Compliance Performance Analysis

Compliance teams operate blind to their own operational efficiency - spending 30-50% of their time on manual remediation, duplicate screenings, and low-value investigations without knowing which activities consume the most resources or which processes are broken. A compliance team that can't measure KYC completion times, screening false positive rates, or investigation backlogs can't optimize headcount, justify technology investments, or explain to the board why they need 3 more analysts. Without performance metrics, compliance is seen as pure cost center rather than scalable operations.

This solution measures compliance operations performance across all functions, identifies resource drains and process inefficiencies, and provides data to optimize team capacity and prove ROI on compliance investments.

WHAT DOES IT SOLVE?

KYC & Onboarding Performance

• Answers: How efficient is our KYC process, where are the bottlenecks, and how does performance vary by customer type?

• What it contains: KYC completion time tracking by customer segment and complexity; process bottleneck identification (document collection, verification, review, approval); abandonment rate analysis; staff productivity metrics; backlogs and queue monitoring; rework and rejection patterns; pass-through rates by verification stage

Sanctions & Screening Operations Efficiency

• Answers: How much time and cost do we spend on screening investigations, and where is effort wasted?

• What it contains: Screening alert volume and investigation time by vendor and list type; false positive rates and investigation outcomes; staff time allocation to screening tasks; hit-to-escalation conversion rates; investigation backlog and aging analysis; vendor performance comparison on operational efficiency

Customer Remediation & Data Quality Performance

• Answers: How effective are we at remediating data gaps and quality issues, and what's the operational cost?

• What it contains: Remediation case volume and completion rates; data quality issue categorization; time-to-remediation by issue type; staff effort tracking for remediation work; repeat remediation patterns indicating systematic issues; customer impact assessment

Compliance Case Management Performance

• Answers: How efficiently do we manage compliance investigations, and where are cases getting stuck?

• What it contains: Case volume, aging, and closure rates by type (AML alerts, screening hits, policy breaches); investigation time tracking from assignment to closure; case complexity analysis; escalation patterns; investigator productivity benchmarking; backlog risk assessment

Compliance Resource & Cost Analysis

• Answers: Where is compliance headcount going, and what's the cost per compliance activity?

• What it contains: Staff time allocation across compliance functions; cost per KYC check, screening investigation, and case review; headcount distribution vs activity volume; productivity metrics by team member; operational leverage analysis; overtime and capacity utilization tracking

CORE MODULES

Descriptive & Diagnostic

ADVANCED MODULES

Compliance Capacity Planning & Forecasting

• Answers: How will volume growth affect compliance headcount needs, and when will we hit capacity constraints?

• What it contains: Predictive modeling of volume growth vs headcount requirements; capacity constraint forecasting by compliance function; scenario planning under different growth and automation assumptions; ROI modeling for compliance technology investments; headcount vs technology trade-off analysis

Process Optimization & Automation ROI

• Answers: Which compliance process improvements deliver the highest ROI, and what should we automate first?

• What it contains: Prioritized automation opportunity identification with expected time savings; ROI calculations for process improvements (technology investment vs capacity freed); implementation complexity vs impact scoring; automation roadmap with quick wins vs strategic initiatives; vendor selection criteria for compliance tech

Compliance Quality & Risk Scoring

• Answers: Are we maintaining quality while improving efficiency, and where are the quality risks?

• What it contains: Quality scoring for KYC decisions, screening investigations, and case outcomes; error rate tracking and root cause analysis; regulatory risk assessment from quality gaps; quality vs speed trade-off analysis; continuous quality improvement tracking

Predictive & Prescriptive

DELIVERABLES

Built in PowerBI, Tableau, or Looker & adhering to client's brand book

Dedicated tab per analysis plus executive summary overview

AI-generated insights and recommended actions per analysis

SQL queries built in client's database system with controlled access

Python scripts for statistical and ML models (if applicable)

Added to client's GitHub repository, or delivered as standalone package

Technical Guide: Data sources, logic, formulas & maintenance procedures

Analysis Handbook: Metric definitions, interpretation, use cases & action framework

Dashboard

Code Base

Documentation

Knowledge Transfer

Live & Recorded walkthrough of dashboard functionality and insights

Q&A session covering methodology, use cases, and recommendations

30-day post-delivery support for questions and adjustments

MAIN REQUIREMENTS

• Transaction and operational data must be accessible in a relational database

• BI Platform Subscription with data base gateway for dashboard automation.

• Relevant APIs & ETL workflows should be functional and consistent.

Data Infrastructure*

• KYC & Onboarding Data - onboarding records with timestamps per stage, document submission logs, verification outcomes, staff assignments

• Screening & Alert Data - with investigation outcomes, time spent, disposition decisions, escalation records

• Case Management Data - Investigation cases with creation/closure dates, case types, investigator assignments, outcomes, and status updates

• Staff Activity Data - Time tracking or task logs by compliance function, team member assignments, productivity records

• Remediation & Quality Data - Data quality issues, remediation requests, correction records, audit findings, QA outcomes

Data Sets

*Data infrastructure set up is out of scope. It can be provided as a separate engagement.