Swati is a Lecturer in Financial Technology. She joined the Management School at the University of Liverpool in August 2021. Her research interests centre around the development of explainable AI and machine learning models to automate decision making. She designs packages in Python to enable industrial research partners to use AI-based tools to automate decision making in finance, insurance, law, and healthcare. Her research interest includes hybrid rule-based systems, evidence reasoning, stochastic Petri-nets, human-in-loop algorithms, and non-linear constrained optimization.
She was a research associate at the Alliance Manchester Business School, the University of Manchester, from Oct 2017 to July 2021 at the Decision and Cognitive Sciences Research Centre. She has worked SmartClaim insurance project funded by UKRI. The SmartClaim insurance project was a collaboration between Kennedys Law, AXA insurance, Leap Beyond, and The University of Manchester to develop an industry-defining toolkit for the augmentation and automation of the whole claims process. She has worked on Fintech project with Together Financial Services to develop an explainable AI decision-support system to automate mortgage lending and a consulting project with AstraZeneca to improve financial data quality by machine learning. She has collaborated with the Berkeley Research Group to develop a multi-segmented deep-convolution neural network to detect the fault in current sensors.
Swati has a Masters in Operational Research in Finance from the University of Edinburgh and a PhD in Operational Research and Applied Statistics from Glasgow. She did her Masters dissertation on econometric modelling with Shell Royal Dutch plc and then worked as a statistician in the School of Mathematics, the University of Edinburgh. After completing her PhD, she joined the University of Nottingham as a Research Fellow to work in a European Commission project on Innovative Intelligent Rail (In2Rail). The project was coordinated by Network Rail (UK) and SNCF (French National Railway Company).