Paradigm Shift: AI-based Data Quality Controls for AML Compliance

How compliance can take control of their data.

Recent regulatory requirements and enforcement actions show that not having effective data quality controls in place is a major roadblock to successful compliance for the financial services industry. Duplicate records, inconsistent formats, misplaced customer names – the list goes on – all lead to increased risk or false positives. Yet, until now, Compliance hasn’t had control over their data used for screening.

Bad Data = Bad Compliance.
Will your data be an asset or a liability?

Now there are compliance-specific, AI-based data quality controls available that enable compliance departments to make their data fit for compliance screening purposes.

We will examine the everyday AML problems caused by bad data and discuss compliance-specific best practices and automation tools you can use to improve the effectiveness of your data and internal controls/procedures.

Topics include:

  • Common AML screening challenges caused by bad data
  • Identifying the root causes of your data problem
  • Establishing specific data quality controls to make sure your data is always compliance-ready

Presented by:

Kieran Holland
Kieran Holland
Head of Technical Solutions FinScan
Carl Case
Carl Case
Advisory – Financial Crimes Technology Ernst & Young
Michael Schidlow, Esq., CAMS-Audit, CFE
Michael Schidlow, Esq., CAMS-Audit, CFE
Financial Crime Compliance Advisory and Training Specialist