The Role of Retrieval-Augmented Generation (RAG) in Financial Document Processing: Automating Compliance and Reporting (Published)
The rapid digitalization of the financial sector has also increased the usage of artificial intelligence (AI) in operations, compliance, and regulatory reporting. Retrieval-augmented generation (RAG) is turning out to be a very prominent AI-driven approach that synergizes retrieval-based and generative models to deliver far better accuracy and efficiency in processing financial documents. Traditional methods for compliance reporting are manual, excruciatingly slow, and vulnerable to human errors, thereby creating a burden of regulatory scrutiny and monetary penalties. By using the power of RAG, financial institutions would automate the encapsulation of relevant information, summarize the sheer volume of regulatory text, and be in a real-time position to comply with ever-changing regulations: IFRS, Basel III, and GDPR. RAG would also provide forensic examination and disparate pattern detection in support of fraud, risk, and due diligence. This paper investigates the role of RAG in the automation of compliance and reporting processes pertaining to financial document processing. It addresses the regulatory compliance challenge, the drawbacks of the traditional document processing approach, and the merits of an AI-based automated approach. A qualitative study of those case studies and industry applications will prove the proposition that RAG enhances financial workflows through lower manual effort, higher data accuracy, and improved decision-making. The paper also discusses strategies for implementation in the context of financial institutions and provides insights into the developments in AI regulation in the future. With the growing embrace of AI-powered alternatives in the financial industry, RAG is an opportunity for game-changing transformation toward optimizing compliance reporting, actualizing risk mitigation, and driving operational efficiencies amid the complexity brought on by the regulatory environment.
Keywords: AI implementation, AI in finance, Fraud Detection, Risk Management, artificial intelligence (AI), compliance automation, compliance monitoring, financial document processing, financial institutions, financial technology (fintech), regulatory reporting, retrieval-augmented generation (RAG)
Information Technology Governance Control Level in Jordanian Banks Using: Control Objectives for Information and Related Technology (COBIT 5) (Review Completed - Accepted)
Information technology is considered a sensitive part for most strategies in the global market competition. There are plenty of factors indicating expansion in the world of information technology, the matter that places greater demands on the control of the environment for information technology and augments the need to mitigate risk and cost control related to the IT environment information. Hence, the importance of emphasizing the horizons of information, and the existence of effective controls on the IT environment should be designed for information technology services used by several parties, managers, auditors and owners.
This should facilitate controls and offer the opportunity to re – engineer the applications of the existing regulatory environment, which requires a comprehensive review and redesign of the regulatory controls.
To respond to any changes in the business environment, executives must ensure that information technology works with the greatest possible efficiency to help achieve goals and objectives. Growing competitive advantage, ensuring compliance and continuity, security and privacy are essential in order to achieve effective management for Information Technology related risks as well as maximal benefits in technology investment.
Keywords: Business goal, Enterprise Governance of IT, IT governance, Organizational structure, Risk Management