Abstract
Benford's Law is the mathematical phenomena that states that the first digits or left most digits in a list of numbers will occur with an expected logarithmic frequency. While this method has been used in industries such as oil and gas and manufacturing to identify fraudulent activity, it has not been applied to the health insurance industry. Since health insurance companies process a large number of claims each year and these claims are susceptible to fraud, the use of this method in this industry is appropriate. This paper examines the application of Benford's Law to four health insurance companies located in the Midwest. For each company, analysis was performed on the first digit distribution, the first two-digit distribution, and providers with high volumes of claims. The results show that the populations are similar to the frequencies predicted by Benfords Law. The findings also suggested possible fraudulent activity by specific providers, however, the com-panies determined that these results occurred due to abnormal billing practices and were not frau-dulent. The insurance companies that participated in this study will continue to use this method to further detect fraudulent claims.
Highlights
T he U.S General Accounting Office has estimated that fraud accounts for up to 10% of the annual expenditure on health care or $100 billion in the United States (GAO 1997)
Given conformity to Benford‟s Law, one can use this tool as a method of detecting possible fraudulent or errant claims received on behalf of a health insurance company
This study reviewed the overall conformity of the entire population to Benford‟s Law at the first digit and first two digits level
Summary
T he U.S General Accounting Office has estimated that fraud accounts for up to 10% of the annual expenditure on health care or $100 billion in the United States (GAO 1997). When utilizing analytical procedures in auditing, the results indicate potential areas of overstatement or understatement in account balances or system data (Nigrini 1997). Nigrini found that the data followed the expected pattern over the first five years, but deviated from the expected values for the second five years This was caused by a repetitive fraud committed by the payroll clerk. Their study noted an unusual frequency of numbers below the signing levels, which did not conform to the predicted results The use of these data analysis tests has a practical application in the field of auditing large sets of data. By applying Benford‟s Law to each company‟s claims, trends can be detected that may indicate possible errors or frauds. Corporate resources can be more effectively used to research those suspect companies, instead of randomly auditing from a pool of all providers
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