Published: 05:40 PM, 13 September 2026 Last Update: 05:47 PM, 13 September 2026
Nasir Uddin Receives Financial Analytics Excellence Award 2026
Nasir Uddin, a Ph.D. candidate in Technology Management at the University of Bridgeport, USA, has been selected for the Financial Analytics Excellence Award 2026 in recognition of his research on artificial intelligence-driven financial fraud detection and risk management.
The award was presented in connection with the Second International Conference on AI-Driven Innovation, Modern Technology and Multidisciplinary Research in Patent Development 2026 (Patent Gen Beta 2.0 2026), held on August 28 and 29, 2026. According to the award materials, Uddin’s abstract was regarded by the selection committee as exceptionally insightful and closely aligned with the conference theme.
The official conference agenda lists Uddin among the recipients at the August 28 award ceremony, where the honor is identified as the Royal Golden Fellow Award – Silver, conferred by Eudoxia Research University, USA, and the Eudoxia Research Centre, India.
Research Focuses on AI and Financial Fraud Detection
During Technical Session 4 on August 28, Uddin participated as oral presenter OP013, presenting his survey-based study titled “Artificial Intelligence Driven Financial Fraud Detection for Enhancing Organizational Integrity and Risk Management.”
The research examined the relationship between four key factors—AI technology readiness, fraud detection capability, risk management effectiveness, and organizational integrity—and their contribution to improved financial fraud detection.
For the study, Uddin surveyed 145 professionals working across finance, banking, insurance, information technology, and corporate sectors in the United States. The data were analyzed using IBM SPSS Statistics Version 29, employing descriptive statistics, correlation analysis, and multiple regression.
The statistical model explained 75.2% of the variation in fraud detection performance. Fraud Detection Capability emerged as the strongest predictor, with a standardized coefficient of β = 0.361, followed by AI Technology Readiness (β = 0.301), Risk Management Effectiveness (β = 0.263), and Organizational Integrity (β = 0.227). All four factors were statistically significant.
Study Highlights Growing Role of AI
The findings indicate broad support for AI-enabled fraud prevention among the surveyed professionals. More than half of respondents reported full AI integration within their organizations, while approximately one-third reported partial adoption.
Respondents also emphasized the importance of accurate fraud detection and continuous monitoring in managing financial risks.
According to the study, AI-enabled systems can help organizations identify unusual financial patterns, support timely investigations, and improve risk-based decision-making. However, the research also emphasizes that technology alone is insufficient. Effective implementation requires trained professionals, reliable organizational processes, and strong standards of integrity.
Potential Implications for Bangladesh
The research could have particular relevance for Bangladesh as financial institutions increasingly rely on digital transactions and technology-enabled financial services.
The proposed framework may assist banks, mobile financial service providers, and insurance companies in identifying suspicious transactions at an earlier stage, reducing potential losses, strengthening internal controls, supporting regulatory compliance, and enhancing public confidence.
However, Uddin noted that the study was based on responses from professionals in the United States. Further research would therefore be needed to test and validate the framework within Bangladesh’s financial and regulatory environment.
Relevance to the United States and Global Financial Sector
For the United States, where the study participants were based, the findings may provide useful insights for banks, insurers, technology companies, and corporate finance teams seeking to strengthen fraud monitoring and enterprise risk management.
Improved AI capabilities could support earlier identification of suspicious activity, more targeted investigations, stronger asset protection, and more consistent compliance practices.
The study also carries broader international significance because financial fraud increasingly crosses institutional and national boundaries. Its central argument is that effective AI-based fraud prevention depends not only on advanced technology but also on organizational readiness, capable detection systems, sound risk management, and a strong ethical foundation.
International Recognition
The award selection process was overseen by the conference’s international Central Organizing Committee, led by Chief Patron Prof. Dr. Rhituraj Saikia, President of Eudoxia Research University, USA. The committee included academic leaders and institutional representatives from the United States, India, Greece, the United Kingdom, and other countries.
Uddin’s recognition at the international conference highlights the growing academic and practical importance of research at the intersection of artificial intelligence, financial analytics, fraud prevention, risk management, and organizational integrity.
His study proposes that combining technological capability with effective risk management and ethical organizational practices can contribute to stronger financial integrity across the United States, Bangladesh, and other economies.
