Manual review is the process where a human analyst evaluates a business verification case that couldn't be resolved through auto-verification. Manual review applies human judgment to ambiguous data, complex situations, and cases requiring investigation.
When Manual Review Is Needed
Auto-Verification Escalations
Cases escalate to manual review when:
- Data doesn't match cleanly across sources
- Risk rules trigger but aren't definitive
- Required information is missing or unclear
- Conflicting signals need interpretation
Mandatory Review Scenarios
Some situations require human judgment by design:
- High-risk industries or transaction volumes
- Enhanced due diligence requirements
- Adverse media or watchlist matches
- Complex ownership structures
- Regulatory requirements for human oversight
Common Escalation Triggers
Name mismatch: "ABC Corp" vs "ABC Corporation LLC"
Address discrepancy: Different addresses across sources
Status uncertainty: Recently changed status, unclear records
Risk signal: Industry flag, geographic concern
Thin data: Micro-business with limited records
Ownership complexity: Multiple layers, international entities
The Manual Review Process
Typical Workflow
- Queue assignment: Case enters analyst queue
- Initial assessment: Analyst reviews available data
- Investigation: Additional research as needed
- Decision: Approve, decline, or request more information
- Documentation: Record reasoning for audit trail
- Action: Trigger downstream processes
What Analysts Review
Submitted information:
- Application data provided by the business
- Supporting documents (if collected)
- Applicant communication history
Retrieved data:
Risk indicators:
- Why the case escalated
- Red flags identified
- Comparison to similar cases
Decision Options
Approve: Business passes verification
Approve with conditions: Additional monitoring, limits
Request information: Need documents or clarification
Decline: Business fails verification
Escalate further: Needs senior review or legal input
Challenges in Manual Review
Consistency
Human reviewers may decide similar cases differently:
- Subjective interpretation of ambiguous data
- Varying risk tolerance among analysts
- Inconsistent application of guidelines
- Decision fatigue affecting quality
Speed vs. Thoroughness
Tension between:
- Completing reviews quickly (customer experience)
- Investigating thoroughly (risk management)
- Documentation requirements (compliance)
Analysts often work with incomplete information:
- Sources don't cover all businesses
- Data may be stale or conflicting
- Cannot independently verify some claims
- Must make judgments under uncertainty
Building Effective Manual Review
Clear Guidelines
Effective review processes include:
- Decision criteria for common scenarios
- Examples of approve/decline cases
- Escalation triggers and paths
- Documentation requirements
Quality Control
Maintaining consistency through:
- Sampling and audit of decisions
- Calibration sessions across team
- Feedback loops on outcomes
- Performance metrics beyond speed
Analysts need:
- Consolidated view of all data sources
- Easy access to additional research tools
- Clear workflow and queue management
- Documentation templates and audit trails
Training
Ongoing development on:
- New fraud patterns and risk indicators
- Regulatory changes and requirements
- Industry-specific considerations
- Using available tools effectively
Manual Review Metrics
Efficiency Metrics
Review time: Average time per case
Throughput: Cases completed per analyst
Queue depth: Backlog waiting for review
First-touch resolution: % resolved without re-queuing
Quality Metrics
Approval rate: % of manual reviews approved
Reversal rate: % of decisions later changed
False positive rate: Good businesses declined
False negative rate: Bad actors approved
Balancing Act
Optimizing one metric often hurts others:
- Faster review → potentially lower quality
- Higher approval rate → potentially more risk
- More thorough → longer queue times
Manual Review in Compliance
Documentation Requirements
Regulators expect:
- Clear reasoning for decisions
- Evidence of investigation performed
- Consistent application of policy
- Retrievable audit trail
Escalation Governance
Effective programs define:
- When to escalate to senior review
- When legal or compliance must be involved
- How to handle edge cases
- Appeals and reconsideration process
The Manual Review Funnel
In a well-tuned KYB program:
100% Applications
↓
[Auto-Verification]
↓
60-80% Auto-approved/declined
↓
20-40% → Manual Review
↓
Most resolved by analyst
↓
5-10% → Senior/escalated review
The goal is minimizing manual review volume while catching all cases that truly need human judgment.
Key Takeaways
- Manual review applies human judgment to cases auto-verification can't resolve
- Cases escalate for data mismatches, risk signals, or mandatory review requirements
- Consistency is a challenge—clear guidelines and quality control help
- Speed and thoroughness are in tension—balance based on risk tier
- Documentation matters for compliance—decisions must be auditable
- The goal is reducing manual review through better auto-verification while preserving quality
Related: Auto-Verification | Enhanced Due Diligence | Entity Verification
