Ethical Risks in AI-Enabled BI Systems in Banking

Abstract

Artificial intelligence (AI) in the banking sector enhances the value of Business Intelligence (BI) systems through operational efficiencies, personalization of services, and more accurate data-driven decision making. Yet the rapid pace of AI technology convergence brings potential losses of trust, fairness, and accountability in the ethics of intersectional financial systems. Key ethical concerns are algorithmic bias, the potential AI systems will fail to provide equitable outcomes and perpetuate discrimination against certain demographics; the processing of sensitive and personal financial data will raise data privacy issues; accountability will be elusive, as the opaque nature of AI systems will render decision-making processes and outcomes inscrutable; and gaps in transparency will escalate. This paper intends to add to the discourse on the ethical concerns associated with AI-driven BI systems by undertaking a holistic examination of the ethical and unregulated aspects of the financial sector. Moreover, it seeks to provide a risk mitigation approach based on the ethical and regulatory oversight applicable to other sectors. Responsible AI governance will facilitate the ethical application of AI in a manner that preserves the institutions’ transparency, fairness, and accountability in core operations. The ultimate aim is to facilitate the use of AI technologies in banking to improve the customer experience while maintaining the highest ethical standards and safeguarding the trust of the public.