For companies to comply with AML regulations, they are required to have a monitoring system to:
- Review Transactions.
- Calculate how potentially fraudulent a transaction is.
- Create risk alerts and compile them into cases.
What is Bad Data?
How does Bad Data occur – The Causes?
However, companies now are required to collect data as part of AML compliance and other financial regulatory compliance. Therefore, data collection has become more complicated, which means that to be able to fix dirty data, you must first understand the cause:
- Inaccurate data: Incorrectly entered or maintained information.
- Missing Data: There are empty fields with missing information.
- Poor data entry: Spelling mistakes, substitutions, and differences in spelling, naming, or formatting.
- Non-conforming data: Data which is not standard to the system of records.
- Inappropriate data: Submitting information in the wrong field.
- Duplicate data: Entering the same information under multiple fields.
What are some additional causes of bad data?
How does bad data affect AML compliance?
- Results in an excessive amount of false positives
- Creates the need for additional due diligence
- Creates missing opportunities for identifying/detecting real hits
- Generating an excessive number of false positives