Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Using data mining to detect crop insurance fraud: is there a role for social scientists?

Using data mining to detect crop insurance fraud: is there a role for social scientists? Defines data mining as the extraction of potentially useful information from large databases. Shows how data mining can be applied to detecting anomalous behaviour in American agriculture and thus support the Risk Protection Agency in its compliance mission to detect fraud in crop insurance, using corn as the crop studied and percentage of acres harvested as the key indicator for “proof of concept”. Indicates potential areas of improvement, such as the development of a single data warehouse, and the role of social scientists with knowledge of data analysis and agricultural management. Concludes that data mining could be more effective than the current technique of random selection for investigation of individual entities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Financial Crime Emerald Publishing

Using data mining to detect crop insurance fraud: is there a role for social scientists?

Loading next page...
 
/lp/emerald-publishing/using-data-mining-to-detect-crop-insurance-fraud-is-there-a-role-for-4oHJxaVhlt
Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
1359-0790
DOI
10.1108/13590790510625052
Publisher site
See Article on Publisher Site

Abstract

Defines data mining as the extraction of potentially useful information from large databases. Shows how data mining can be applied to detecting anomalous behaviour in American agriculture and thus support the Risk Protection Agency in its compliance mission to detect fraud in crop insurance, using corn as the crop studied and percentage of acres harvested as the key indicator for “proof of concept”. Indicates potential areas of improvement, such as the development of a single data warehouse, and the role of social scientists with knowledge of data analysis and agricultural management. Concludes that data mining could be more effective than the current technique of random selection for investigation of individual entities.

Journal

Journal of Financial CrimeEmerald Publishing

Published: Jan 1, 2005

Keywords: Fraud; Data handling; Insurance; Crops; United States of America

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$499/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month