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How to make your warranty program more profitable

By Jeremy P. Pecora and Ron Fowler, FCAS, MAAA | February 17, 2026

You can avoid sleepwalking into unprofitability and maximize value by mastering your data.
Corporate Risk Tools and Technology|Enterprise Risk Management Consulting|Global claims management|Insurtech|Risk and Analytics
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If you’re responsible for a warranty program, safeguarding profitability means uncovering hidden problems, and value.

Even if your program is already profitable, experience tells us there’s almost always more value for the smart program manager to unearth, assuming you can get on top of your data.

When tariffs, changing costs and inflation can quickly turn a profitable program into a loss-maker, extracting all your data can tell you about where you can generate stronger profitability becomes non-negotiable.

Below, we look at how to master your data to avoid sleepwalking into unprofitability and move instead toward maximum value.

How can you understand why warranty programs become unprofitable?

As well as inflation eroding profitability if you don’t factor it into your pricing models, our specialists see other common causes of unprofitable warranties regularly.

Uninformed pricing, often driven by marketing or competitive pressures, can lead to losses if you don’t account for actual product failure rates and claim frequencies.

Deterioration in product quality can also have a big impact, though it can take years to manifest, particularly in extended warranty programs.

However, many of the most vulnerable programs share one common denominator: their reliance on aggregate analysis. Generalized views of the data too easily mask unprofitable sub-segments. Even where high-level analysis shows your warranty program is profitable, dig deeper into your data and you’re likely to find a more nuanced story.

What value can you drive by analyzing warranty data at the product level?

When you group products together through aggregate analysis, you risk overlooking those segments, draining your profits.

By analyzing your warranty claims data at the product level, you can review factors like failure rates, diagnostic fees, coverage limits and repair costs for each product.

We understand the potentially vast time and resources involved in manual data analysis, particularly if you’re looking at thousands or tens of thousands of products. Getting to the point where you can spend less time wrangling the data instead of interpreting results may feel out of reach, but remember, advanced analytics can automate the heavy lifting. The right analytics free you to focus on interpreting the numbers and making strategic decisions that don’t let opportunities for profitability slip away.

How can you identify key indicators of unprofitable segments in warranty programs?

Look for high claim frequencies or severity, products with inherently higher failure rates, regions with elevated repair or replacement costs and customer segments with higher warranty utilization rates.

Again, you can turn to advanced analytics to dissect your warranty portfolios and pinpoint those specific products, customer segments, or geographic regions generating losses.

You’re trying to spot outliers here; those products or segments quietly eroding your margins while the rest of your portfolio looks healthy. By identifying these indicators, you can then zero in on the areas that require the most attention.

How can you use warranty data for more efficient analysis and scenario testing?

Scenario analysis and scenario testing let you understand how different factors, like inflation, supply chain disruptions or product quality issues, impact your bottom line. The more granular your data, the more accurately you can identify profitable segments and act before small problems become big ones.

Large warranty datasets are too complex for manual analysis or basic tools like Excel. Warranty management software enables you to efficiently analyze data at the product level and run scenario tests.

How did one manufacturer boost its warranty portfolio profitability using analytics?

We worked with one manufacturer that faced declining profitability in its warranty portfolio due to hidden losses in specific product segments. Aggregate analysis initially showed a healthy 70% loss ratio, but deeper product-level segmentation revealed one product had a 150% loss ratio, significantly impacting overall results.

By repricing this product to a 100% loss ratio, losses decreased by 33%.

Further analysis demonstrated how inflation assumptions dramatically affect loss ratios, especially for longer warranties. For example, a 48-month warranty’s loss ratio could rise from 70% to 135% as inflation increases from 2% to 6%.

The manufacturer could clearly see how inflation moves could jeopardize the entire portfolio, leading the business to consider robust scenario testing tools to safeguard profitability.

Enhance the profitability of your warranty program through data and analytics. Get in touch with one of our specialists to take control of your warranty program data and profitability.

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