Numerous models pushed out faster
More time on value-added tasks
Clear auditability & review process
Like many insurers, Old Mutual Insure faced a growing imbalance between the volume of pricing work and the availability of senior actuaries. With most pricing models being developed by junior team members, senior actuaries were spending a significant amount of time reviewing, correcting, and refining models. This created several challenges.
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Recognizing that this process was neither sustainable nor efficient, Old Mutual Insure started to search for solutions that would empower their actuarial team. This led the company to open discussions with Akur8 with the aim of accelerating the deployment of pricing models and reducing bottlenecks around senior expertise.
After a successful pilot, Old Mutual Insure decided to implement Akur8’s Risk and Rate modules. From the very beginning, junior actuaries became self-sufficient on the platform thanks to its easy-to-use interface and continuous support.
Using Akur8 allowed them to quickly reduce the amount of manual work and repetitive review cycles required previously. They were able to start building high-quality models independently and improve the review process with auto-generated documentation produced during modeling. This streamlined reviews by clearly showing where and why expert judgment was applied, making it easier for teams — and the second-line function — to understand decisions and accelerate approvals.
This shift allowed the team to redirect their time toward more value-added tasks and speed up pricing processes, which is key to staying competitive in the market.
After a successful pilot, Old Mutual Insure decided to implement Akur8’s Risk and Rate modules. From the very beginning, junior actuaries became self-sufficient on the platform thanks to its easy-to-use interface and continuous support.
Using Akur8 allowed them to quickly reduce the amount of manual work and repetitive review cycles required previously. They were able to start building high-quality models independently and improve the review process with auto-generated documentation produced during modeling. This streamlined reviews by clearly showing where and why expert judgment was applied, making it easier for teams — and the second-line function — to understand decisions and accelerate approvals.
This shift allowed the team to redirect their time toward more value-added tasks and speed up pricing processes, which is key to staying competitive in the market.
