Sanctions & Screening Coverage Analysis

Most fintechs use multiple screening vendors (sanctions lists, PEP databases, adverse media) but have no visibility into coverage gaps, vendor overlaps, or comparative false positive rates. It's common to pay for redundant coverage across 3-4 vendors while potentially missing high-risk individuals who fall through the cracks. Compliance teams can't confidently answer "are we screening everyone we should be?" or "which vendor is actually adding value?" without manually analyzing thousands of screening results.

This solution maps complete screening coverage, identifies both gaps and expensive redundancies, and benchmarks vendor performance on match quality and false positive rates.

WHAT DOES IT SOLVE?

Screening Coverage Analysis

• Answers: What's our complete screening coverage across all vendors, and where are the gaps?

• What it contains: Coverage mapping across all vendors and watchlist types; sanctions list coverage comparison; PEP database scope analysis; adverse media source inventory; geographic and entity-type coverage assessment; gap identification for uncovered risk areas

False Positive Analysis by Vendor

• Answers: Which vendors generate the most noise, and what's the true hit-to-investigation ratio?

• What it contains: False positive rates by vendor and list type; match quality assessment and scoring; investigation time tracking per vendor; hit-to-SAR conversion rates; alert quality benchmarking

Vendor Performance Comparison

• Answers: How do vendors compare on effectiveness, efficiency, and cost?

• What it contains: Hit rate comparison across vendors; data quality and coverage assessment; cost per screening & per true hit; vendor API reliability & performance; value-for-money analysis

Screening Workflow & Efficiency Analysis

• Answers: How efficient is our screening process, and where are the operational bottlenecks?

• What it contains: Screening volume and processing time analysis; investigation workflow efficiency; backlog and queue analysis; staff productivity metrics; process bottleneck identification

CORE MODULES

Descriptive & Diagnostic

Vendor Consolidation Decision Support

• Answers: Which vendors should we keep, consolidate, or replace for optimal coverage and cost?

• What it contains: Optimal vendor configuration recommendations; consolidation scenario modeling with coverage impact; expected cost savings from rationalization; migration planning and risk assessment; ROI projections for vendor changes

Coverage Risk Assessment & Mitigation

• Answers: What's our exposure from coverage gaps, and how do we close them cost-effectively?

• What it contains: Quantification of coverage gap risk exposure; high-risk entity identification in gaps; minimal vendor set recommendations for complete coverage; risk mitigation strategies and implementation priorities

Screening Optimization & Threshold Tuning

• Answers: How should we configure screening rules and thresholds to reduce false positives while maintaining coverage?

• What it contains: Optimal threshold recommendations by vendor and list type; rule configuration optimization; fuzzy matching calibration; expected false positive reduction; regulatory compliance validation for threshold changes

ADVANCED MODULES

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*

• Screening Results Data - All screening hits and matches from all vendors with match scores, list types, and disposition outcomes

• Investigation & Resolution Data - Investigation outcomes, true positive vs false positive classifications, SAR filings, and resolution times

• Vendor Configuration & Costs - Active screening vendors, watchlist subscriptions, API configurations, and vendor fees

• Screened Entities (customers, beneficiaries, counterparties) including screening frequency, and risk classifications

Data Sets

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