Chae Jun calls for AI agent research model in finance

Yuanta Securities outside director and Seoul National University business professor Chae Jun is urging a structured AI agent-based research model for financial investing, built through cooperation among financial firms, universities and AI companies. The approach is meant to automate data gathering and risk monitoring, not make direct investment decisions, as Korea’s markets grow more complex.

Why it matters: - AI agents are moving from general workplace automation into finance, where faster analysis and risk monitoring can affect research quality and investor decisions. - Chae Jun’s proposal points to a model that supports independent judgment instead of replacing analysts, which could shape how Korean financial firms adopt AI. - The plan also highlights the need for security, privacy and regulatory compliance as AI use expands in capital markets.

What happened: - Chae Jun, a Seoul National University business professor and outside director at Yuanta Securities, called for an AI agent-based financial research model built through institutional cooperation. - The proposal was framed around Korea’s increasingly complex capital markets, with high interest rates, won volatility, global capital flows and policy shifts affecting the investment landscape. - The article was published Sept. 29, 2026, in Seoul.

The details: - The proposed “agent training plan” is not designed to let AI make investment calls or recommend stocks. - The system would automatically collect and analyze corporate disclosures, financial statements, market news and macroeconomic indicators. - The goal is to give researchers and investors a more structured support layer for analysis and risk monitoring. - The cooperation model would bring together financial institutions, universities, AI technology companies and education providers. - Proposed workstreams include real-time integration of corporate disclosures, financial data, market data and macroeconomic indicators. - Another workstream would use AI agents to support company and industry analysis, market volatility monitoring and early detection of risk factors. - The project also includes investor education tools so users can learn to analyze financial statements and company value on their own. - The model would combine securities firms’ practical experience, universities’ academic capacity and AI companies’ technical expertise to test the framework. - The project would proceed in stages with accuracy and safety as the top priorities. - Data security, personal information protection, financial regulation compliance and verifiable analysis results are treated as required conditions for adoption.

Between the lines: - The pitch reflects a broader shift in Korean AI strategy, where the focus is moving beyond large language models and text generation toward task automation and industry-specific AI transformation. - Government support is also accelerating, including the Ministry of Science and ICT’s push for the “K-AI” large-scale project. - In finance, the strongest near-term use case appears to be research assistance rather than autonomous trading, which lowers regulatory and operational risk.

What's next: - The proposed collaboration would need to be validated across financial, academic and technology partners before it could become a working model. - Any rollout will likely depend on how well the system proves accuracy, safety and compliance in real market conditions. - If adopted, the framework could become a template for AI-assisted research across Korean capital markets.

The bottom line: - Chae Jun is pushing a finance AI model built to help humans analyze better, not to replace human decision-making. That distinction is likely to matter as Korean firms race to deploy AI in more regulated industries.