Information Spillovers and Semicollaborative Networks in Insurer Fraud Detection

MIS Quarterly (Forthcoming)

Posted: 18 Nov 2015 Last revised: 17 Aug 2017

See all articles by Nirup M. Menon

Nirup M. Menon

George Mason University - Department of Information Systems and Operations Management

Date Written: November 16, 2015

Abstract

IT-related spillovers occur via data- and information-related transmission paths, so these types of spillovers are best studied through process-level measures. The medical claims fraud detection is a prototypical data- and information-intensive process in insurance companies. This paper examines the impact of IT-related spillovers on fraud detection outcome for insurers and patient-care quality for hospitals. I theorize three semicollaborative networks formed between state-level subsidiaries of insurers (regulation-bound network), between subsidiaries of an insurer parent company (sibling network), and between insurers and hospitals (risk-sharing), and hypothesize that these networks convey information spillovers. I then examine the impact of spillover benefits and the impact of spillover IT pools on future IT-related investments. The empirical analysis is conducted using 2011-2013 data for insurers and hospitals. I use a generalized linear model with a Tweedie distribution to correct for the finite mass of zeros for my dependent variable. Results reveal that the sibling network contributed the most of the spillover benefit, and the risk-sharing network did not contribute to fraud detection. I also find that the sibling network depresses future spending on fraud detection.

Keywords: technology spillovers, insurance company, externality, mortality rate, readmission rate, hospital quality

Suggested Citation

Menon, Nirup M., Information Spillovers and Semicollaborative Networks in Insurer Fraud Detection (November 16, 2015). MIS Quarterly (Forthcoming), Available at SSRN: https://ssrn.com/abstract=2691467 or http://dx.doi.org/10.2139/ssrn.2691467

Nirup M. Menon (Contact Author)

George Mason University - Department of Information Systems and Operations Management ( email )

4400 University Drive
MS 5F4
Fairfax, VA 22030
United States

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