Optimize Your AML Compliance with Better Data
If you feel like you have no control over the quality of your input data, you’re not alone. High-quality customer data is essential to reduce false positive rates and the risk of missing a true hit. We bring decades of experience in data management to help you assess and improve your data integrity and continuously monitor for errors in customer data feeds—getting you better results, faster.
.png)
.png)
Level-up Your Data for Stronger AML Compliance
Backed by 50 years of experience in data, FinScan can help you effectively optimize your data so that it no longer holds back your AML screening. Achieve compliance-centric data quality in less than 20% of the time and at 50% of the total cost of other providers.
Assess Data Quality for Compliance
Understanding your data quality and the recommended next steps are crucial to address issues that expose you to financial risk. Knowing the true condition of your data is the first step towards mitigating AML risk.
-
Explore the quality of your underlying data
-
Uncover the data errors, gaps, and duplicates
-
Get started quickly and easily
A GLOBAL FINANCIAL SERVICES FIRM
46K misplaced names identified, 560K false matches eliminated
-
misplaced names, now screened, identified 407 actual sanctions matches
-
20% of false matches eliminated saved 1.8 FTE in resources
A LEADING UNDERWRITER
FinScan consistently caught more than 38 algorithmic variations
-
phonetic algorithms, date shifts, character mapping, abbreviations, concatenations, and transliteration and translation errors
A LARGE SHIPPING COMPANY
93% reduction of existing near matches
-
solved data quality issues caused by inconsistent notations
-
fine-tuned matching scenarios and precise watchlist pre-filtering
Real-time API-based screening, where automated parsing creates sub-records to catch true hits
A TECH-FORWARD SPONSOR BANK
Reduced False Positives by 74%
-
dropped noise words, incorporated spelling variations & cultural naming conventions
-
fuzzy match capture improved from 82% to 93%
Achieved 60 ms end-to-end latency per transaction
A GLOBAL FINANCIAL SERVICES FIRM
46K misplaced names identified, 560K false matches eliminated
-
misplaced names, now screened, identified 407 actual sanctions matches
-
20% of false matches eliminated saved 1.8 FTE in resources
A LEADING UNDERWRITER
FinScan consistently caught more than 38 algorithmic variations
-
phonetic algorithms, date shifts, character mapping, abbreviations, concatenations, and transliteration and translation errors
A LARGE SHIPPING COMPANY
93% reduction of existing near matches
-
solved data quality issues caused by inconsistent notations
-
fine-tuned matching scenarios and precise watchlist pre-filtering
Real-time API-based screening, where automated parsing creates sub-records to catch true hits.
A TECH-FORWARD SPONSOR BANK
Reduced False Positives by 74%
-
dropped noise words, incorporated spelling variations & cultural naming conventions
-
fuzzy match capture improved from 82% to 93%
Achieved 60 ms end-to-end latency per transaction
Ensure Match-ready Data for Compliance
Data quality issues can impair the effectiveness of any matching technology and your ability to detect risk. Quickly and easily resolve data errors, gaps, and inconsistencies continuously to prepare your data for AML compliance and KYC onboarding efforts with minimal effort.
-
Improve screening results
-
Reduce false positives/negatives
-
Save valuable time and resources
