An Appraisal of AI-Driven Fraud Detection Models in Nigerian Banks: A Case Study in Yobe State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Background of the Study
Fraud detection is a critical component of the banking sector’s operational framework, with artificial intelligence (AI) playing a transformative role. AI-driven models, such as neural networks and machine learning algorithms, enable banks to identify fraudulent transactions in real-time by analyzing patterns and anomalies in financial data.
In Nigeria, banks face increasing risks of fraud due to the growing sophistication of cyberattacks. Yobe State, like other parts of the country, has experienced significant challenges in mitigating fraud, necessitating the adoption of advanced technologies. Research by Nwachukwu and Oladipo (2024) highlights the potential of AI-driven models in reducing fraud and improving financial security. However, the effectiveness and adoption barriers of these models in Yobe State require further examination.
Statement of the Problem
Fraud remains a persistent challenge for Nigerian banks, with traditional detection methods proving inadequate against modern cyber threats. Banks in Yobe State face additional hurdles such as limited technical resources and high implementation costs for AI-driven solutions.
Although AI models offer enhanced capabilities, such as predictive analytics and real-time monitoring, their adoption in Yobe State’s banking sector has been inconsistent. Yusuf and Ibrahim (2023) observed that challenges such as data quality and lack of expertise often hinder the effectiveness of these models. This study appraises the use, impact, and challenges of AI-driven fraud detection models in Yobe State’s banking sector.
Objectives of the Study
-
To evaluate the adoption level of AI-driven fraud detection models in banks in Yobe State.
-
To assess the effectiveness of these models in reducing fraud.
-
To identify challenges affecting their implementation in Yobe State.
Research Questions
-
How widely are AI-driven fraud detection models adopted by banks in Yobe State?
-
How effective are these models in mitigating fraud in the banking sector?
-
What challenges hinder the implementation of AI-driven fraud detection models in Yobe State?
Research Hypotheses
-
AI-driven fraud detection models are not significantly adopted by banks in Yobe State.
-
AI-driven fraud detection models do not significantly reduce fraud in the banking sector.
-
Challenges do not significantly hinder the adoption of AI-driven fraud detection models in Yobe State.
Scope and Limitations of the Study
The study focuses on banks in Yobe State, appraising the adoption and impact of AI-driven fraud detection models. Limitations include variability in model sophistication and restricted access to detailed fraud data for analysis.
Definitions of Terms
-
AI-Driven Models: Algorithms and systems that utilize artificial intelligence for decision-making.
-
Fraud Detection: The process of identifying and preventing fraudulent activities.
-
Banking Sector: Financial institutions providing monetary services.
Related Project Materials
THE IMPACT OF CAREER ACADEMIES ON VOCATIONAL SCHOOL SUCCESS
ABSTRACT: This study explores the impact of career academies on vocational school success, investigating their role in improving student outco...
An examination of the role of cultural institutions in shaping Yoruba language policies in Ibadan
Background of the Study
Cultural institutions, including museums, cultural centers, and literary societies, are vital in p...
Implementation of an Augmented Reality-Based Historical Monument Guide in Abuja, FCT
Background of the Study
In recent years, augmented reality (AR) has emerged as a transformative technology in the cultural...
The Effect of Financial Accountability on NGO Operations in Jos North LGA
Background of the Study
Non-governmental organizations (NGOs) in Jos North LGA play a significant role in...
The impact of CSR budgeting on financial performance in Nigerian banks: A case study of UBA Plc
Background of the Study
Corporate Social Responsibility (CSR) has become an essential component of modern business pract...
An exploration of data-driven marketing on optimizing campaign performance: Evidence from an FMCG company in Port Harcourt, Nigeria
Background of the study
Data-driven marketing has become a cornerstone for modern advertising, enabling firms to harness la...
An Analysis of the Effect of Fiscal Policies on Business Investment in Nigeria
Background of the Study
Fiscal policies have long been recognized as influential determinants of business investment, shapi...
An Assessment of the Role of GDP Growth in Shaping Nigeria’s Economic Forecasts
Background of the Study
Economic forecasts are fundamental tools for policymakers, investors, and business leaders, providi...
An assessment of the influence of translator expertise on Efik language interpretations in cultural events
Background of the study
Cultural events are vital in preserving and celebrating the rich heritage of the...
The impact of mobile financial services on corporate banking outreach: A case study of First Bank Nigeria, Lagos
Background of the Study
Mobile financial services have revolutionized the banking sector by providing rapid, convenient, an...
