Testing GenAI in Asset Management: Automating Compliance Review
How do you test GenAI in a real-world asset management setting?
At Optimus E2E Consulting we deliver solutions for asset management firms. Here is a Proof-of-Concept from one of our most popular requests — to review and automate compliance processes.
📄 The Challenge
Could we parse complex regulatory disclosures and check them — clause-by-clause — against internal sustainability guidelines?
⚙️ What We Built
A modular GenAI app that:
- Parses legal text into structured clause objects (LLM → JSON)
- Parses firm guidelines the same way
- Uses a map-reduce LLM approach to match clauses to rules
- Generates a compliance report with ✅/❌ flags and confidence scores for human review
🧠 Key Takeaways
- Document parsing is improving fast, but you still need to customise approaches to ensure you capture required details from complex docs.
- It's not just about matching — naive top-X scoring can over-apply rules. You need more intelligent logic (vector similarity, or a second LLM pass) to check.
- Confidence scores are critical — a human-in-the-loop is still needed to judge edge cases and sign-off.
- But GenAI has the potential to cut manual review time and cost significantly.
💸 The Economics Are Shifting
High-end LLMs bring better accuracy — but also higher inference costs. The cost/quality/speed trade-off matters, especially for scaling. But those costs keep falling fast.
🛠️ Proved With
- MistralAI & OpenAI (structured outputs & parsing)
- LlamaIndex foundational layer
- FastAPI backend + React frontend
Broad Applicability
This approach has broad applicability: fund & legal docs, ESG policies, mandates — any situation where contractual intent needs to align with internal rules or guidelines.
If you're thinking about how GenAI could be safely and practically applied inside your firm — happy to swap notes or show a demo.