to this growth?

John Gidman: Insurers often bring us challenging, and sometimes quite specific, objectives shaped by factors such as their operational, risk, tax and regulatory profile. In order to add value in such relationships, we consciously undertook a multi-year process that resulted in a differentiated and efficient infrastructure.

Back in 2000, our management team projected explosive data management requirements heading our way. Our projections were correct. Today, Loomis Sayles has approximately 20,000 distinct client investment management agreement guidelines supported by more than 3,500 security-level risk factors that govern how we manage.

To address this inevitable data wave, we initiated a “back-to-front” strategy that first focused on the spending and direction the back office needed to ensure data quality efficiently. We then moved on to the middle office segment of Loomis Sayles, otherwise called client services. Here too, creating straight-through processing efficiencies was a significant goal.

We then felt we had the architecture to underpin evolving needs in our front-of-house asset management groups. During this process, Loomis Sayles developed $300 million in intellectual property assets, protected by a combination of trade secrets and patents, that are delivered through an integrated architecture of around 16,000 apps—mixed and matched to our clients’ individualized specifications.

Colin: As a member of the Insurance Solutions Team, I have seen how this custom technology has benefited our clients. For example, one client needed a portfolio risk system that would speak to their in-house actuarial and pricing software. The client perceived that risk analytics customization, and the related cost, was beyond them. However, with a high degree of partnership over nine months, we guided them to a solution while also recommending various ways to look at risk based on our work with a variety of clients. The result was a highly customized risk analytics platform that enabled the client to price insurance policies using real-time data, view asset/liability metrics across its book and develop specific buy boxes to properly oversee various fixed income relationships and put money to work in the appropriate sector, duration, key rate duration and quality metrics. This solution provided us with a template for differentiation in the highly competitive fixed income markets.

John: You and I and our colleagues have partnered throughout the years to bring creative solutions to clients. One of my favorite outcomes has been our “insurance benchmark snapping” tool. Is it yours?

Colin: Yes, our development of a benchmark snapping process (Proprietary Benchmarks Aligned with Insurers’ Needs) stands out to me as well.

Late in 2019, our Technology and Insurance Solutions teams began engaging with a $40+ billion life insurance company. Its management needed a quantitative way to measure book-yield performance. Loomis Sayles Insurance Solutions team had developed a proprietary "benchmark snapping" process to quantitatively track buy-and-hold investment decisions relative to the opportunity set utilizing the extensive fixed income data housed in our risk systems. We can track the performance of the securities relative to the opportunity set through the life of the bond. We were able to perform over 80 distinct "snaps" for the client on a daily basis across their many sectors and product cells bringing an established and quantitative measuring solution to the client's Board of Directors. This process has been extended to P&C insurers oriented to book yield investing as well. We are nearing a four-year track record since its first client use.

Colin: From your technology vantage point, how might we meet clients’ future needs?

John: I believe the acceleration in technology capabilities that appears to be underway will have implications for large asset owners overall, with insurers representing an important growing segment of the institutional market. For example, consider the advent of large language models and substantial data sets that employ artificial intelligence algorithms (AI). This form of AI uses neural networks with sweeping parameters for advanced language and analytic processing. This is only one area where we believe Loomis Sayles’s intellectual property and proprietary technology can be leveraged for the benefit of insurers.

Closer to home, Loomis Sayles is not a sales and marketing firm, and we are not changing our stripes. Our focus is on developing customized solutions for our institutional clients, and therefore, we orient our technology budget to that end. More specifically, we plan for our ongoing analytics development to enable us to continue offering differentiated capabilities. We believe that if we are able to deliver a solution that works hand in glove with a client’s specific needs, we can grow alongside them.

For more, listen to Podcast Episode 133: Benefits of Proprietary Technology for Insurance Clients.