How to Defuse the Ticking Time Bomb of Bad Data in AML Compliance

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Accurate Data Reduces False Positives and Identifies Hidden Risks to Improve Watch List Screening Outcomes

There are countless ways data can become “bad” data. Whether it is due to siloed data sources across the enterprise, inflexible legacy systems that were not built to interact with modern day technology, lack of budget or resources to clean up years’ worth of inaccurate data entry, or simply human error, poor data quality is at the core of compliance screening problems that anti-money laundering (AML) professionals must deal with daily.

In most organizations, the data that AML departments receive was originally collected and processed for various business purposes other than compliance. Therefore, it’s no wonder that that same data causes numerous issues when brought together for compliance purposes such as sanctions and Politically Exposed Persons (PEP) screening.

Analysis of a Financial Institution’s Customer Data Prior to Screening

FinScan helps you identify a variety of errors in your organization’s data so that your data can be optimized for compliance screening.

Anti-money laundering officers, Bank Secrecy Act (BSA) officers, Money Laundering Reporting Officers (MLROs), and other compliance professionals are undoubtedly aware of problems with their data quality. In fact, according to a 2019 FinScan survey, a whopping 63% of compliance professionals reported lacking confidence in their data. Unfortunately, they may not have any direct influence or control over the quality of their internal data, leaving them powerless to resolve the complex problems that bad data can create.

Empowering Compliance Officers to Control the Quality of Their Data

FinScan, the AML compliance brand of data quality pioneer Innovative Systems, Inc. has brought to market a next-generation screening solution that employs the company’s decades of data management experience. With the new FinScan Premium solution, AML compliance departments can control the quality of their internal data being used to screen against sanctions, PEPs, and adverse media — ultimately improving their compliance processes and results.

This article discusses key information you need to know about the ticking time bomb of risk caused by bad data and what you can do to defuse the situation. We’re answering essential questions, including:

  • How large of a problem is bad data, and how does it impact regulatory compliance?
  • How can compliance departments improve their data quality to optimize risk management and compliance efforts?
False positives are reported as the number one issue across compliance departments. Keep reading to learn how FinScan can help you combat false positives and strengthen your overall efforts to fight against financial crime today.

The weight of all this bad data bogs down the entire AML/KYC screening process. Compliance specialists worldwide are struggling with too many false positives and a high backlog of alerts, which create regulatory risk and inefficiency.

The Traditional Approach to AML/KYC Screening No Longer Works

Typically, firms attempt to address these issues by tweaking their matching algorithm, buying the best regulatory list database, and applying new technologies such as artificial intelligence and machine learning. These efforts, however well-intentioned, do not address the root cause of the problem — the bad data itself.

The Advanced approach includes data quality optimization as part of the screening process. Without good data quality as the foundation, even adding technologies such as AI or machine learning will still result in inefficiency and undetected hidden risks.

Good Data is the Foundation of Effective AML Compliance

Data is the foundation of a firm’s compliance program. If the data is weak, all of these other strategies will yield results just as unsatisfactory as the first attempt. For this reason, addressing data quality is a critical component of the sanctions and PEP screening process. Not only will it save your organization from wasting time and resources by reducing false positives — it will also help you catch true hits you might otherwise miss before they can wreak havoc on your AML compliance.

Bad Data Can Have Big Consequences

Using clean data for compliance purposes not only increases productivity and minimizes a firm’s risk of doing business with bad actors — it’s also a regulatory requirement.

Consider these excerpted requirements from New York State’s Department of Financial Services Part 504 regarding Transaction Monitoring and Filtering programs:

  • Identification of all data sources that contain relevant data
  • Validation of the integrity, accuracy and quality of data to ensure that accurate and complete data flows through the Transaction Monitoring and Filtering Program
  • Data extraction and loading processes to ensure a complete and accurate transfer of data from its source to automated monitoring and filtering systems, if automated systems are used

Essentially, these regulations require financial institutions to put in place a robust process for screening and proving the quality of their data. Failure to comply with such regulations can result in sanctions breaches that involve public censure, fines, reputational damage, loss of consumer confidence, and even personal accountability.

Further, if your screening system cannot overcome your bad data, it will not bode well for your organization. For example, the US Treasury’s Office of the Comptroller of the Currency (OCC) has issued a Finding of Violation to JPMorgan Chase & Co. (“JPMC”) for violations of the Foreign Narcotics Kingpin Sanctions Regulations.


From approximately 2007 to October 2013, JPMC used a vendor screening system that failed to identify these six customers as potential matches to the SDN List. The system’s screening logic capabilities failed to identify customer names with hyphens, initials, or additional middle or last names as potential matches to similar or identical names on the SDN List.

These types of enforcement actions have historically originated in the US, but new EU and UK sanctions have led to recent increases in compliance enforcement around the world.

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When Bad Data Happens to Good People

If you’re struggling to maintain high quality data or achieve AML/KYC screening compliance, you are not alone. Many organizations have difficulty keeping their data clean. It’s challenging because data changes all the time. The average rate of data decay in an organization is 3% per month — or 36% per year — which means maintaining data integrity is a constant battle.

Your data will continue to deteriorate without a proper, continuous data optimization process, posing significant risk to your screening effort.

Average Data Error Rate Can Be As High As 50%

Even if an organization has a mechanism to ensure data integrity, at FinScan we have seen many cases where this still is not sufficient to bring the quality of the data to levels that will enable proper compliance with the latest laws and regulations. This is not a surprise given that organizations’ customer databases were built for business purposes other than compliance. Based on numerous assessments FinScan has conducted, we estimate that the average error rate in the data sets we encounter is an incredible 50% before we clean it.

