Innovation Area Lead at The MITRE Corporation
Dr. Sanith Wijesinghe is an Innovation Area Lead at The MITRE Corporation. His research focuses on the development of algorithms to help combat tax fraud. His most recent work on detecting tax schemes was awarded the Peter Jackson award at the International Association of Artificial Intelligence and Law and was featured in the New York Times. Prior to joining MITRE, Dr. Wijesinghe was VP Project Deployment at MillenniumIT, a software development firm serving the capital markets industry. Dr. Wijesinghe earned his master’s in Aeronautical Engineering from the Imperial College of Science, Technology & Medicine, London, U.K., and his Ph.D. in Aeronautics and Astronautics from MIT.
Track: Emerging Analytics
Tuesday, April 16, 1:50–2:40pm
Detecting Tax Evasion: A Co-evolutionary Approach
We present an algorithm that can anticipate tax evasion by modeling the co-evolution of tax schemes with auditing policies. Malicious tax non-compliance, or evasion, accounts for billions of lost revenue each year. Unfortunately when tax administrators change the tax laws or auditing procedures to eliminate known fraudulent schemes another potentially more profitable scheme takes it place. Modeling both the tax schemes and auditing policies within a single framework can therefore provide major advantages. In particular we can explore the likely forms of tax schemes in response to changes in audit policies. This can serve as an early warning system to help focus enforcement efforts. In addition, the audit policies can be fine tuned to help improve tax scheme detection. We demonstrate our approach using the iBOB tax scheme and show it can capture the co-evolution between tax evasion and audit policy. Our experiments shows the expected oscillatory behavior of a biological co-evolving system.