CAMS · Question #779
A financial institution plans to implement adverse media screening with Artificial Intelligence (AI)/Machine Learning (ML) capabilities During testing, the system produces high volumes of irrelevant…
The correct answer is D. Adjust AI/ML models to focus on high-risk keywords/phrases from reputable media sources. The most effective way to reduce irrelevant results in AI/ML-driven adverse media screening is to fine-tune the models to prioritize high-risk keywords and reliable sources. This improves precision by filtering out noise and directing focus toward content that is more likely to…
Question
A financial institution plans to implement adverse media screening with Artificial Intelligence (AI)/Machine Learning (ML) capabilities During testing, the system produces high volumes of irrelevant news articles for review. What is the best way to address this issue?
Options
- ANarrow the media sources to avoid unrelated articles
- BRely on manual filtering by investigators
- CIncrease the frequency of updates to media sources
- DAdjust AI/ML models to focus on high-risk keywords/phrases from reputable media sources
How the community answered
(39 responses)- A13% (5)
- B3% (1)
- C5% (2)
- D79% (31)
Explanation
The most effective way to reduce irrelevant results in AI/ML-driven adverse media screening is to fine-tune the models to prioritize high-risk keywords and reliable sources. This improves precision by filtering out noise and directing focus toward content that is more likely to indicate financial
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