How to Leverage Paxata for Timely Anti-Money Laundering Investigations
By Mike White
One of the biggest hurdles faced by many enterprises today is simply getting data ready for analytics and decision-making. Bringing together multi-structured datasets from diverse sources, profiling it, cleansing it, and shaping it are just a few of the challenging tasks that plague modern enterprises across all industries.
To illustrate this point, let’s take a look at the financial services industry. A critical business process within every financial institution is compliance with Anti-Money Laundering (AML) regulations. In order to effectively conduct precise, ongoing investigations of accounts with transaction patterns that indicate potential money laundering, banks need to possess complete knowledge of their clients and continually monitor and measure their activities. This should be a repeatable and auditable process that doesn’t require heavy dependence on technical tools and resources.
This requires banks to address some common and critical data challenges, including:
– High volumes of data, such as transaction files from data lakes
– Combining data from multiple sources, such as a database which contains the high-risk accounts and Federal Reserve information which may come in an XML format from an external source
– Filtering out noise in the data and addressing data quality issues, such as unstandardized values, missing values, unexpected anomalies, duplicates, and inconsistencies
The video below demonstrates how Paxata’s Adaptive Information Platform integrates and transforms raw data into serviceable information to support timely and accurate AML investigations.