Prompt engineering improves AI outputs by designing clearer questions and supplying relevant context. In financial research, it shifts LLM use from generic stock recommendations toward structured due diligence, such as examining a company’s management style and building a personal investment scorecard. section 8.0 section 8.4
A stronger prompt can specify:
- The investor’s goals, risk tolerance, and tax residency. section 8.5
- The company, decision, or research question being investigated. section 8.0
- Reference examples and enough surrounding context to avoid a generic answer. section 8.4 section 8.5
From recommendation to due diligence
Instead of asking, “Recommend me three stocks,” ask an LLM to describe the management style of a named company, while providing the investor’s goals and risk profile. Compare the resulting details with other research before using them in a personal scorecard. section 8.0 section 8.5
Prompt engineering refines research; it does not replace judgment. LLMs can hallucinate, provide outdated information, or make mistakes, so their outputs require due diligence rather than automatic acceptance. section 8.0 section 8.5
