Simulating Human Behaviour in Financial Contexts: Leveraging AI and Agent-Based Models

Abstract: 

In this session we will explore how AI and agent-based modelling can be used to simulate human behaviour and explore financial strategies and policies. We will first delve into an advanced agent-based model designed to explore the effect of credit card promotions. Using real-world data from the UK credit card market, this model helps us understand how different promotion strategies and the presence of competition affect financial performance and consumer behaviour. Additionally, we will touch upon the potential of generative agents in simulating human behaviour within financial contexts. These agents, powered by LLMs, provide a glimpse into future applications where realistic simulations can enhance our understanding of consumer behaviour and decision-making.

Understand how ABMs can be used in a financial context and how LLMs are reshaping our understanding of consumer behaviour.

Bio: 

Raad Khraishi is currently a Principal Data Scientist at NatWest Group, where he builds machine learning solutions for a wide range of problems in areas such as financial crime, pricing, finance, marketing, and credit risk. Raad also leads advanced research in deep learning, language models, privacy, and reinforcement learning. He holds a BA in Economics from UCSB, an MSc in Economics from UCL, and is currently pursuing his PhD with a focus on finance and machine learning at UCL's Institute of Finance & Technology.

Open Data Science

 

 

 

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