Or how hybrid workflows lead to greater precision and control in risk assessment
Why purely automated approaches are often insufficient
Especially in asset management—and particularly in risk assessment—blind trust in fully automated systems is the wrong approach.
- Regulatory requirements change quickly.
- Documents are often inconsistently structured or contain complex wording.
- Risk evaluation requires professional judgment that cannot be inferred from data alone.
Pure AI models (e.g., LLMs or rule-based systems) can handle large portions of the work, but they reach their limits when context, experience, or company-specific nuances are decisive.
The strength of hybrid approaches
Hybrid workflows combine automated AI analysis with targeted human expertise, achieving the best mix of speed, precision, and regulatory assurance.
Building blocks of a hybrid risk assessment workflow
- Automated pre-screeningAI extracts relevant passages from contracts and risk reports.Initial categorization (e.g., Low / Medium / High Risk) based on predefined criteria.
- Rule-based safeguardsCross-check against regulatory requirements and internal risk policies.Clearly defined “red flags” are always highlighted, regardless of the AI model.
- Human expert reviewExperts validate critical points flagged by the AI.Context-driven decisions are documented.
- Feedback loop to the AIExpert decisions are fed back into the system.Models learn continuously, increasing the automation rate over time.
Benefits for risk assessment
- Minimized error rate: AI reduces human oversight errors, while experts prevent AI misjudgments.
- Higher compliance assurance: Combination of automatic detection and human plausibility checks.
- Improved auditability: Every decision is traceable—whether made by human or AI.
- Scalability without loss of control: Even with rising document volumes, review depth remains constant.
Practical example
An asset manager reviews several thousand fund prospectuses and issuer reports each year.
With a hybrid workflow:
- Manual reading time per document is reduced by 60–70%.
- The hit rate for potential risks increases by up to 40%.
- Regulatory changes can be integrated into the review system within days—rather than weeks.
Conclusion
Hybrid AI approaches in asset management are not a compromise, but the optimal strategy to combine efficiency and regulatory security—especially in risk assessment, where trust and traceability are top priorities.
