Banks spend billions each year combating financial crime through anti-money laundering (AML) and fraud prevention efforts, such as customer due diligence and data-sharing initiatives. They work closely with regulators like the Financial Conduct Authority (FCA) and the National Crime Agency (NCA) to exchange intelligence and develop more effective defences against criminals exploiting financial services. They invest in software solutions and implement proactive measures to detect and disrupt illicit activity. However, achieving quick returns from such investments remains a challenge due to several hurdles.
For example, many teams get bogged down by workflows relying on disparate tools, spreadsheet-based reconciliations, and manual reviews. A typical mid-size bank might use separate systems for transaction monitoring, sanctions screening, case management, KYC checks, etc., with little integration. Teams spend a lot of time exporting data from one tool and importing into another, or copying information to local drives - a perfect recipe for errors and delays.
Tackling the quality of source data is the other significant problem which can catch organisations off guard. Successful projects typically define clear benchmarks to assess whether incoming data is fit-for-purpose and continuously monitor its quality during the transformation phase. Checks might include validating date ranges, row counts, and acceptable levels of missing values. In some cases, missing data in specific fields may be of particular interest as it may even signal suspicious activity. While completeness is important, other dimensions like validity and consistency are equally critical. Any data quality issues discovered during processing must be addressed appropriately.
A lot has been written already about the vast range of SAS Viya platform capabilities but when it comes to SAS industry solutions in specialist areas such as Risk, Fraud and Public Security, the volume of information shared about best practices and the relevance of core platform capabilities in this context remain relatively low. I aim to redress this imbalance through this mini-series of posts and share some practical examples of how our customers are adopting innovative ways to generate value for their business. My next post will describe a unique approach using SAS Solution Factory that enables faster time to value with SAS industry solutions through configuration artifacts rather than writing custom code for each individual deployment.
