Most insurers are invested in developing risk models but despite their achievements, many are failing to progress their models and expand their application over time. As a result, they could be losing out on substantial value creation.
At the core of the issue is the fact that most data scientists/analytics experts thrive in creating innovative risk models but are not always as skilled at the more mundane work of implementing and monitoring those models. Carefully crafted risk models create little business value if they never get implemented or end up being one-time efforts that grow stale over time. When a risk model is created to solve a business problem, it should always be viewed as an ongoing program and effort.
Insurance executives should be asking: How are we managing our risk modelling program? And can we be doing things more efficiently and effectively?
This blog highlights five key points to consider in developing next-generation risk models.