AI与NLP结合提升尼日利亚金融欺诈检测能力
Artificial Intelligence-Enabled Accounting Information Systems and Fraud Detection in Nigeria's Financial Services Sector: The Moderating Role of Natural Language Processing
- 用AI驱动的会计系统增强审计与反欺诈能力
- NLP显著提升AI系统在语义理解与分析解释上的表现
- 适合关注金融科技安全与合规的从业者参考
金融系统数字化加速提升了运营效率与金融包容性,但也增加了网络欺诈和电子财务违规的风险。传统依赖事后验证和规则监控的审计体系难以应对现代金融犯罪的复杂性和速度。因此,金融机构正逐步采用人工智能(AI)驱动的会计信息系统(AIS)和自然语言处理(NLP)技术以强化欺诈检测、持续审计与机构监控。本研究基于欺诈钻石理论和技术接受模型,采用横断面问卷调查法,收集了尼日利亚银行业、保险业及金融科技机构共186名专业人员的数据,通过描述性统计、多元回归与分层调节回归分析发现:AI-enabled AIS显著提升审计与欺诈检测效果,尤其在预防、检测、数据分析与调查方面;同时,NLP正向调节AI-AIS与审计有效性之间的关系,通过改善语义解析与分析可解释性。研究结论指出,AI-enabled AIS与NLP对新兴数字金融环境中强化欺诈治理、监管问责与机构信任至关重要。
原文摘要 · Abstract (English)
The rapid digitalisation of financial systems has improved operational efficiency and financial inclusion while simultaneously increasing exposure to sophisticated forms of cyber-enabled fraud and electronic financial misconduct. Conventional auditing systems, which largely depend on retrospective verification and rule-based monitoring, increasingly struggle to address the complexity and speed of modern financial crime. Consequently, financial institutions are progressively adopting Artificial Intelligence (AI)-enabled Accounting Information Systems (AIS) and Natural Language Processing (NLP) technologies to strengthen fraud detection, continuous auditing, and institutional monitoring. This study examined the influence of AI-enabled AIS on auditing and fraud detection effectiveness within Nigeria's financial services sector while additionally evaluating the moderating role of NLP. Anchored on the Fraud Diamond Theory and the Technology Acceptance Model, the study adopted a quantitative cross-sectional survey design. Primary data were collected from 186 professionals across banking, insurance, and FinTech institutions in Nigeria. Data were analysed using descriptive statistics, multiple regression, and hierarchical moderated regression techniques. The findings revealed that AI-enabled AIS significantly improves auditing and fraud detection effectiveness, particularly through prevention, detection, data analysis, and investigative capabilities. The results further indicated that NLP positively moderates the relationship between AI-enabled AIS and auditing effectiveness by improving semantic interpretation and analytical explainability. The study concludes that AI-enabled AIS and NLP are increasingly important for strengthening fraud governance, regulatory accountability, and institutional trust within emerging digital financial environments.
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