Deep Dive on 3 Areas of Data and Analytics
1. Data Ingestion: Optimizing Data Flows at the Source
One Insurtech executive has estimated that, alarmingly, some underwriters and actuaries can spend more than two-thirds of their time doing basic transformation and cleansing before they can use the data to make decisions. Differing standards in terms of the format, quantity, and quality of data in cedent submissions mean that vast amounts of manual work are required to bring the data into systems.
Additionally, much of the data is either “lost” and unusable, stuck on PDFs or huge spreadsheets with no efficient process to consolidate it into data systems. This leads to inconsistencies across the business, as individual teams use the raw data differently for their own processes — cleansing and standardizing the same data multiple times. The ability to capture and structure data accurately and efficiently at source will not only direct time that would otherwise be wasted towards value-add activities, but it is a pre-requisite for more advanced analytics. Best-in-class reinsurers invest significantly in developing a strong data culture, processes and partnerships to maximize the quality and scope of their data capture.
2. Systems and Methods: Integrating Systems for Effective Underwriting
Multiple disconnected systems are the norm across reinsurers. Often resulting from rapid growth or acquisition, these inefficient and cumbersome systems mean that data is typically scattered across the business. Individual teams create their own tools in Excel to store and analyze data which they then need to manually update. A lack of co-ordination between these teams gives rise to inefficiencies and inconsistencies across the business in addition to the risk that, without a central data repository and central control, the knowledge is lost when key personnel leave the company.
For reinsurers, there are two options for having an integrated pricing system: build or buy. Only the very largest reinsurers have the budget and scale of developer teams to build and maintain a pricing system in-house. For most reinsurers, the right option is to license integrated pricing systems off-the-shelf.
3. Advanced Analytics: Leveraging Data to Improve Risk Understanding
Once an efficient ingestion method and central system has been established with more granular data at their fingertips, reinsurers can conduct more sophisticated analyses to enhance their decision making. This includes sensitivity testing of parameters, portfolio optimization or marginal impact analysis on treaty deals. Most reinsurers can only perform a basic version of these portfolio analyses at a high level, months after a renewal period has concluded.
Sourcing and integrating third-party data — such as for example industry-specific inflation data — can also enrich the underwriter’s knowledge to enhance risk selection and better manage market cycles. Most reinsurers take a view on the current trends in the market to build into their view of risk via ad-hoc research projects. However, digitizing and centralizing analysis of market indicators using third-party data sources (both publicly available and licensed) would allow reinsurers to take a proactive approach to market cycle trends. This would enable reinsurers who do this effectively to react faster than their peers to market movements.
