A Detailed Study on Machine Learning Techniques for Data Mining

Research focus

Data mining extracts useful information and patterns from large volumes of data. The paper examines Knowledge Discovery in Databases and compares classification, clustering and regression approaches, including their advantages and limitations.

Agentic AI for decision-ready data intelligence

Agentic AI adds an action layer to traditional data mining. Instead of stopping at patterns or predictions, intelligent agents can investigate anomalies, select suitable analytical methods, combine signals from multiple sources, explain findings and trigger next-best actions for insurers and financial-service teams.

What this means for insurers

• Build reusable domain intelligence instead of isolated AI use cases.
• Connect structured and unstructured data to contextual decisioning.
• Continuously improve knowledge and recommendations with governed feedback loops.
• Keep humans in the loop for high-impact decisions and exceptions.