Don’t let data inconsistency exacerbate a catastrophic event
RMS’ Cihan Biyikoglu highlights how integrated data system designs can help avoid inconsistency issues…
Across every enterprise, we have more data and apps at our fingertips today than ever before. We all deal with multiple systems across departments to execute and optimise critical risk decisions. Each decision centre uses systems built by in-house teams or vendors, all creating and storing their own version of data, and then, as integration teams move in, each system copies data from each other. What’s wrong with this picture?
Data inconsistency issues – which are not exclusive to risk management – can quickly snowball into bigger problems from missed opportunities to costly financial mistakes. An IBM study stated data quality issues cost the US economy $3trn. The industry can avoid these mistakes with integrated data system designs.
For an insurer or reinsurer, risk trading decisions are complex as teams collaborate across underwriting, exposure management, actuarial, finance and other departments. Each discipline also has its own systems which optimise part of the risk puzzle. Each system is built for a purpose, but none is designed to host data from other systems.
Some systems create new data, others compile new insights from existing data. However, they are all siloed systems. These systems require copies of your data: your portfolio, accounts, policies, treaties and more. Each system then makes its own edits, iterating on its own snapshot.
“Data inconsistency issues – which are not exclusive to risk management – can quickly snowball into bigger problems from missed opportunities to costly financial mistakes”
After a few cycles the data starts to drift and fork away. Each system has an incomplete view, each copy gets out of date and inconsistent. No single copy is your complete “golden” data or a single version of truth.
Why does this matter? Let’s go back a year to September 2021 and Category 4 Hurricane Ida is unfolding. The clock ticks as your business attempts to understand potential event losses. Teams try to set underwriting moratoriums. Risk analysts scramble to find and implement the latest event tracks and shapefiles to understand portfolio losses for various business lines. And your claims teams are figuring out loss adjuster allocation. Your CEO is also expected to report on losses to shareholders and the board.
But both the cat modelling and exposure management systems report concerningly different loss expectations. Both systems use copies of the same portfolios – copied at different times between various systems, with different exposures and policies. And with multiple edits across systems, they have experienced significant information drift.
Meanwhile, the hurricane gets closer, changing direction from the initial tracks and the pressure for accuracy is high.
To help resolve the issues of siloed risk systems, the RMS Intelligent Risk Platform unites all teams from exposure managers, underwriters and treaty managers with a unified data store with a shared copy of your data: your portfolio, account information, policies, treaties and more.
Importing a new account snapshot into RMS Risk Modeler enables data to be immediately available via our ExposureIQ and UnderwriteIQ applications to get answers to your questions. The shared data model enables these applications to speak the same language, which can be extended to other in-house and third-party applications to store portfolios and accounts of exposures, policies and treaties.
Learn more about the Intelligent Risk Platform and IQ applications that run on our platform on our website.
Cihan Biyikoglu is an Executive Vice President at RMS