Bayesian multinomial latent variable modeling for fraud and abuse detection in health insurance

DOI10.1016/j.insmatheco.2016.09.013zbMath1373.62510OpenAlexW2531896837MaRDI QIDQ2374118

Andreas Bayerstadler, Fabian Winter, Linda van Dijk

Publication date: 14 December 2016

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.insmatheco.2016.09.013

zbMATH Keywords

Bayeshealth insurancelatent variablepredictive modelfraud and abuse detection

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Generalized linear models (logistic models) (62J12)

Related Items (2)

An evolutionary approach to fraud management ⋮ Statistical Medical Fraud Assessment: Exposition to an Emerging Field

Uses Software

• R
• MASS (R)
• Mcmcpack

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bagging predictors
• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• A Bayesian dichotomous model with asymmetric link for fraud in insurance
• Multivariate adaptive regression splines
• Polynomial splines and their tensor products in extended linear modeling. (With discussions)
• Statistical fraud detection: a review
• Multinomial logit models with implicit variable selection
• A Bayesian semiparametric latent variable model for mixed responses
• Geoadditive Latent Variable Modeling of Count Data on Multiple Sexual Partnering in Nigeria
• Statistical Analysis of Financial Data in S-Plus
• Cost-sensitive learning and decision making for massachusetts pip claim fraud data
• The Bayesian Lasso
• Polychotomous Regression
• Evaluating Learning Algorithms
• Random forests

This page was built for publication: Bayesian multinomial latent variable modeling for fraud and abuse detection in health insurance