THOUSANDS OF TRANSACTIONS. WHICH ONES ACTUALLY NEED INVESTIGATION?
Teams spend time reviewing large volumes of activity with inconsistent prioritization.
01The problem
Review teams can spend large amounts of time examining cases or transactions with inconsistent prioritization.
02Baseline
Rules may generate broad queues; analysts manually gather context; high-value human judgment is consumed by low-value review.
03Root cause
Detection and prioritization are not the same problem. Teams need context-rich ranking that helps decide what deserves human attention first.
04SMART target
Illustrative target
Improve review prioritization and reduce unnecessary manual investigation while preserving human decision authority.
05Solution
Combine transaction/case history, business rules and relevant features; score/rank exceptions; present context and evidence; route prioritized cases to human review.
06Architecture
- Transactions / Cases + History + Rules
- Feature / Context Layer
- Risk or Priority Scoring
- Ranked Queue + Evidence
- Human Review
- Disposition
- Feedback
0790-day proof
Use historical/controlled data, define review outcomes, compare baseline queue quality with proposed prioritization, pilot with reviewers and measure precision, workload and usability.
08Business case
How value would be calculated — assumptions, not claimed savings
Review hours avoided + faster high-priority intervention + operational/risk value − implementation/run cost.
09Guardrails
- Human decision authority
- Explainability/context
- Bias/fairness review where applicable
- Privacy/security
- Audit trail
- No autonomous regulated decision without appropriate controls.