Concerns related to data privacy, cybersecurity

The gap

Evidence profile

Sourced from the recommendations and limitations section and future-work section of the source papers, classified as general, spanning 4 journals.

Supporting evidence — 4 representative gaps

• Research on Personalized Asset Allocation Using AI Agents in Robo-Advisory Scenarios (2026) · Journal of Computer Signal and System Research · doi

  Mitigation Strategy Robust encryption of financial data (e.g., income, assets 𝑎, risk tolerance 𝑟); strict access controls; continuous security monitoring and threat detection. Implement multi-factor authentication; regularly update security protocols; conduct penetration testing; incident response plan. Develop transparent data usage policies; obtain explicit user consent for data collection and processing; establish data subject rights processes (e.g., right to access, right to be forgotten). Employ fairness-aware AI algorithms; regularly audit AI models for bias; use diverse training datasets; establish explainability and interpretability of AI decisions; independent ethics review board. Improve transparency in AI decision-making processes; provide clear explanations of investment recommendations; offer human advisor oversight to provide reassurance and address user concerns.

  generalrecommendationsevidence 5/5
  Keywords: access security regularly user establish processes right provide mitigation strategy robust encryption financial income assets
• Artificial Intelligence for Financial Inclusion and Digital Banking (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Data privacy concerns and cybersecurity threats remain significant barriers to effective implementation. Algorithmic bias, regulatory issues, and digital literacy gaps are also significant challenges. The study highlights the importance of responsible AI governance and collaborative efforts among policymakers, financial institutions, and technology providers.

  generallimitations sectionevidence 5/5
  Keywords: data privacy concerns cybersecurity threats remain significant barriers
• A STUDY ON THE USE OF ARTIFICIAL INTELLIGENCE IN FINANCIAL DECISION MAKING (2026) · International Journal of Progressive Research in Engineering Management and Science · doi

  Concerns related to data privacy, cybersecurity, transparency, and overdependence on technology remain significant. Complete reliance on AI remains unlikely in the near future. Financial decisions often involve ethical considerations, emotional understanding, and interpretation of unexpected events that require human judgment.

  generallimitations sectionevidence 5/5
  Keywords: concerns related data privacy cybersecurity transparency overdependence technology
• Artificial Intelligence: Reshaping the Financial Market Landscape (2026) · International Journal of Science and Social Science Research · doi

  Future research should focus on developing frameworks for Responsible AI that emphasize fairness, transparency, and accountability. Future research should explore AI integration with block chain and decentralized finance (De-Fi) for enhanced efficiency. Future research should investigate how to build customer trust in AI by improving AI explanations and outcomes.

  generalfuture-work sectionevidence 5/5
  Keywords: future research focus developing frameworks responsible emphasize fairness

Questions about this gap