Agent-based Modelling of Credit Card Promotions
Conor B. Hamill, Raad Khraishi, Simona Gherghel, Jerrard Lawrence,, Salvatore Mercuri, Ramin Okhrati, Greig A. Cowan

TL;DR
This paper develops an agent-based model to analyze credit card promotion strategies, optimizing interest-free durations and promotion windows to maximize profit and market share under various competitive scenarios.
Contribution
It introduces a novel agent-based modeling approach focused on optimizing credit card promotion strategies, calibrated with UK market data from 2019-2020.
Findings
Optimal interest-free period is about 12 months without competition.
Longest promotion window maximizes profit and market share when no competitors offer promotions.
Delayed response to competitor promotions reduces lender income by approximately 2.4%.
Abstract
Interest-free promotions are a prevalent strategy employed by credit card lenders to attract new customers, yet the research exploring their effects on both consumers and lenders remains relatively sparse. The process of selecting an optimal promotion strategy is intricate, involving the determination of an interest-free period duration and promotion-availability window, all within the context of competing offers, fluctuating market dynamics, and complex consumer behaviour. In this paper, we introduce an agent-based model that facilitates the exploration of various credit card promotions under diverse market scenarios. Our approach, distinct from previous agent-based models, concentrates on optimising promotion strategies and is calibrated using benchmarks from the UK credit card market from 2019 to 2020, with agent properties derived from historical distributions of the UK population…
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Taxonomy
TopicsFinTech, Crowdfunding, Digital Finance · Digital Platforms and Economics · Banking stability, regulation, efficiency
