Burglary theft claims are seasonal and spike in December, April and September, according to research from Enservio, an insurance applications software vendor. And, those claims are increasing in frequency, value and suspicion, according to a study by the National Insurance Crime Bureau, which discovered a rise in questionable property claims it has received from carrier members over the past three years.

“We have terabytes of data about the contents inside the average American home tied to its location and demographics,” said Jon McNeill, Enservio CEO. “Searching for insights to better service our carriers, we delved into this data to analyze all types of property claims against consumer product categories. We studied the frequency of property claims and time of year when claims were filed to arrive at our findings.”

Enservio also found that the average property contents claim settlement is $4,000 and growing; the average-stated value of many objects being claimed is more than twice their actual retail value; and burglary claims are increasing in value, outpacing the rate of inflation by 2 percent to 3 percent.

In addition, the National Insurance Crime Bureau (NICB) reported that suspicious personal property claims submitted to NICB increased by 46 percent from Jan. 1, 2010 to Dec. 31, 2012. Of those questionable claims, 72 percent were associated with homeowners’ policies.

Enservio’s findings were derived from a statistical analysis of the company’s data warehouse, which contains billions of dollars’ worth of settled contents claims, the company said, across geographies, perils, policy types and claim sizes. Aggregated pricing data from millions of consumer products, from hundreds of retailers, also were refreshed daily and factored into the analysis.

 

The highest volume in theft claims occurs in December, at the height of the holiday season, followed by April, tax time in the United States, and September, which is associated with back-to-school shopping and tuition payments.

Enservio’s advice to insurers:

  • Use data to score claims on their fraud potential
  • Use data to identify their most loyal and profitable customers; compare claims values to average retail values and flag questionable claims
  • Ask policy holders for proof of purchase or credit card statements on suspicious claim values
  • Offer access to current retail prices on common claims category leaders
  • Give adjustors qualifying questions to ask claimants
  • Use technology to flag suspicious claims amounts and focus on higher-value cases
  • Use predictive analytics to deliver more accurate payment amounts to insurers.

“Our findings show that a simple form of analysis of big data can reveal important trends and spur actionable results that should make a real difference in the profitability of homeowners insurance,” McNeill said.
Related content: Personal Property Questionable Claims Jump 19% 

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