Approximately 3 minutes reading time
For insurers, good data management is essential for success, and perhaps even crucial if they want to survive in today's data-driven economy. A lot of insurers, however, still struggle to make effective use of their data. That is hardly surprising considering the large number of mergers and acquisitions in recent years, not to mention the increasing complexity of IT landscapes and the explosive growth of data in general.
Complex IT landscape
Data is often not stored centrally, or is collected in a variety of back-office systems. Nobody has a complete overview or really knows what was actually buried away in all the different systems. KPMG put it this way: “IT infrastructures have evolved to become a complex collection of systems that hardly support processes, let alone satisfy the need for data and information. This is one of the main reasons why a lot organisations are afraid to take dependable decisions.”
Quick wins often backfire
Although data management applications have been introduced to overcome these IT challenges, the practical impact has been rather limited. As KPMG put it: “These applications were often just a one-off 'retro fix’ and not a future-proof solution.” The creation and maintenance of high-quality data takes more than just a few updates and patches. If the foundation isn't solid, then the rest will soon start to crumble.
Successful data management is difficult and perhaps even a little boring. It is much more fun to dream about the future than to tackle difficult (and sometimes obscure) practical realities. Research shows, for example, that approximately 80% of organisational data is stored in different systems and in different ways. Even though this data an essential source for all types of management information (such as underwriting, pricing, and claims handling), there is often minimal control over all this information. The structuring of data and the central organisation and orchestration of core insurance processes is a challenge facing all insurers.
Integrated approach to data
In today’s data-driven economy, it is important for insurers to have effective control over their data. The hunger for more data is enormous, for example to find out more about customers or to identify who the UBO is, or to run background checks on PEP lists and sanction lists. Badly organised data leads to poor decision-making, which might not only have an adverse effect on compliance and control, but also on pricing and underwriting. Luckily there is a solution that makes it possible to keep this huge “data monster" under control. The Digital Insurance Platform of CCS delivers a uniform and fully integrated presentation of data. We do this by putting all the data from all the different sources into a uniform data structure, and then map out all the business applications and external sources. In this way you can create ‘a single version of the truth’. Outdated systems are transformed into modern ‘data mines’. Unstructured data is structured to provide clear and comprehensive insight, including audit trails for all transactions. Whether it involves price quotations, renewals, or claims.
Consistency of data management
You can add various data sources to our Digital Insurance Platform (for UBO verification, PEP and fraud checks, etc.). Most importantly, though, you need to understand your existing data first. We use the data language ACORD for this. This makes rapid, accurate data exchange and more efficient workflows possible through the development of industry standards and standardised forms.
Our Digital Insurance Platform ensures good data quality and successful data integration. The platform uses an industry standard ACORD data model, which significantly enhances the quality and uniformity of your data. This is crucial for strategic decision-making, the acceleration of the time-to-market, and the improvement of your customer satisfaction. Ultimately, the Digital Insurance Platform will enable you to improve the quality of your data, which is essential if you want to survive in today's data-driven economy.