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Take a tourAcross the insurance industry, claims data is one of the most valuable but underutilized sources of insight. Every claim tells a story—not just about an individual incident, but about how a company operates, manages risk, and serves its policyholders.
When viewed in isolation, claims data can show trends within a single organization. However, without a point of reference, it is difficult to understand whether those trends reflect strong performance or hidden inefficiencies.
This is where benchmarking comes in. By comparing claims performance to that of industry peers, insurers can place their own data in context and identify areas for improvement.
Claims history benchmarking compares an organization's claims data with similar companies to see how they stack up. It looks at metrics like how often claims happen, how much they cost, and how long they take to resolve.
This process uses both structured data (like claim amounts and dates) and unstructured information (like adjuster notes) from various sources. Companies can compare their current performance to their past results or look at how they're doing compared to competitors in the same line of business.
The real value comes from turning raw numbers into useful reference points. These reference points help claims and underwriting teams spot patterns and figure out if their current practices are in line with what others are doing.
For example, if a company notices their auto claims take 20% longer to close than the industry average, they can look for ways to streamline their process.
Benchmarking transforms claims data from isolated information into actionable intelligence. When insurers compare their performance to industry peers, they gain perspective on what's working and what needs attention.
Take a regional insurer who discovered their water damage claims cost 30% more than similar companies. By digging deeper, they found they were using contractors who charged premium rates. Switching to a more cost-effective vendor network brought their claim costs in line with industry standards.
Benchmarking also helps refine pricing models. When insurers spot consistent differences between their loss experience and their peers, they can adjust pricing or underwriting guidelines to better match the expected risk.
Here's how benchmarking delivers concrete benefits:
A property insurer in Florida used benchmarking to discover their hurricane claims were settling 15% faster than competitors. This became a marketing advantage they highlighted to attract new customers.
Effective benchmarking starts with gathering the right data from both inside and outside your organization. This creates the foundation for meaningful comparisons.
Start by collecting your own claims information, including:
This data typically lives in claims management systems, but might also be found in financial records or adjuster reports.
For the data to be useful, it needs consistent formatting. For example, if one team measures "time to close" from when a claim is reported and another from when it's assigned, the comparison won't be accurate.
Legacy systems often create challenges with inconsistent coding or missing information. Taking time to clean and standardize this data pays off with more reliable benchmarking results.
External data provides the comparison points that make benchmarking valuable. Common sources include:
The key is finding data that matches your business. A commercial auto insurer should look for benchmarks from companies with similar fleet sizes and risk exposures.
When evaluating external sources, check how recently the data was collected and how closely it aligns with your business model. Data from five years ago or from a completely different market segment won't provide useful comparisons.
Raw numbers rarely tell the whole story. Normalization adjusts data to account for differences in company size, geography, and customer mix.
For example, comparing total claim counts between a large national insurer and a regional carrier doesn't make sense. Instead, looking at claims per 1,000 policies creates a fair comparison.
A workers' compensation insurer might normalize data by dividing claim counts by payroll to compare frequency across different sized accounts. This reveals whether higher claim counts stem from more exposure or higher risk.
Effective benchmarking focuses on metrics that reveal meaningful performance differences. These key indicators help insurers understand where they stand relative to industry peers.
Claims frequency measures how often claims occur relative to exposure. It's typically calculated as claims per unit of exposure, such as:
A retail chain's risk manager noticed their slip-and-fall claims frequency was 40% higher than similar businesses. Investigation revealed poor maintenance procedures at several locations, which they promptly corrected.
Comparing frequency across business lines requires consistent exposure definitions. Higher or lower frequency compared to peers might indicate differences in risk selection, safety programs, or claim reporting practices.
Claims ratio compares the number of claims to premium volume or policy count. This metric helps assess whether pricing adequately reflects risk.
For example, if a commercial property insurer has a claims ratio of 5 claims per $100,000 in premium while the industry average is 3, they might be underpricing their coverage or attracting higher-risk clients.
