Developing a Compliance Model for AI-Driven Financial Services: Navigating CCPA and GLBA Regulations

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@article{1707092,
      author = {Grace Annie Chintoh, Osinachi Deborah Segun-Falade, Chinekwu Somtochukwu Odionu, Amazing Hope Ekeh},
      title = {Developing a Compliance Model for AI-Driven Financial Services: Navigating CCPA and GLBA Regulations},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {10},
      pages = {468-476},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707092.pdf},
      abstract = {Integrating artificial intelligence (AI) in financial services offers transformative opportunities, enhancing efficiency, customer experience, and decision-making processes. However, the adoption of AI also introduces significant compliance challenges, particularly under stringent regulatory frameworks such as the California Consumer Privacy Act (CCPA) and the Gramm-Leach-Bliley Act (GLBA). This paper explores the regulatory landscape and its implications for financial institutions adopting AI technologies. It identifies key challenges, including data privacy, security, transparency, and bias, and proposes a conceptual compliance model centered on data governance, risk management, and audit mechanisms. The model integrates privacy-by-design principles, robust risk assessments, and mechanisms to ensure AI transparency and fairness. Additionally, it addresses scalability and adaptability, enabling institutions to align with evolving regulations and advancements in AI. The paper concludes with actionable recommendations for financial institutions, regulators, and AI developers and suggests future research directions to navigate emerging technological and regulatory complexities.},
      keywords = {Artificial Intelligence, Financial Services, Compliance Model, Data Privacy, Regulatory Challenges, CCPA and GLBA},
      month = {April},
  }