The human-centric algorithm: synergising AI-driven fraud detection with ethical human oversight to optimise sustainable banking integrity, Aminu Masanawa, Ahmad Shaheen

Aminu Usman Masanawa
DBA Research Scholar, Rushford Business School
Bank of Industry Limited
Nigeria
ORCID: 0009-0005-4158-3075
Ahmad Shaheen
College of management and technology, Arab Academy for Science, Technology and Maritime Transport
Egypt
ORCID: 0009-0002-5677-1990

Purpose: The ethical governance of Artificial Intelligence (AI) is becoming the new institutional sustainability in the modern digital banking environment.
Design/Methodology: On the Kaggle Credit Card Fraud Dataset, the research group structures a collaborative system in which Machine Learning models generate sub-second anomaly detection, and an Ethical Human Override (EHO) system adjudicates ambiguous, high-value transactions. The approach includes an empirical study of Principal Component Analysis (PCA)-transposed features to single out grey-zone clusters in which algorithmic rigidity tends to cause false positives and unjust rejection. The framework adopts a more socially sustainable framework by moving towards a defensive security posture through the application of a Human-in-the-Loop protocol to prevent the risk of algorithmic redlining.
Findings: The novelty of the writing is in the fact that the Cost of False Positives became a part of the more comprehensive sustainability discussion, and human control was seen as an essential measure of financial equity.
Originality/Value: This research proposes a bimodal fraud detection framework that resolves the inherent tension between algorithmic efficiency and socio-economic inclusion.
Practical Implications: In practice, the research offers a transformational map of applying human contextual judgment to FinTech ecosystems, balancing predictive accuracy of AI with moral responsibility of human intelligence to create a resilient, inclusive and sustainable financial future.
Keywords: Artificial Intelligence; Algorithmic; Machine Learning Models; Financial Equity.