A data set for modeling claims processes—TSA claims data. Issue 3 (20th August 2020)

• Record Type: Journal Article
• Authors: Kelly, Mary; Wang, Zilin
• Is Part Of: Risk management and insurance review. Volume 23:Issue 3(2020)
• Page Start: 269
• Page End: 276
• Publication Date: 2020-08-20
• Subjects: claims data -- claims modeling -- frequency and severity models; Risk (Insurance) -- Periodicals; Risk management -- Periodicals; Risk (Insurance) -- United States -- Periodicals; Risk management -- United States -- Periodicals; 368
• DOI: 10.1111/rmir.12155
• Languages: English
• ISSNs: 1098-1616

Abstract

Abstract: This data insight highlights the Transportation Security Administration (TSA) claims data as an underused data set that would be particularly useful to researchers developing statistical models to analyze claim frequency and severity. Individuals who have been injured or had items damaged, lost or stolen may make a claim for losses to the TSA. The federal government reports information on every claim from 2002 to 2017 at https://www.dhs.gov/tsa-claims-data . Information collected includes claim date and type and site as well as closed claim amount and disposition (whether it was approved in full, denied, or settled. We provide summary statistics on the frequency and the severity of the data for the years 2003 to 2015. The data set has several unique features including severity is not truncated (there is no deductible), there are significant mass points in the severity data, and the frequency data shows a high degree of auto correlation if compiled on a weekly basis, and substantial frequency mass points at zero for daily data.