Guest editorial: Artificial intelligence in financial services marketing
Emmanuel Mogajia, Jillian Dawes Farquharb, Patrick van Eschc, Clara Durodiéd, Rodrigo Perez‐Vegae
- aDepartment of Marketing, Events and Tourism, University of Greenwich, Greenwich, UK
- bSolent University, Southampton, UK
- cDepartment of Marketing, Kennesaw State University, Kennesaw, Georgia, USA
- dCognitive Finance, London, UK
- eHenley Business School, Greenlands, UK
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Abstract
Background Artificial intelligence (AI) technologies have been incorporated into marketing where big data has been used to develop hyper-personalized profiles of customers (Payne et al., 2021) predicting consumer demand and creating targeted advertisements (Mogaji et al., 2020). In response, financial service providers are adopting AI to enhance their business operations (Arli et al., 2020). AI application in financial services includes chatbots and virtual assistants, underwriting and lending decisions, relationship manager augmentation, fraud detection, personalized banking, process automation, credit scoring and analytics (Riikkinen et al., 2018). The context of financial services is distinctive as solutions that use AI, big data analytics and blockchain technologies. Their rapid implementation is occurring at an unprecedented rate, posing new theoretical and managerial challenges (Bussmann et al., 2020). This special issue explored the intersect ofAI and financial servicesmarketing, recognizing the adaptiveness of financial service providers amidst the vast available data, making it an imperative for these providers to better understand their customer needs, attitudes and preferences, and use this information to develop relevant financial services to enhance service delivery. In addition, there are implications for policymakers and regulators, as financial services are a highly regulated sector, and technology’s impact on both customers and services provider are essential. Further implications arise in relation to information acquisition and information analysis (Duan et al., 2019). Financial services providers are required to collect data to teach and operate their AI systems, consequently, enabling concerns around AI policies, governance and control over the data. Consumers’ ethical considerations are also important. Their concerns relate to ethical data collection, biases in algorithms and discrimination (e.g. gender and race; Mogaji et al., 2021). As an imperative, financial service providers must be held accountable for their algorithms and AI-enabled technologies, regardless of their different data and ecosystem conventions (Buckley et al., 2021).
TL;DRThis special issue explored the intersect of AI and financial services marketing, recognizing the adaptiveness of financial service providers amidst the vast available data, making it an imperative for these providers to better understand their customer needs, attitudes and preferences, and use this information to develop relevant financial services to enhance service delivery. (Semantic Scholar)