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Summary
- The rapid escalation in the volume and quality of exposure data available on a global scale has led to high demand for powerful, effective exposure management technology that can track how insurers’ exposures are changing on a daily or hourly basis.
- Adding the latest third-party data to the mix on top of your live contracted portfolio can then allow you to react proactively to developments from external events such as CAT risks or escalating instability in an airport or conflict zone.
- Much like exposure monitoring, the ability to not only ingest data but pull out pertinent insights quickly and at scale in a format accessible to a wide range of stakeholders is an important tool for risk management teams.
- Technology like artificial intelligence offers the opportunity to improve not only the speed at which information is ingested but the insights that can be generated from it, through advanced visualisation to help improve underwriter’s speed and quality of decision making.
- Alongside AI and other technologies, predictive analytics has now emerged, playing a critical role in both claims processing and underwriting.
- With the rise in predictive analytics, the common issue of Black Swan events, described as such due to their unpredictable frequency, like the recent geopolitical and natural catastrophes taking place, can now be better understood, anticipated and contained with applied risk management.
Historically, one of the big challenges for insurers is how to accurately track and monitor their moving assets. It’s no longer enough to just be aware of the location of an asset. And recent geopolitical events have challenged many insurers to prove they have the confidence to provide accurate and detailed insights into the impact of an event. However, many of the systems that insurers have in place to monitor and manage this exposure are out of date and unable to deliver the level of accuracy required.
Technology platforms that allow real-time tracking of exposures, quick access to granular insights and the ability to overlay third-party data are well-placed to help you better understand your exposures, write better business and fill that knowledge gap.
A real-time perspective
The rapid escalation in the volume and quality of exposure data available on a global scale has led to high demand for powerful, effective exposure management technology that can track how insurers’ exposures are changing on a daily or hourly basis.
Many technology platforms are now available that can help you combine the latest asset tracking information with data directly from your portfolio, ensuring that you can report on your underwriting decisions with confidence, backed by detailed data points.
There are always new sources of data you can leverage to understand or get a different insight or perspective on what’s happening. Adding the latest third-party data to the mix on top of your live contracted portfolio can then allow you to react proactively to developments from external events such as CAT risks or escalating instability in an airport or conflict zone.
While it could be said that an insurance company would have the expertise available internally to be aware of and react to a geopolitical event promptly, having that additional data available at your fingertips to provide additional options and insight to inform how an insurer’s response is invaluable.
“Being able to understand your exposure in real-time when an event does occur and ensure you are better informed and confident that you know where things are when things happen is a very powerful step change for insurers,” explained Richard Archer, Chief Strategy Officer at Insurwave.
Speedy insights
Much like exposure monitoring, the ability to not only ingest data but pull out pertinent insights quickly and at scale in a format accessible to a wide range of stakeholders is an important tool for risk management teams.
Data capture across many insurance firms has traditionally involved a lot of manual labour through the repetitive rekeying of lots of data. As a result, the process is often outsourced to third party providers which slows the process down even further, with SLAs ranging from 1 to 5 days for the return of a single submission.
Human errors are frequent, and insurers do not have the resources available to ensure consistent quality across data sets prior to quoting and binding policies. With limited access to real-time insight, correlation to loss is less transparent and correct interpretation is not guaranteed.
Thankfully, technology like artificial intelligence offers the opportunity to improve not only the speed at which information is ingested but the insights that can be generated from it, through advanced visualisation to help improve underwriter’s speed and quality of decision making.
During an interview with InsureTV, Chris Weller, Head of Exposure Management at Inigo Insurance weighed up the benefits of the technology. “There is a lot of negativity that comes with the association with AI, but in my perspective I can’t see how it can’t be useful to help in that world [...] being able to analyse information quickly. But there is always going to be an element of reviewing that information which is where a human touch comes in and using your own underwriting teams and subject matter expertise internally, so I would say it’s a constructive tool rather than a replacement.”
A predictive future
Alongside AI and other technologies, predictive analytics has now emerged, playing a critical role in both claims processing and underwriting. Through its use of historical data and real-time data to predict future events, outcomes and to help inform decision-making, predictive analytics is often cited as a promising area from an exposure monitoring perspective.
“There are patterns out there [...] how can we use them and link it into helping clients better understand their own risks or risks they haven’t anticipated yet [...] there is a lot more to do to utilise it and harness its power as an industry,” Weller told Insure TV.
In addition to helping their clients, insurers can also benefit from interrogating this historical view of their data to identify patterns. “What are the patterns in the data? And what might that mean for an insurer's appetite for how they look at risk and support their clients?” Richard added. For example, in the risk assessment process, predictive analytics can help brokers assess risk with greater accuracy through analysis of various claims data analysis points.
With the rise in predictive analytics, the common issue of Black Swan events, described as such due to their unpredictable frequency, like the recent geopolitical and natural catastrophes taking place, can now be better understood, anticipated and contained with applied risk management. As a result, the term has shifted colours to a new term: Grey Swan events. However, as technology providers help insurers build on their data quality to write better business and ultimately respond more quickly with the help of real-time insights, we may see another colour change in the not-too-far flung future.
Seeing is believing
By using technology to combine the latest asset tracking information with data from your portfolio, insurers now have the opportunity to improve the speed and effectiveness of their underwriting decisions and how they report on them through the ability to access all of their portfolio data in one place.
If you want to understand your exposures in more detail, Insurwave can offer you a unified view of your portfolio with real-time tracking and detailed data points you can share with your stakeholders across the insurance value chain. Getting started and adopting an iterative approach versus sweeping changes is key.