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The four pillars of a successful exposure monitoring solution

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Richard Archer
6 mins read
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Contents

Summary

  • With an abundance of data comes an equal abundance of opportunity to create a dynamic view of your exposures that combines both the static world of property exposure and other fixed assets with the physical, moving world of vessels, aircraft, cargo and more. 
  • Having sophisticated tracking and interoperable systems is great, but ultimately, it all comes down to ensuring a high level of quality data is being ingested. The more quality data a firm can ingest, the more meaningful insights can be unlocked, as patterns emerge and new metrics can be calculated.
  • The opportunity to leverage new datasets grows larger every day, however it's important to make sure you’re doing it in a way that allows you to ultimately improve the view you have of your risk. 
  • Effective exposure management technology is only as useful as its ability to offer seamless integration with external third-party data providers. This integration augments the core data record of insurers' contracted portfolios and delivers additional data points and insights.
  • To get a solid grasp of your exposure, access to good quality data and an effective form of visualisation for that data is key to both understanding and making better-informed decisions about contracts, premiums and claims.
  • In order to build a successful platform of moving data for your firm, you must consider how you bring your data into your organisation, incorporate the latest data sets, and visualise your data effectively.

On-going global conflicts have created an era of heightened uncertainty. We are seeing an increasing concentration of economic and insured risk in areas that are being affected by more frequent, more severe events. Against this backdrop of increased volatility, exposures continue to shift and transform. However, as this uncertainty has grown, so too has the availability of data, from a world of very little actionable data sources to one of abundance. With this abundance of data comes an equal abundance of opportunity to create a dynamic view of your exposures that combines both the static world of property exposure and other fixed assets with the physical, moving world of vessels, aircraft, cargo and more. 

How can you harness this potential and make sense of the data? And what opportunities await those that can create a holistic view of all the types of insurances within their business? It all starts with how you bring that data in.

 

Data ingestion

Having sophisticated tracking and interoperable systems is great, but ultimately, it all comes down to ensuring a high level of quality data is being ingested. The more quality data a firm can ingest, the more meaningful insights can be unlocked, as patterns emerge and new metrics can be calculated. This means risk professionals aren’t just able to work with new data more quickly, but are also presented with a much larger and richer picture of their overall risk environment. It can make a fundamental difference to underwriting decisions.

This also feeds into the risk selection and pricing perspective, as a robust data ingestion process can potentially open up opportunities to help drive and enable underwriters to think differently about the types of business they’re bringing in, in a more intelligent way. Therefore it is imperative that insurers have sophisticated tools and programs as part of their tech stack, to collect and ingest data at industrial scale.

Alongside data ingestion, as the world of data continues to develop and grow, having a data model that’s extensible and allows for the use of new datasets as they emerge is important to retain a competitive edge.

 

Building an extensible data model

The opportunity to leverage new datasets grows larger every day, however it's important to make sure you’re doing it in a way that allows you to ultimately improve the view you have of your risk. 

For example, Insurwave consistently makes use of different data sources as the platform evolves and grows, most recently migrating to a new vessel tracking system that uses satellite data in addition to our existing terrestrial data feeds to allow us to track our clients assets in more detail. Similarly, last year Moody’s RMS began integrating third party risk models through its Intelligent Risk Platform such as Fathom’s US flood catastrophe model.

The benefits this extensibility brings ensures that organisations stay up-to-date with the latest changes and updates to better inform any shifts in your exposure management strategy. Part of the key to establishing a truly extensible data model is the continued addition of new data sources. So, how does increasing interoperability help build an extensible data model?

 

Interoperability

Effective exposure management technology is only as useful as its ability to offer seamless integration with external third-party data providers. This integration augments the core data record of insurers' contracted portfolios and delivers additional data points and insights. For instance, an expanded dataset might incorporate risk scores tied to specific geographic coordinates or integrate a map layer, providing a quick snapshot on the stability of a particular region. This push and pull from multiple data sources, often referred to as interoperability, is a growing requirement for insurers to help them optimise their portfolios and make better informed decisions.

These decisions can then go beyond just on a functional level affecting risk selection but also on an executive level allowing exposure managers the ability to communicate on-going change at different levels of the organisation, from on the ground monitoring through to executive levels and ultimately, the board, all at a click of a button.

Now you have established the tooling to give your team a cross-class, real-time view of risk, overlaid with third party data sources that you trust. What is missing? Visualising this live view of your portfolio to help you more effectively track your exposure and enable alerts from any movements from within your portfolio.

 

Visualising change

Unfortunately, insurers still spend a lot of the time attempting to extract insights from data lakes within Excel spreadsheets and associated with each individual policy within the underwriting system. Making sense of large volumes of data is essential in today’s conflict-heavy environment. And thankfully, here’s one tool that can help to convey and understand huge sets of data quickly. Enter data visualisation.

To get a solid grasp of your exposure, access to good quality data and an effective form of visualisation for that data is key to both understanding and making better-informed decisions about contracts, premiums and claims. Making use of data visualisation tools such as Insurwave’s risk map helps insurers to create a holistic view of all of the types of insurances you might have within your business, and bringing those together in an integrated way to help you understand the exposure through a different lens.

As an example, effective visualisation has allowed insurers using the Insurwave platform to effectively monitor developing conflicts such as the Israeli–Palestinian conflict and utilise their data to manage their exposures more with a focus on war risk scores and risk management.

 

Building a successful process

In conclusion, amidst the ongoing global conflicts and heightened uncertainty, the insurance industry stands at a pivotal juncture where the abundance of data presents both challenges and opportunities. In order to build a successful exposure monitoring solution your firm, you must consider how you bring your data into your organisation, incorporate the latest data sets, and visualise your data effectively. Fortunately, numerous third-party data providers and management solutions, such as Insurwave, are available to help you achieve this objective.

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