Barriers to the Adoption of Artificial Intelligence Techniques for Credit Scoring Systems: An Exploratory Study in Jordanian Banks

Artificial Intelligence (AI) integration in Jordanian banking sector, particularly AI-based Credit Scoring Systems (AI-CSSs), offers transformative potential for credit risk management. AI-CSSs can enhance predictive accuracy, reducing of human errors and bias, promote financial inclusion, streamline loan processing, improve fraud detection, and reduce operational costs. However, their adoption remains limited, especially in regions facing political and economic instability. This study investigates the factors influencing AI-CSS adoption in Jordanian banks, applying the Technology-Organisation-Environment(TOE) framework and Institutional Theory to provide a comprehensive analytical perspective. A qualitative research approach was employed, involving 30 in-depth interviews with senior executives, including Chief Executive Officers, Chief Risk Officers, and Chief Technology Officers from 10 of Jordan’s 20 licensed banks. Thematic analysis identified key TOE barriers to AI adoption: (1)technological (IT infrastructure, AI expertise, AI training, safety and security, and data availability and validity); (2) organisational (organisational attitude, top management support, financial resources, and AI strategy; and (3) environmental (coercive pressures – government and AI governance, Central Bank and AI initiatives, cash culture, state-level big data centres, market dynamics and FinTech suppliers ;normative pressures – educational institutions; and memetic pressures – peer influence). Economic constraints and regional instability further drive a risk-averse banking approach, where financial stability is prioritised over technological innovation. This study offers important theoretical contributions by refining the TOE framework and institutional theory to incorporate contextual factors unique to AI-CSS adoption in banking, particularly in apolitically and economically volatile emerging economy like Jordan. Through a restructured conceptual model, this research extends the applicability of these frameworks to emerging financial technologies in developing economies. The findings emphasise the need for strategic interventions at both the institutional and organisational levels to enable sustainable AI-CSS integration in Jordanian banks. Additionally, the research provides a practical roadmap for policymakers, financial institutions, and technology providers in Jordan to address identified barriers and promote effective technology adoption strategies.

Name dc:type.qualificationname

PhD

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

De Montfort University

Year dc:date.issued

2025

Author dc:creator

• Al-Akayleh, Malek Abdallah Ali

Licence

• https://dora.dmu.ac.uk/bitstreams/bbae0b6c-ad75-442b-81e4-775eae8e9df2/download