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When a catastrophic event such as a hurricane or an earthquake strikes, an insurance business relies on the exposure management team to answer the big questions: What level of loss is the business looking at, how much will be recovered from our reinsurance, and how do we communicate this?

In a recent blog for insurers, I looked at the importance of real-time event response and exposure management; in this blog, I will focus on reinsurance and the need to generate net loss figures. For most reinsurers, answering these questions requires collecting and analyzing data from a wide range of tools, data sources, and systems.

The data volumes are significant, spanning hundreds or even thousands of client exposure databases, each with multiple treaty layers on top. To address this challenge, many reinsurers have created homegrown data warehouses that summarize their data across all cedants.

The original exposure data may be rich in detail but may need to be preaggregated to a specific level, such as at the county level, to handle the data volumes. However, when an event occurs, using preaggregated data is inevitably going to limit the accuracy of the analysis. A county-level or even CRESTA-level analysis may be far too broad given the granularity of the event footprints and the sensitivity to the specific locations impacted.

Reinsurers also have the additional challenge of ensuring they correctly calculate the losses to the treaty layers they are participating in. To do this, they need a financial engine capable of taking the underlying client losses and then applying their layers, along with any subconditions or restrictions given that the treaty may not cover the entirety of the underlying portfolio.

All these tasks are time-consuming. The longer it takes to get a loss estimate, the longer the business is deprived of crucial loss guidance when they need it most. And where inaccuracies creep in, it can lead to unexpected claims and can impact how the business may deploy its capital.

Getting to a Net of Reinsurance Loss

A gross loss estimate takes a lot of work, but it is not the end of the story. Once a gross loss estimate is established, exposure management teams really need to generate a loss estimate that is net of any outward reinsurance recovery. For the business, this net number is key, as clearly once the event unfolds it is the number that will be recorded in the profit and loss at the end of the year.

Accelerating insights to get a gross loss estimate is an essential part of Moody's RMS ExposureIQ™ exposure management application, and so is helping to establish the net of reinsurance position. Depending on the reinsurance structures in place, a situation could occur where there is a large variance in the potential gross loss estimates, but due to the outward reinsurance structures these “net down” to a similar position.

For example, if gross loss estimates for an event vary between US$100 million and US$350 million but the net losses will be a maximum of US$150 million, the market will be reassured to understand that net position. Still more reassuring is understanding that even if the gross loss were to escalate to US$500 million, the net loss would still remain at US$150 million, based on the reinsurance protections in place. Therefore, establishing the net of reinsurance loss is vital, as it reduces variance in loss estimates and demonstrates how the business has actively managed and prepared for this type of event.

But again, getting to this net of reinsurance number can be extremely difficult due to the multiple structures and entities that are protected by each reinsurance policy from the outward program, as well as the complex financial terms used within these reinsurance programs. For many (re)insurers, their exposure management system does not capture their full outward reinsurance structure, especially with regard to reinsurance purchased at the group level that impacts many entities within the organization.

Often, the full details of (re)insurers’ outward reinsurance structures might only exist in their capital model, a homegrown tool, or even in a spreadsheet. And in order to net down their loss estimates, they must pull the gross loss numbers from their exposure management system or catastrophe risk model, then put that into yet another system to manually net these down. For some organizations, they even have their outward programs defined in slightly different ways in different applications, meaning it’s very hard to get consistency across the organization.

The ExposureIQ application looks to solve this complexity. Organization-wide reinsurance structures and their impact on net losses are all managed within the ExposureIQ application and are applied when the losses from an event are calculated. This makes it easy for the organization to view the net losses, even drilling down to see where losses are driven within the organization, before reconsidering when extra capital or reinsurance is needed.

ExposureIQ Application: End-to-End Exposure Management

When Moody's RMS set out to build the ExposureIQ exposure management application, we wanted to streamline into a single solution all the processes that are managed across multiple applications. The goal was to simplify data collection, management, and analysis to quickly establish and understand net losses.

Our clients are moving forward with the ExposureIQ application that benefits from the cloud-native Moody's RMS Intelligent Risk Platform. When a catastrophe looms, Moody's RMS Event Response teams start to flow event footprints – and for hurricanes, real-time Moody's RMS HWind forecasts – directly into the ExposureIQ application, ready to run across a client’s exposure.

With the event footprint ready and loaded in the ExposureIQ application, exposure managers can then establish losses across an entire book of business, run analysis across all cedants, or drill down to a specific portfolio – or even a single location. Clients can manage and display exposure accumulation data however the business needs it, all within a rich, geographic interface. All of this is achieved without any manual data management or SQL (structured query language) scripts and uses real-time exposure data.

When building business hierarchies within the ExposureIQ application, clients can also associate the relevant outward reinsurance structures to the applicable business or portfolios. All this reinsurance structure information within the ExposureIQ application enables clients to generate net numbers for each event in the same analysis as the gross numbers. This allows for multiple scenarios to be run, so clients can see them all from a gross and net perspective then quickly establish – and communicate – these positions to the business.

The ExposureIQ application removes the grind of gathering and structuring exposure data across a business. It can switch views to quickly establish gross and net losses, so a (re)insurer can start to make time-sensitive, critical choices with accuracy and informed decision-making.

Find out more about the Moody's RMS ExposureIQ application.

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Luke Norman
Luke Norman
Director, Product Management, RMS

Luke is a Director of Product Management at RMS. He has more than 15 years of experience delivering risk management solutions to both insurance and reinsurance companies. In his role at RMS, Luke is responsible for developing the roadmap for ExposureIQ™, the company’s enterprise-class, cloud-based exposure management application.

Prior to his role at RMS, Luke was Product Manager at AdvantageGo, where he managed the exposure management products Exact and Exact Max. Through this role, he has worked closely with clients across multiple insurance and reinsurance lines of business to understand their exposure management needs and ensure they are met with innovative solutions.

Luke has a bachelor's degree in Mathematics from the University of Nottingham.

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