Building Trust in AI-First Banking: Ethical Models, Explainability, and Responsible Governance

Vijay Kumar Adari

doi:10.15662/IJRAI.2021.0402004

Authors

Vijay Kumar Adari Enterprise Data Architect, Cognizant Technologies Solutions, USA Author

DOI:

https://doi.org/10.15662/IJRAI.2021.0402004

Keywords:

AI-first banking, ethical AI, explainable artificial intelligence, financial governance, transparency, trustworthiness, regulatory compliance, responsible AI, consumer trust, model fairness

Abstract

The rapid adoption of artificial intelligence (AI) in banking is reshaping every major financial function—from credit risk assessment and fraud prevention to personalized financial advisory. However, the increasing autonomy of AI models has raised critical concerns regarding transparency, fairness, and customer trust. As financial institutions transition to an AI-first operating model, establishing responsible governance becomes essential to maintain regulatory compliance and public confidence. This paper examines the core components required to build trust in AI-driven banking systems, focusing on ethical model development, explainable decision-making, and accountability frameworks. It investigates international AI principles and emerging financial regulatory mandates while analyzing the implications of bias, data privacy risks, and model opacity on customer trust. Based on a synthesis of industry trends, technology practices, and governance standards, the paper introduces a comprehensive Trustworthy AI-First Banking Framework that integrates ethical guardrails, lifecycle governance, and explainable AI (XAI) methodologies. The findings highlight that financial institutions adopting proactive risk oversight and transparent algorithmic communication can significantly improve trust and customer acceptance of automated decision systems. This provides a strategic pathway for secure, fair, and responsible AI adoption in the banking sector.

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