Data analytics has the potential to be the next big thing in reinsurance. The ability to consolidate reinsurance data into one centralized repository and perform business intelligence functions is already significantly improving carriers’ bottom lines.
While sophisticated data analytics tools are available, many insurance executives continue to wait on the sidelines when it comes to making the investment for analysis of their reinsurance data – even with the knowledge that reinsurance recoveries are one of the largest assets on their balance sheet.
The Manual Approach Falls Short
Reinsurance firms and carriers alike have always processed huge quantities of data for administration of their reinsurance book and loss recoveries, as well as for actuarial modeling, trending and general modeling. Analysis has traditionally been performed via add-on tools, spreadsheets or even on paper – this duplication and/or manual approach has often led to errors, inaccuracies and discrepancies.
Data Analytics Software Trumps Expertise
Companies are discovering that not only does data analytics software enable them to collect and analyze data quickly and conveniently to optimize enterprise risk management, but that reinsurance is a big part of managing that risk. It is becoming more evident that no matter how much expertise a human resource may possess, robust data analytic tools can assist in the identification trends and forecasts by providing quicker and more accurate analysis.
Today, many companies still use spreadsheets and/or a multitude of systems to administer their ceded reinsurance. Business partners, reinsurance terms, multiple internal companies and documents may all be housed in separate repositories. The first step in the journey from manual to automated data analytics is to implement a centralized ceded reinsurance system that captures all of the data for the companies/subsidiaries within an organization. This requires building feeds from all of the various primary policy and claims sources into one centralized data repository, enabling you to have a system that can administer all of your reinsurance.
This system will automatically interrogate all policy and claims transactions and perform the automated identification and attachment of reinsurance cessions based on the terms, dates and user-definable criteria defined for reinsurance arrangements.
This automated process allows carriers to bring all of their reinsurance data into one centralized repository. Once this is accomplished, they can handle all types of accounting: reinsurer/broker current accounts, inter-company accounting, reinsurance and general ledger, as well as reporting and analytics.
The Competitive Advantage
Traditionally, data has been viewed as little more than the by-product of doing business, but data analytics, when deployed effectively, can transform an insurer’s data from by-product to asset – offering the ability to make fast, accurate decisions and enable change quickly in a constantly evolving market. With data analytics, firms have the opportunity to make data a competitive advantage. Utilizing data and analytics tools to determine and monitor key performance indicators (KPIs) help insurers plan most effectively for future reinsurance coverage. Loss development forecasting, profitability, risk and claims profiles and reinsurer exposure all contribute to these decisions.
Few software systems can handle the complex interrogation of primary data and automatically allocate to reinsurance arrangements, such as multi-layered programs, inuring programs and aggregates– just to name a few. Companies that cannot access all of the relevant data cannot automatically perform data analysis, so choosing the right system is paramount.
Enhanced Service and Faster Recoveries
Insurers are constantly being asked by their reinsurers to provide more underwriting and business results based on captured data insurers. Insurers must be able to compile the relevant and accurate information, slice-and-dice it and present it to their customers, the reinsurers and brokers. Several departments, along with management, can use this data to collaborate more efficiently.
Analytics software eliminates the need for extensive manual analysis, freeing up skilled analysts to use and present that information to the reinsurers and brokers. It is important for a system to be easy to use and intuitive, allowing for quick responses to business needs.
Insurers that can identify emerging trends and act upon them before their competitors will be able to refine their risk models and underwriting practices, and enhance service
Due to the transformative potential of data analytics, reinsurance providers have begun employing Chief Data Officers (CDOs) to find ways of extracting valuable insights from new forms of digital information and putting them to practical use.
Updating systems and processes and being able to utilize all the reinsurance data is transforming the way insurers are managing and buying reinsurance. The ability to not only analyze the past and present, but also identify future trends, is a tremendous benefit. Many insurers are losing significant revenues by hesitating to invest in the proper systems and tools to make this transformation a reality.