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Insurance Solutions

Formerly Moody’s RMS

Residential and small commercial market insurers are facing continued pricing and coverage challenges.

First, consumer demand for properties located in traditionally higher-risk areas has continued to rise, and with a changing risk landscape, inflation, and other factors, losses in these locations have also increased significantly.

Second, the rise of on-demand, Internet-driven services with easy-to-use comparison sites, instant access to media sources, and same-day goods delivery, has seen consumer expectations changing significantly – especially around speed.

Buying insurance is certainly not immune from this shift in consumer habits.

Waiting days, hours, or even minutes for a quote is no longer acceptable for consumers.

If other insurers and service providers can provide almost instant service and can quote and bind policies quickly, they are now more likely to win business over those who cannot.

So, how can insurers and consumers both find value in these difficult conditions?

Balancing the need to accurately quantify risk with the consumer’s demand for quotation speed presents a problem for residential and small commercial insurers.

Quantifying Risk at Speed

To help insurers understand the risks associated with a given location and to price accordingly, insurers increasingly rely on third-party data delivered at the point of underwriting.

However, this need to fulfill consumer demand for quick decisions and competitive pricing is often hampered by the tools primary insurers currently have at their disposal to make an informed decision.

Third-party data delivery methods greatly vary in terms of speed.

Depending on an insurer’s requirements, data delivery currently ranges from a basic flat file manually implemented into an insurer’s own systems to complement their existing data, to cloud-based databases delivering data directly into a proprietary platform via an API, with regularly updated information across a wide range of perils.

There are barriers in the way. Manual cross-referencing of multiple different systems will add time to the quote process.

For example, an underwriter may need to cross-reference different IT systems when using third-party risk data, as multiple vendors supply data for different perils.

There may also be a requirement for insurers to manually check an address using the Internet to cross-reference similar properties in an area or check for any held claims data to get a better understanding of the property. All these actions again add time to the quote delivery process.  

Even if a data delivery method is quick, speed brings its own risks when delivering quotes as quickly as possible to customers.

Leveraging inaccurate, incomplete, or redundant data when deciding to accept a policy can have significant implications on profitability later in the insurance lifecycle when seeking reinsurance.

Fast but inaccurate decisions could lead to very costly poor underwriting which will not be sustainable especially when a catastrophe strikes.

So, speed must also be balanced against the need for accuracy. Insurers must have confidence in the analytics they are using to make these split-second decisions on pricing, to operate at the speed their customers increasingly demand.

Moody’s RMS® Location Intelligence solution combines our strength in catastrophe modeling and with the latest technology, to deliver risk data into the heart of an underwriting system.

Location Intelligence helps insurers address the challenges of combining speed and confidence.

Underwriters can trust they are getting a much clearer risk picture as the same science and data from our world-renowned risk models are delivered in real-time and seamless API integration – with sub-second responses.

The solution helps in a variety of ways, including:

Better Risk Insights with Superior Data Quality and Resolution

The chance of an insurer truly understanding the potential exposure when quoting on a property is limited if they rely on partial data.

For example, insurers using postcode-level data would fail to appreciate that there could be a variety of building types each with a unique set of attributes in that location.

With a higher level of data granularity, insurers can make better decisions at the point of quote, avoiding costly mistakes in the event of a claim.

Underwriters also have the confidence that any quote offered to a customer is based on the risk specific to their property and based on the same science and data used during reinsurance purchasing later in the insurance cycle. 

For insurers to validate data quality from different sources, including geocoding and valuation, can also take up significant time and cost.

However, with Location Intelligence data delivered via the API, insurers can utilize a comprehensive view of Moody's RMS data layers, including average annual loss (AAL), return period, scoring, and property data.

Real-time Response

As previously mentioned, a quick reaction to a quote request is essential to win business as consumer demands have changed.

Therefore, from the moment a quote request lands on an underwriter’s workbench, they need to have access to the right data to quickly make informed decisions.

With sub-one-second latency, the Location Intelligence solution delivers high-quality analytics at the speed of business.

Combining speed with Moody’s RMS-derived risk insights into pricing and risk selection systems means underwriters can now work both fast and with confidence. 

Ease of Use

To underwrite business, many insurers currently rely on legacy systems with technology investment largely spent on maintaining quote capacity.

Implementing major technology changes can be viewed as a huge logistical and financial challenge, but with the power of cloud-native technology, a single API can deliver all risk insights without the need to rearchitect processes.

This means insurers can drive revenue growth with a solution that offers unlimited processing power to help expand a book of business and have confidence in the tools at their disposal in this highly competitive underwriting environment.

Location Intelligence is a trusted, proven solution that integrates insights seamlessly with Moody’s Intelligent Risk Platform via the API and is used by many leading insurers around the world.

Conclusion: You Can Quote with Speed and Confidence And Make Better Underwriting Decisions

Moody's RMS Location Intelligence API delivers tremendous business value for insurers seeking to enhance their risk analysis capabilities.

With its superior data quality, accessibility, real-time response speed, and ease of use, this innovative tool empowers insurers to make more accurate and informed decisions.

By incorporating Location Intelligence into their workflows, insurers can unlock new opportunities for revenue growth and gain a competitive advantage in the dynamic insurance landscape.

To find out more about Location Intelligence contact sales@rms.com or visit the solution webpage here.

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James Lynn
James Lynn
Senior Product Marketing Manager, Moody's RMS

James is a Senior Product Marketing Manager at Moody’s RMS, where he helps customers develop data-driven strategies to better understand their risk.

He has more than a decade of experience in marketing roles within the insurance industry. Previously, James was a Global Marketing Manager for Verisk, leading campaigns and strategy across the non-U.S. underwriting portfolio.

Prior to Verisk, James worked as Group Marketing Manager at Newton Media, publishers of Intelligent Insurer, Bermuda:Re+ILS, Captive International, and other industry titles.

James has a bachelor’s degree in Politics and Film from Oxford Brookes University.

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