Research Suitability
Description
The AI is intended to reduce the manual workload involved in reviewing and scoring materials used for symposiums. Evaluators currently spend considerable time assessing relevance, quality, and technical rigor. The AI helps streamline this process by providing an initial, consistent rating that supports quicker filtering and prioritization.
Detailed example
The system generates a rating or score for each material artifact, along with brief reasoning based on relevance, technical execution, and alignment with the symposium’s thematic criteria. These outputs act as a first-level filter to support reviewers in identifying papers that merit further consideration.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
By speeding up the presentation reference material selection process, the AI allows subject-matter experts to focus on deeper evaluation rather than preliminary screening. This improves efficiency and helps ensure that high-quality, policy-relevant research is highlighted for symposiums, ultimately supporting better-informed supervisory and regulatory perspectives that benefit the broader financial system and the public.
Audit / financial statement impact
This use case assigns ratings to research papers and is a solely internal analytical task.
Controls / human review
ATO: Not reported; PIA: Not published