Insurers must unlock the value of data analytics
Data analytics has revolutionised and improved many insurance processes. We spoke to Munich Re’s Dr Tobias Farny to understand how insurers can leverage data to boost efficiency and accuracy.
By Jimmy John
With advanced analytics incorporated into claims management processes, insurers can deliver high-value and comprehensive analysis of portfolios that can boost accuracy and efficiency across business critical functions.
Some motor insurers in Asia have already begun to digitalise and automate claims process based on AI for images, text and structure data. “When proper data-driven tools are in place, insurers can also improve overall business performance and minimise costs across the entire value chain,” said Munich Re Asia Pacific – Greater China and Australia, New Zealand CEO Tobias Farny.
“For the clients it means faster and more reliable claims settlement,” he said.
Solutions for reinsurers
The ability to collect, analyse and draw actionable insights from data is beneficial as it allows insurers to implement suitable claims analytics tools in place to control costs. “However, tools like advance fraud detection for example, require a strong foundation of quality data in order to be optimised,” said Dr Farny. He mentioned that since many primary insurers have not yet fully embraced the importance of having quality data, it is essential that reinsurers offer plausibility checks and data cleansing in order to improve the quality of existing data and refine data fields.
Notably, insurance analy tic s platforms operated by the more advanced players in the industry can enable insurers to collate their data with sector-specific external data. “This utilises greater and more relevant data volumes, which offer the basis for enhanced portfolio management and smarter decision making – from distribution and pricing to claims handling,” he said.
“We provide advice to AI providers in designing their performance guarantees, relieve them of significant balance-sheet risks and, thus make them more attractive to investors and their clients at the same time,” said Dr Farny.
Another example, he said, is the availability of global data, enabling local insurers to gain access to benchmarking, helping them to identify potential areas of strength and weakness.
Value of data analytics
Dr Farny believes that in order to unlock the value of data and digitalisation, it is critical for insurers to recognise that the competitive advantage will go to those who are able to leverage the power of big data and analytics – whether to identify early signals and emerging risks and opportunities, to increase customer value through better insights into their behaviour, or to make business operations more efficient.
“However, while most insurers are increasingly seeing the benefits of harnessing data analytics and have begun to perform data hunting and analytics in house, small and mediumsize companies are more likely to continue to face limitations associated due to cost and lack of infrastructure,” he said.
Insurers can consider partnering with other players to promote innovation, knowledge-sharing and faster implementation of data-driven solutions, skillsets and IT infrastructure without losing control of costs. “We adopt a relationship-based approach and work closely with insurers as we believe that such long-term partnership not only provides greater integration, but it allows primary insurers to take advantage of the full breadth and depth of our offerings,” he said.
The pandemic has accelerated digitalisation in the public and private sectors. Looking ahead, he expects further and faster investments in the digitalisation of most primary insurance business models especially with higher cost pressure to automate processes. Insurers, he feels will also increasingly embrace machine learning on existing data to optimise pricing and distribution and address individual demands for more usagebased products.
“AI will play a role in structuring data from images and text and therefore set the foundation for smarter and more automated decisions in underwriting and claims,” he said.
As the industry continues to digitalise and become even more data-driven, new risks will emerge, such as the risk of using a new technology like AI itself. “Insurers must not only navigate this dynamic risk landscape and re-assess and implement current data protection and local regulation requirements but continue to provide the best solutions for insurance clients,” he said.