Many insurers and underwriters see the relevance of data science and a data-driven customer journey, but not everyone is putting it into practice yet. Erwin van Oosten, Commercial Director at Building Blocks sees several reasons for this, but also offers solutions. The first reason mentioned is that data science still feels complex to people who don’t deal with it on a daily basis. It is therefore important to show that it does not necessarily have to be complex and that it fits within – and delivers value to – the daily operations of the business of insurance companies. By working pragmatically and experimenting, a solution can be tested relatively quickly and be optimized and further developed over time.
But which business case is best to start your data science journey with? Erwin van Oosten explains that it is crucial to start thinking from the business perspective, so what are the most important KPIs you want to improve? And what factors contribute to the performance of these KPIs? You want to have insight into the biggest bottlenecks of your customer journey, and thus where the most value can be delivered. From these data-driven insights, the most valuable business cases can be detected.
That insurance companies, intermediaries and underwriters can gain much value with their data is shown by the examples and concrete successes in practice. So do you as an insurer want to be successful with data science and machine learning? Then start thinking from the business, look for the most valuable business cases, align these with your strategy and apply the insights step-by-step throughout the value chain. In this way, you guarantee long-term success and short-term results