The Top Item for Your Anti-Money Laundering List: Clean Data
July 06, 2021
The Overwhelming Volume of Suspicious Activity Reports Makes One Thing Clear: Get Your Data Ready for RegTech
There’s a vast disconnect between the bleeding edge of technology and the financial infrastructure on the ground.
Most average Americans would be shocked by how much inefficiency remains in the typical financial organization. Not only are we still waiting for jet packs, we’re still waiting for a lot of basic automation.
Fragmented data sources from legacy systems have been hobbling our forward progress. Whether you build a solution or buy it from a third-party, for most any purpose, you’ll need to feed it data. And the quality and value of the solution outputs depend on the organization and accuracy of the inputs.
BSA/AML compliance suffers from a lot of noise-to-signal. You could go through the motions, check the boxes, and call it good enough. This understandable, too prevalent approach results in a FinCEN SAR flood. At the agency level, there’s a whole other host of modernization challenges to overcome in sifting through all the suspicious activity to find the reports worth further action.
To embrace the meaningfulness in anti-money laundering work – to make the know-your-customer (KYC) processes, AML investigations, transaction monitoring, and
suspicious activity reports really count – we need to hone in on the information that could lead law enforcement to criminals.
The very first step towards that goal involves cleaning the data.
Waves of M&A consolidation over the last several decades have led to disparate sources of raw data locked up in legacy systems and proprietary formats. Recently many of the larger banks have been investing in migrations to “data lakes” – consolidated warehouses of unstructured data where modern APIs, scripting, and analytics are possible. This is a very good development for AML in financial services.
The scope of a financial institution’s data problems can be overwhelming. To break the challenge down into manageable steps, here are a half-dozen AML data focal points:
- Structured insights: Ensure that investigator insights such as categorizations, decisions and other findings are captured as structured data that can be parsed for analytics.
- Machine-readable formats: Store supporting documentation in a centralized repository in machine-readable formats. Spreadsheets and tabular data are much easier to work with than written documents or proprietary formats like PDFs.
- Standardized schemas: Organize case information into a standardized data schema, adding structure to things like subject profiles, transactions, account information, addresses, and device information (such as IP addresses).
- Modern APIs: Ensure that tools you use for regulatory compliance have modern APIs that are well documented and kept up to date.
- Summarized extracts: Choose tools that go beyond charts and graphs and provide summarized data extracts in tabular or machine-readable formats – for example, APIs or .csv downloads of important case information and findings.
- Interoperability: Look for systems that can natively connect your case findings back to the case sources. For example: Does the compliance management system take in transaction monitoring alerts, and then allow you to see the outcomes for those alerts in a structured format?
Improving the quality of existing and expanding datasets will be well worth the effort for effective AML reporting. Preparing data to leverage RegTech will free compliance teams from the existential dread of pointless tasks, and then fill our work lives with meaning and purpose as the clean data points us to the dirty money.
SARs are the main communication channel in the fight against financial crime, but they can be tricky. Our APIs for SAR filing handle the heavy lifting, so you can focus on investigations. Learn more.