CORMSIS Seminar "Brief Introduction to DCSRC and Hybrid Data-Driven and Knowledge-Based Fraud Detection in Insurance" - Prof Jian-bo Yang Event

Date:: 3 June 2021
Venue:: Please email Huan Yu for a link to the virtual seminar

For more information regarding this event, please email Huan Yu at Huan.Yu@southampton.ac.uk .

Event details

This presentation is divided into two main parts. In the first part, the research profile of the Decision and Cognitive Sciences Research Centre (DCSRC) of Alliance Manchester Business School, The University of Manchester will be introduced and some of the recent and current research projects undertaken by DCSRC staff will be briefly discussed. The second part is dedicated to discussing a KTP project in more detail, which focuses on hybrid data-driven and knowledge-based fraud detection in the insurance sector. This KTP project was jointly conducted with a multinational law firm: Kennedys Law. The methodologies in data analysis and probabilistic inference developed by DCSRC researchers were applied to fraud detection in insurance claims. Findings from the application will be presented and lessons learnt from the KTP project will be discussed. The successful completion of this KTP project shows that the proposed methodologies preserve the interpretability and usability of expert detection systems and can be used to predict changing patterns in fraud practices by tracking the trend of the weights of experience-based indicators. The findings also show that the proposed methodologies outperform a number of widely used machine learning models.

Speaker information

Dr Jian-Bo Yang, Chair Professor of Decision and Systems Sciences and Director of the Decision and Cognitive Sciences Research Centre at Alliance Manchester Business School, The University of Manchester, UK. He is also visiting Advisory Professor at Management School, Hefei University of Technology, China. Over the last three decades, He has conducted theoretical and methodological research in many areas, including the evidential reasoning (ER) theory; multiple criteria decision analysis under uncertainties; probabilistic inference and decision analysis using both data and judgments; multiple objective optimisation; intelligent system modelling; explainable artificial intelligence (AI) and interpretable machine learning; hybrid decision methodologies and technologies combining concepts and techniques from decision science, systems science, operational research and AI. His current applied research covers a wide range of applications driven by data, powered by AI and enabled by ER, including modelling and decision support for professional services such as finance, insurance and healthcare; diagnosis and prognosis, design and operation decision analysis in healthcare, engineering and social systems; pattern identification and analysis of consumer behaviours; analysis of public sentiments and system risks (financial or non-financial); new product development; aggregated production management; system maintenance management; risk and security modelling and analysis; performance analysis and improvement of products, processes and organizations. He is principal investigator or co-investigator for over 70 research projects at a total value of over £21m, funded by many organisations, including UK Engineering and Physical Science Research Council (EPSRC), UK Economic and Social Research Council (ESRC), Innovate UK, UK Department of Environment, Food and Rural Affairs (DEFRA), European Commission (EC), Natural Science Foundation of China (NSFC), Hong Kong Research Grant Council (HKRGC) and industry. He has published 4 books, over 260 journal papers and book chapters, and a similar number of conference papers, with extensive citations such as in Web of Science and Google Scholar, and developed several software packages in optimisation and decision support with wide applications worldwide.