Data enhancement: providing data quality that meets exacting standards

The goal

Tokio Marine America (TMA) is a US-based commercial property and casualty insurance company and part of Tokio Marine Group. Operating across all 50 states, it works with major brokers and leading independent insurance agents throughout the region, providing a wide range of insurance solutions across multiple industries.

The company maintains rigorous underwriting standards for every risk it writes and fundamental to this is a commitment to ensuring that decisions extending from individual risk to the portfolio level are made based on the most accurate and complete exposure data available. This approach improves catastrophe modeling and enhances technical pricing, helping TMA maintain more consistent rates for clients throughout the insurance market cycle.

TMA applies stringent data evaluation criteria and has been working with Moody’s Managed Client Services and Analytical Services in several capacities including maintaining high levels of data completeness.

In this case study, the company had provided Moody’s with data relating to a specific property account for a Japanese client with several high-value assets located in the US.

 

The objective

Analyzing data quality for property account

Moody’s delivered several data-related services to TMA, which include risk data assessment and cleansing, catastrophe modeling activities, and generating portfolio roll-ups and management reports. The first phase of the process for any data received was to conduct a thorough review of the information quality and completeness and highlight any information gaps. 

TMA’s portfolio spanned 60 separate locations with property exposures across the United States, including a significant number of high-value assets located in Florida. The total insured value of the account was approximately US$900 million. The account information included standard datasets relating to building locations and Construction Occupancy Protection Exposure (COPE). 

TMA initially required Moody’s to conduct a thorough check of the account information to establish whether it met the organization’s minimum quality standards.

 

The process

Data Quality Index (DQI) assessment and feedback

To maintain high-quality data, the team scored the data against its Data Quality Index, which analyzes the exposure information in terms of the availability of location details and COPE building characteristics. It achieved a score of 3.7 out of 5, which was below TMA’s minimum required level.

The missing data for the account included:

• Negative business interruption values
• Missing address details for high exposure values
• Incomplete COPE for high exposure values

The findings were instantly reported to TMA, and the teams worked together to secure the missing data from a range of different sources, including the Moody’s Industry Exposure Database, which was used to provide a significant amount of the COPE information, including construction type, occupancy, and number of stories.
 

The outcome

Significant data improvement enhances exposure understanding

Using the augmented account data, Moody’s conducted a reassessment of the account’s DQI score and confirmed that the data now exceeded TMA’s minimum data quality standard.

Through analyzing the enhanced datasets and running the losses through Moody’s RiskLink™, we were able to show the impact on overall annual average losses at the individual peril level. The analysis revealed a 12% reduction in ground-up (GU) losses for the combined perils, with a:

• 19% reduction in GU windstorm losses
• 3% increase in GU convective storm losses
• 1% reduction in GU earthquake losses
  
  

Conducting the analysis for the individual high-value exposure locations in the account, the team revealed the following:

• For the second-highest total-insured-value (TIV) location, there was a 46% reduction in GU earthquake losses, a 68% reduction in GU windstorm losses, and a 31% reduction in GU convective storm losses.
• For the sixth-highest TIV location, there was a 47% reduction in GU earthquake losses, a 22% increase in GU windstorm losses, and a 43% increase in GU convective storm losses.

The improved data accuracy for location and COPE for a number of the high-value locations resulted in a 22% increase in the TIV for the overall account.

In total, the initial assessment and subsequent analysis of the account data took the team approximately 6.5 hours.

By having access to more accurate exposure insights based on the enhanced account data, the TMA underwriting team could achieve the following:

• Reduce underwriting decision-making time frames
• Improve efficiencies at every stage in the risk assessment process
• Apply more stringent risk selection criteria 
• Accurately select the layers it wishes to write on
• Charge premium rates precisely aligned with the risk exposure
• Conduct more robust and informed reinsurance discussions based on more accurate data
• Demonstrate higher-quality data as part of rating agency assessment processes 

"Since we began working with Moody’s, the relationship has led to a huge number of very positive changes across many aspects of our business. We’ve improved our data quality, replaced numerous cumbersome data processes, reduced manual data input requirements and instances of duplication, and ultimately created a much more streamlined ecosystem."

Vinay Annigeri, HPR Property Manager, TMA