How can the insurance market capitalise on the benefits of Big Data to enhance profitability and reduce loss ratios? Read on to learn more.
The glory days of large-scale growth and profitability within the London insurance market no longer exist. The market has been stuck in a period of high catastrophe losses combined with inadequate premium rates. Underwriting loss ratios are the defining measure of success in insurance. Whilst it is primarily assessed through internal metrics, it’s essential to acknowledge that it is a moving target. Loss ratios are evidently a result of account performance and retention, however account performance stems from access to strong business. Business is delivered to Underwriters through Brokers. As an Underwriter, it is necessary to create long standing relationships with Brokers to be in contention for the best business.
We recently discussed how the London market is one of the last relationship-led markets still standing. With current pressures on such a market, innovation is focussed on empowering a new generation of underwriters. Digging deeper into the topic, we can better understand how technology is not only improving operational processes that translate to improved metrics, but also the alignment of data pipelines for shared insight and improved business relationships.
Over the years we have seen numerous examples of technology improving book health. One example is how RMS changed the way in which syndicates modelled their exposure across the globe. By providing an independent reference for static exposure, insurers could set more credible premiums. Today, RDS reports generated by RMS are shaping the way information is fed back to Lloyd’s.
The Insurtech sector offers the best view of how the market continues to innovate and solve complex problems. Its acceleration is attributed to the need for a digital-led way of working that provides both operational efficiencies and more stable loss ratio’s. With current market pressures, Underwriters need a better view of risk alongside a reduction in manual processes. Increasing capability whilst streamlining workflows will ensure a new generation of Underwriters can thrive within the London market.
Given the multitude of factors involved in overall book health from an operational perspective, a collaborative approach to development with in-depth market consultation is the only way to ensure success. Success in this case is defined as stabilising performance whilst improving business relationships.
In a regulated market, a black box approach to data interpretation is not sustainable, the market must work with InsurTech to thrive. Concirrus’ approach to the application of machine learning remains transparent. We analyse verified datasets, apply proprietary algorithms and provide accurate insight that aids decision making. The interpretation of data is shown through simple modules, allowing a decision maker to fully understand the most influential factors relating to a specific result.
Such a tool changes the view of risk during the lifetime of the policy, utilising real-time data to gain an on-going view of risk. Intervention methods can be introduced depending on the relative behaviour of the Insured. This can lead to policy changes, behaviour changes and premium changes, which mitigate risk, improve Insured compliance and keep the level of premium relative to risk as it arises.
Pricing also becomes more accurate through new predictive capabilities. By understanding the severity and frequency of claims within an account, an expected loss can be generated with a risk score. This helps identify the overall likelihood of a claim, as well as what premium you should set relative to the expected loss.
Improving risk management and pricing capabilities directly affects the overall profitability of a portfolio. Mitigating claims, improving pricing and maintaining premium percentage relative to exposure allows for the maximum value of the accounts held to be realised.
Digital platforms are aligning teams within Insurance organisations which were originally fragmented. Teams that see the same information daily can therefore make more informed decisions by utilising their colleagues’ expertise. Underwriting teams can apply insight from Sanctions, Claims and exposure management into their processes as they are more aware of their relative impact. The work of the claims team specifically becomes more visible to Underwriters. Underwriters can therefore see the true extent of their portfolio, whilst the claims team can view the portfolio and claims in detail when required.
The ability to see behavioural factors as well as static data enables the Exposure Management team to better understand the risk written by the underwriting team. The true extent of a book of business can therefore be reported and modelled accurately in order to highlight under performance and prospect accounts that can generate profit.
Network and Net Worth
Data science and automation reduces the need for remedial tasks, meaning (re)insurers and brokers that embrace technology become more effective at writing/placing business. In doing so, they are also more aware of the relative impact of risk on the organisation, improving internal workflows. Operational benefits also extend to the assured, offering additional value to working with those who have embraced innovation.
Data underpins all operations within an insurance organisation, and the further alignment of data amongst industry partners will become apparent in future business. The vertical integration of data will mean all stakeholders will have a shared view of risk, which is previously unheard of. Underwriters will know that Brokers will have an idea about the relative value of an account ahead of negotiation. Brokers will know that Underwriters will have a comprehensive understanding of the risk, with a clear guide on whether it should be written ahead of negotiation. With a shared view, partners throughout the value chain can ensure they’re focused on a shared goal. The improved performance on one party can drive improved performance for another, such as insurance to reinsurance.
It’s clear that any approach needs to be holistic, harnessing data to improve operational performance, organisational alignment and partner relationships.
Learn more about the new capabilities available to the industry through InsurTech here