This metric helps identify portfolio segments that need attention. A high claims ratio in a particular region or customer segment suggests a need to review pricing or underwriting guidelines.
Average payout per claim reveals the typical cost of resolving claims. It includes both payments to policyholders and claim-related expenses like legal fees.
This metric helps evaluate cost control and settlement practices. If an insurer's average auto physical damage claim costs $3,200 while competitors average $2,800, they might need to review their repair shop network or adjustment practices.
Tracking average payout trends over time also helps detect shifts in claim severity or litigation rates before they significantly impact the bottom line.
Operational metrics like handling expenses and closure rates show how efficiently claims move through the system.
Closure rate measures the percentage of claims resolved within specific timeframes (30, 60, 90 days). This reflects both customer experience and internal efficiency.
Factors affecting closure rates include:
A commercial liability insurer found their claims stayed open 25% longer than the industry average. By implementing automated status updates and streamlining approval processes, they reduced their average claim lifecycle by three weeks.
Not all benchmarking delivers useful insights. Without proper context and methodology, comparisons can lead to flawed conclusions.
One common mistake is comparing dissimilar risks. A homeowners insurer in Florida faces very different claim patterns than one in Minnesota due to weather exposures. Meaningful benchmarking requires comparing similar risk profiles.
Using outdated data also undermines benchmarking value. Claims patterns change with legal trends, economic conditions, and social factors. Data from before a major regulatory change or significant court ruling may no longer reflect current reality.
Inconsistent definitions create another pitfall. If one insurer counts a claim when it's reported and another when it's paid, their frequency metrics aren't comparable. Clear, consistent definitions are essential for valid benchmarking.
Looking at metrics without understanding context can be misleading. Lower average payouts might indicate efficient claims handling—or they could signal inadequate investigations leading to future reopened claims.
To avoid these pitfalls, focus on relevant comparisons with similar organizations, use recent data, establish clear metric definitions, and look beyond surface numbers to understand underlying causes.
A regional insurer once celebrated their low loss adjustment expenses until benchmarking revealed they were significantly underpaying claims compared to peers, leading to higher litigation rates and customer dissatisfaction.
Benchmarking isn't just about measuring—it's about improving. Turning benchmark insights into action requires a structured approach.
Effective improvement starts with clear targets based on benchmarking findings. These targets should be specific, measurable, and realistic.
A commercial auto insurer discovered their collision claims cost 18% more than the industry average. They set a 12-month target to reduce this gap by half through better vendor management and process improvements.
Performance targets work best when they:
Benchmarking isn't a one-time event but an ongoing process. Regular monitoring helps track progress and identify emerging issues.
Most insurers review operational metrics quarterly and conduct deeper benchmarking annually. This cadence provides timely feedback while allowing enough time for improvement initiatives to show results.
Trend analysis helps distinguish between normal variations and significant shifts. For example, a gradual increase in litigation rates might indicate a changing legal environment, while a sudden spike in a specific claim type could signal a process breakdown.
Benchmarking delivers the most value when connected to broader business goals. Different departments can use the same benchmarking data to support their specific objectives:
A specialty insurer used claims benchmarking to identify high-performing market segments, which informed their growth strategy and helped them increase market share by 3% in targeted regions.
Today's technology is transforming how insurers approach benchmarking. Modern platforms consolidate fragmented data into unified views, making it easier to compare performance across portfolios.
AI and machine learning enhance benchmarking by automatically identifying patterns and anomalies in claims data. These tools can detect subtle trends that might escape human analysis, such as emerging fraud patterns or shifts in settlement outcomes.
For example, an AI system might notice that claims involving certain types of injuries have higher settlement costs when handled by specific adjusters, suggesting a need for additional training or guideline updates.
Real-time analytics replace the traditional quarterly or annual benchmarking cycle. Instead of looking backward at what happened months ago, insurers can now track performance against benchmarks as claims develop, allowing for faster adjustments.
By connecting claims history benchmarking with day-to-day operations, insurers can turn insights into action more quickly, improving results across the insurance lifecycle from initial underwriting to final claim resolution.