Review of Explainable AI and Data Security in Financial Decision-Making

A review project by Godwin Chakkappan, last updated on 2026-05-27, aims to interpret and identify gaps in knowledge regarding data security and Explainable AI technologies used for decision-making in the finance industry. It examines methodologies, technologies, and approaches for optimal decision-making alongside data security.

Use Cases

• Identifying research gaps in financial data security based on the review's analysis of existing knowledge.
• Comparing methodologies for secure and explainable decision-making in finance based on the described review of technologies.
• Informing future research directions in AI-driven finance based on the project's insights into security and privacy issues.

Strengths

• Project focuses on a specific, high-impact domain combining Explainable AI, big data analytics, and financial security.
• Explicitly aims to provide insights for future research in the relevant field.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

figshare, author Godwin Chakkappan

Collection Method

Likely a literature review or synthesis project, as described.

Freshness

Last updated 2026-05-27 01:54:40; freshness should be verified.