A Survey on AI Implementation in Finance, (Cyber) Insurance and Financial Controlling

Aleksandrova, Aleksandrina; Ninova, Valentina; Zhelev, Zhelyo

doi:10.3390/risks11050091

Cited by 5 publications

(4 citation statements)

References 42 publications

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“…Identification and access management support tight control over information access rights, reducing the likelihood of unauthorized access or misuse (Aleksandrova et al 2023). It includes establishing user profiles, assigning roles, and restricting access rights to the "need to know" principle.…”

Section: Information Management Methodsmentioning

confidence: 99%

“…The automation of data collection and processing reduces the likelihood of errors and frees up valuable resources that can be redirected to other activities. For this purpose, advanced analytical tools such as Artificial Intelligence (AI) (Aleksandrova et al 2023) and Machine Learning (ML) (Zarkova et al 2023) may be included to help identify patterns and trends.…”

Section: Information Management Methodsmentioning

confidence: 99%

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Investigating the Application of Digital Tools for Information Management in Financial Control: Evidence from Bulgaria

Zhelev,

Kostova

2024

JRFM

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This paper discusses the application of digital information management tools in the context of financial control. In Bulgaria, such research is innovative as it is the first time that digital transformation in crucial financial control institutions, which influence the formation of the revenue part of the state budget and the spending of public funds, has been studied. The study aims to answer the research question of to what extent the application of digital tools in financial control improves its effectiveness. It analyses how modern technologies improve the efficiency and accuracy of information used in financial control institutions. The authors examine the impact of digital tools, such as database management systems, business analytics platforms, and electronic document management tools, on collecting, analyzing, and managing financial and non-financial information. The study uses descriptive statistics and a correlation analysis, which significantly contributes to establishing the relationship between implemented digital tools and improvements in financial control procedures. The results show that despite the conditions created for digitalization in financial control institutions, digital tools are used to a limited extent in the information management process. The study emphasizes the need for continuous investment in digital technologies and training to maximize the benefits of their application in financial control.

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Section: Information Management Methodsmentioning

confidence: 99%

Section: Information Management Methodsmentioning

confidence: 99%

Investigating the Application of Digital Tools for Information Management in Financial Control: Evidence from Bulgaria

Zhelev,

Kostova

2024

JRFM

Self Cite

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“…The authors identify key trends and themes in AI-related publications, offering insights into the future of AI in finance and insurance. This survey underscores the interdisciplinary nature of AI and its growing demand in providing innovative solutions and services (Aleksandrova, Ninova, & Zhelev, 2023).…”

Section: Case Studies: Successful Implementation Of Ai In Compliancementioning

confidence: 97%

“…This case study highlights the transformative potential of AI in reshaping job roles and enhancing business processes in the financial sector (Parker and Appel, 2021). Aleksandrova, Ninova, and Zhelev (2023) conduct a comprehensive survey on AI implementation in finance, insurance, and financial controlling. Their study provides an indepth overview of AI's role in these sectors, discussing the advantages, challenges, and relationship between economic development and AI.…”

Section: Case Studies: Successful Implementation Of Ai In Compliancementioning

confidence: 99%

Automating Financial Regulatory Compliance With Ai: A Review and Application Scenarios

Oluwatobi Opeyemi Adeyelu,

Chinonye Esther Ugochukwu,

Mutiu Alade Shonibare

2024

Financ. account. res. j.

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This scholarly paper delves into the transformative realm of Artificial Intelligence (AI) in financial regulatory compliance, offering a classical and engaging exploration of its multifaceted impact. Against an increasingly complex financial landscape backdrop, the study aims to unravel the intricacies of AI integration in compliance models, juxtaposing traditional methodologies with cutting-edge AI-driven approaches. The scope of the paper encompasses a systematic literature review and qualitative analysis, focusing on the evolution of AI in financial services, its necessity for enhanced compliance efficiency, and a comparative analysis of traditional versus AI-driven compliance models. The study synthesizes findings from diverse peer-reviewed articles, case studies, and comparative analyses by employing a meticulous methodology. It illuminates the state-of-the-art AI technologies in financial compliance, evaluates their effectiveness in various regulatory contexts, and identifies key performance indicators for AI compliance. The paper also critically examines the challenges and limitations observed in AI compliance solutions alongside emerging trends and future directions. The main conclusions reveal that AI significantly enhances compliance efficiency and accuracy, adeptly addresses complex regulatory challenges, and has strategic implications for financial institutions. However, the study also highlights the need for balancing innovation with regulatory and ethical compliance. Recommendations include the adoption of proactive regulatory frameworks, stakeholder engagement, and the development of robust AI governance models. This paper contributes to the academic discourse on AI in financial services, guiding policymakers, regulators, and industry practitioners. It advocates for a harmonized approach to AI integration, ensuring responsible and effective utilization in the financial sector. Keywords: Artificial Intelligence, Financial Regulatory Compliance, Systematic Literature Review, AI Technologies, Regulatory Challenges, Strategic Implications.

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Integrating blockchain and deep learning for intelligent greenhouse control and traceability

Frikha

Ktari

Zalila

et al. 2023

Alexandria Engineering Journal

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A Survey on AI Implementation in Finance, (Cyber) Insurance and Financial Controlling

Cited by 5 publications

References 42 publications

Investigating the Application of Digital Tools for Information Management in Financial Control: Evidence from Bulgaria

Investigating the Application of Digital Tools for Information Management in Financial Control: Evidence from Bulgaria

Automating Financial Regulatory Compliance With Ai: A Review and Application Scenarios

Integrating blockchain and deep learning for intelligent greenhouse control and traceability

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