In recent times, we have witnessed the insurance industry getting repeatedly redefined by ever-changing client demands based on unprecedented uncertainties. With every new product launched by insurers, the need for a holistic exposure management plan only heightens further.
The Covid-19 pandemic related losses to the insurance sector has highlighted the need for a more analytical perspective and a personalized approach to risk mitigation when it comes to exposure management, a task that requires that middle managers perform a daily assessment of the insurer’s risk management plan.
Lloyd’s said that Covid-19 pay-outs would eventually be on par with 9/11, which cost the insurance industry over $47Bn. With enterprises still reeling from the economic fallout of the pandemic, it becomes imperative that insurers focus more on controlling risk exposures in the underwriting process.
The larger goal of risk and exposure management is to guarantee, as much as possible, that losses are accidental, through a robust set of systems and processes to record, monitor and assess the underwriting process. Given this scenario, exposure management needs to evolve in parallel with the customer demands of insurance products.
Over the past few years, exposure management as a discipline faster has evolved faster than ever in the history of organized insurance. Having emerged out of the catastrophe modelling paradigm that prevailed in the early 1990s following Hurricane Andrew, today we appear to be set to go beyond modelling providers AIR and RMS into open source options.
Historically, controlling or managing exposure in the industry across different business lines was achieved through separate technology-based platforms like the above. Many of these systems did not boast interoperability, which resulted in carriers never really getting the full picture of their exposure landscape. They were, in all probability, flying blind, leaving them exposed to potential losses and / or missed market opportunities.
However, things changed drastically post 9/11 and hurricane Katrina in the United States as the unidimensional approach to assessing risk was re-examined to explore how loss potentials could be ascertained better. This was a major step up from the then prevailing practice of excessive reliance on seemingly precise numbers generated by models while underwriting.
These events strengthened the belief that portfolio managed requires knowledge of risks distribution and accumulation at a granular level to manage both opportunity and risks across geographies and industry verticals. Given the direct correlation of exposure management to profitability, identifying regions and perils to growth allows insurance companies to optimize portfolio performance under different strategies.
There are innumerable examples of how the gaps in exposure management led companies to an incomplete view of the risk that eventually resulted in grave losses. One ready example that comes to mind is how insurance firms underwrote hospitality properties in New Orleans, classifying them as large hotels on solid ground, only to realize they were floating casinos that blew away when hurricane Katrina crashed into the city in August 2005.
Post 9/11, while the industry became aware that cat-models only helped understand uncertainties, these were but one piece of a growing puzzle, the casino instance demonstrated how the models were only as effective as the quality of data that went in. Both these events cause a significant rethink on exposure management.
Today we see a significant drive to include many more dimensions while considering the exposure of a book of business. Assessing accumulations, data quality and risk clash potential around risk-prone areas such as earthquake zones or considering market fluctuations around political uncertainties have become major factors today.
As a result, the complexities resulting from multiple lines of business and associated re-insurance, the challenge to map day-to-day underwriting decisions to the risk appetite is becoming an increasing challenge. Software today allows carriers to manage a broad range of exposures against perils or lines of business such as pandemics, trade credit, besides political risk and those posed by climate change patterns.
Cutting-edge risk analytics software today helps insurers place all risk in a single location through a combination of seamless integration with existing process workflows via APIs and are also supported by enterprise-grade admin and self-service reporting capabilities. This allows users to configure the solution to meet their requirements. They are capable of handling data associated with everything from pandemic coverage to underwriting to political risks to underwriting credit risk exposure.
The one area requiring maximum focus remains the exposure to climate change risks. Earlier this month, the Central Bank of Ireland launched a consultation paper on guidance for insurance and re-insurance undertakings on climate change risk. The Bank said its purpose was to define necessary action in the wake of the increasing severity and instances weather-related events connected to climate change and its global impact, a rise in insurance claims linked to such events, and the need for re-insurers to transition away from greenhouse gas activities.
Given the spate of innovations in insurance products, specialized exposure management needs to remain in focus. Data and analytics need to delve across a range of businesses, systems and cultures to be able to add real value across the insurer.
