ANALYSIS: COMMERCIAL INSURANCE actively monitored by intelligent systems that alert underwriters or risk managers to changes in peak exposure, compliance, and even pre-claim detection. Predictive analytics also delivers real value to customers by providing tangible insights into risk which can be proactively managed. This is a win-win situation for commercial insurers and their customers.
The global macro environment has become increasingly interconnected, volatile, uncertain
Asia leads the charge to digitalised insurance industry
Its less mature commercial insurance market is actually an asset, Concirrus’ Client Development Director for Asia reveals.
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he commercial insurance industry has been operating at 20% to 30% loss for some time now. This is becoming the norm, especially in Asia, where losses are incurred because of the climate-related natural disasters that most often hit the region. S&P Global Ratings, for instance, mentioned the wildfires in Australia, destructive and costly typhoons in Japan and the Philippines, and last year’s devastating flooding in Henan, China that cost the industry more than $2b in losses. Despite this, Concirrus’ Client Development Director for Asia, Oliver Miloschewsky, still expressed his belief that the region will revolutionise the commercial insurance industry. Here is his exclusive interview with Hong Kong Business where he discussed how Asia’s digitalisation trend will further push the growth of the industry. 34
HONG KONG BUSINESS | Q1 2022
Digitalisation directly addresses key challenges in commercial insurance, namely operational efficiency and sustainable profitability
How will digitalisation solve the problems the commercial insurance industry is facing now? In order to derive real value out of data, organisations need a digital environment that deploys all the data and analytics in a consumable and user-friendly way. Digitalisation significantly reduces operational costs and, at the same time, lays the foundation to enable powerful analytics to unlock meaningful insights to drive faster decision making with more accuracy. Predictive analytics is the most exciting and arguably the most significant step. Underwriting teams can then develop new coverage types, price them using the latest available data, and rate them in a digital system that delivers real-time visibility of changes associated with the risks. Once bound, individual risks and indeed the entire portfolios can be
What are the strategic advantages of having a data-driven model in the commercial insurance industry? All insurers have historical data within their existing portfolio; however, they are not necessarily resourced to take full advantage of this data, which can be limiting when looking to grow or expand into new areas of risk. Historical data of individual companies will also have an inevitable bias to risks written in the past and often significant blind spots regarding segments or geographies not previously serviced. This is where the third-party data and analytics providers can play a crucial role, not only in making a company’s own data accessible in a cleansed and meaningful format but also to provide access to broader market models that provide a much more accurate and holistic view of risks. This directly informs underwriting strategy and risk appetite which can be adjusted almost in real-time. For the underwriter, it is important to receive submissions that are prioritised based on their appetite and targeted market segment. The immediate and long-term benefit is a much more productive use of time, as insurers are able to focus on the most relevant risks and make much better-informed underwriting decisions, resulting in a more balanced and profitable portfolio. What digitalisation trends do you see affect Asia’s commercial industry? What is different in some Asian countries’ digitalisation trends is the strategic mindset and
