The Rise of goAML: Part 3

December 12, 2017

In part 1 and part 2 of this blog series, we noted that Financial Intelligence Units (FIUs) around the globe are adopting the United Nations Office on Drugs and Crime's (UNODC's) goAML intelligence analysis system. But what does this mean for you?

Why goAML matters 

For goAML to be an effective reporting tool, the data that is submitted must be complete thorough and accurate. With FIUs in more jurisdictions adopting goAML—and given that the UNODC has taken a clear view that regulators are not responsible for data quality issues—it will fall to financial institutions to collect the appropriate data and to verify its quality.

Now more than ever organizations that complete and submit regulatory reports will have to make significant investments into improving the quality of their data, especially customer information.

Although customer data is collected during onboarding to fulfill know your customer (KYC) requirements, there are often issues around how the information is then maintained in order to always be current.

Call on technology to improve data

Technology can be leveraged in many areas to improve the quality of data recorded and maintained over time by financial institutions, including customer due diligence (CDD), sanctions screening and suspicious activity monitoring.

Data quality and customer due diligence

When completing KYC to onboard a customer, it’s necessary to identify a customer and then verify that they are, in fact, who they say they are. Performing CDD both verifies the customer’s identity and determines what is considered normal behavior and activity for that customer, helping to establish how risky that particular customer is.

Data analytics can be leveraged to ensure that all information has been verified and policies complied with during CDD and onboarding, thereby helping to improve the quality of data. The analytics can help ensure that:

  • CDD is thorough, leading to more accurate data
  • Customer information is logical and appropriate---for example, that all social security numbers have the correct amount of numbers
  • Accounts have been periodically subject to a refresh of CDD
  • Based on customer risk profiles, customer information is updated, with higher-risk customers being updated most frequently
  • All accounts have been assesses for risk and marked as a high, medium or low risk for AML risk, thus determining how much enhanced due diligence (EDD) should be performed

What sanctions screening can do for data quality and risk management

All customers should be screened against sanctions lists when they first open an account or just after to ensure that they are not a politically exposed person (PEP) or another type of high-risk client.

Preferably this screening is completed in real-time during onboarding, and then periodically thereafter as a customer can become a higher risk over time.

Information can be checked against both internal and externals lists such as OFAC and OSFI, as well as against third-party lists like the Refinitiv World-Check database and Dow Jones.

Better data leads to better suspicious activity monitoring

High-quality data is essential when it comes to monitoring for suspicious activity. Effective transaction monitoring systems require as much accurate information as can be gathered, including data on the customer him/herself as well as the accounts, products, financial institutions and jurisdictions involved.

Linking transactions that are indicative of patterns related to various financial crimes can be missed or overlooked when KYC data from multiple branches are not funneled into a single database and scrubbed for accuracy and consistency.

Small issues—missing fields, extra punctuation, spelling errors and wrongly interpreted abbreviations, for example—can make it challenging or can even prevent an AML system from detecting transactions that should be reported.

In addition to poor internal customer data, working with non-traditional financial institutions such as money services businesses (MSBs) or with a correspondent bank, introduces further opportunities for problematic information.

Organizations such as these may bring with them missing, inconsistent or duplicate data, or may have introduced errors simply through manual data entry, all of which can reduce the quality of data and lead to overdue regulatory reports.

Technology can be relied on in all of the cases to help identify and fill in gaps in data, and to correlate multiple transactions that, once aggregated, may exceed reporting thresholds and must be reported.

Improve Data Quality, Decrease Regulatory Reporting Problems

With goAML being implemented in increasing numbers by countries such as Ireland, New Zealand and Mexico, AML compliance departments will be expected to understand the solution and ensure that the quality of their data is as high as possible to avoid fines and penalties for not meeting reporting requirements.

To learn more about how technology can help improve the quality of your data—and can even complete and submit goAML reports—contact us at

About Anu Sood 

Anu Sood (LinkedIn | Twitter) is the Director Marketing at CaseWare RCM and is responsible for the company’s global marketing strategy. She has over 20 years of experience in product development, product management, product marketing, corporate communications, demand generation, content marketing and strategic marketing in high-tech industries.

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