Compliance Is Not Responsible for Their Organization’s Data Problems But Are Impacted By Them

The problem is not that compliance professionals are unaware of their poor data quality — it is that they simply do not have the time, resources, or ability to clean up the bad data entries that have accumulated in their systems over many years. The resources in their IT departments are dedicated to managing today’s challenges and pursuing future advancements, not fixing yesterday’s mistakes.

Unfortunately, in many firms, the reality is that the quality of client data is not even close to being good enough to enable an effective, efficient and compliant screening program.

Optimizing the Data for Compliance Screening

FinScan Premium takes that problem away by taking the raw data — or data that’s not fit for compliance purposes — and cleaning and optimizing it before it goes into the matching cycle, while leaving the actual source data in the same, unaltered format that it was.

In the words of Randal Skipper, president of worldwide field operations at FinScan:

“Rather than putting the onus back on the organization’s IT department to fix the data challenges that are causing risk issues for compliance teams, we are giving tools to the compliance teams themselves to address the problems.”

FinScan’s data quality engine cleanses your data before screening begins

FinScan’s data quality engine cleans your data before screening begins, which means you get more accurate results every time.

Defusing Bad Data with FinScan Premium

FinScan is a leading global provider of advanced AML and risk management solutions. Our roots are in the development of software for addressing data issues, making us uniquely positioned to provide comprehensive AML and watch list screening solutions that ensure the highest levels of data integrity.

We’ve taken our 50 years of experience in ensuring high quality data at financial institutions around the world and incorporated that into our FinScan screening solution for a seamless, accurate and efficient process.

FinScan Premium is an AML platform that utilizes artificial intelligence and the algorithmic learnings from over 100 billion data entries scanned every year and five decades of experience in data quality and data management. We draw on this expertise to fix data quality issues at the source and prepare clients’ data records to be “compliance-ready” for screening against any watch lists or high-risk databases.

Meeting the Demand for a Compliance-specific Data Quality Solution for AML Officers

We developed FinScan Premium at the request of our customers. Countless conversations with the AML officers we work with every day revealed that there was a great need for a product that combats data issues and empowers them to better control their own compliance screening results.

FinScan Premium addresses data quality problems such as duplicates, inconsistent formats, dummy data, and customer names misplaced in non-name fields, thereby reducing false positives and the risk of missing true hits. We have seen from 50% to 500% improvement rates, and low quality alert rates drop from 35% or 15% of the number of records screened to 1%.

To ensure that our clients’ data security, data privacy, and efficiency requirements are met, FinScan can be deployed via on-premise, SaaS, or web services.

Taking Control of Data — and the Success of Compliance Programs

Ultimately, FinScan Premium enables AML officers and compliance professionals to take control of their data, and therefore, the overall success of their compliance programs.

FinScan helps you achieve greater accuracy than ever before.

Who Can Benefit from FinScan Premium?

FinScan Premium offers an enormous benefit to any organization that has problems maintaining clean, high-quality data or achieving compliance with AML regulations. If your company or organization is experiencing any of the problems below, FinScan can help.

FinScan is perfect for:

  • Companies plagued by low-quality false positive alerts. If you have bad data resulting in false positive alerts, your company could experience a “needle in the haystack” phenomenon — you’re constantly spending resources checking alerts, but never uncovering any true hits. This can have a negative impact more severe than just wasted resources — having too many hits to review or getting used to constantly finding that alerts are false positives can result in reviewers letting down their guard and missing a true hit when it does come along. FinScan can reduce false positives to reduce wasted time and resources and keep you focused.
  • Companies with a backlog of uncleared alerts. You already allocate a significant amount of time and manpower to reviewing alerts during the sanctions and PEP screening process. When you’re receiving an abundance of false positives, the number of alerts you need to check quickly gets out of hand. Regain control over your alerts by cutting out false positives with FinScan.
  • Companies with resource-constrained AML compliance departments. If your team is overburdened with IT tasks, FinScan can help. By providing better alerts — that is, fewer false positives and more true hits — FinScan keeps you from wasting time and helps you increase the productivity of your AML compliance department.
  • Companies with numerous legacy systems across various countries or data sources. If your company grew through mergers and acquisitions, you likely have a data problem that is jeopardizing your AML compliance program. FinScan can help you eliminate that risk.
  • Companies preparing to embark on an IT transformation project. Whether you are planning, in the midst of, or have just completed an IT transformation project, it can impact the quality of your screening results. FinScan can help you maintain data quality during or post this transition.
  • Companies whose IT departments are overwhelmed. If your IT department has one or more important projects occupying the bulk of its resources but you cannot afford to wait for them to fix the data problems that are affecting your screening performance, FinScan can put you back in control so that you don’t have to be at the mercy of your organization’s resource constraints.

To highlight how helpful FinScan can be in these and other situations, we have launched The FinScan Premium False Positive Challenge — read on for details!

How to Improve Your Data Quality Today with the FinScan “False Positive” Challenge

FinScan Premium’s False Positive Challenge provides a free, no obligation opportunity for AML officers and other compliance professionals to see how their false positives and associated risks can be drastically reduced by allowing FinScan Premium to address their data quality issues and make their data “compliance-ready”.

We have identified significant data issues in customer and vendor records of most of the organizations whose data we have analyzed.

FinScan’s software helps you identify instances in which a company appears in your data as a person, helping you better understand your data.
FinScan’s software automatically identifies duplicate data so that your team doesn’t spend time sifting through the same data multiple times. Applied across your entire data set, this can lead to significant time savings.

When you take the False Positive Challenge, you will receive:

  • A diagnosis of the current condition of your data
    • Identifies the type of data issues, including duplicate and dummy records
    • Includes a recommendation of how to improve data before using it in compliance screening
  • The business case for fixing your data to achieve better screening accuracy, productivity, and risk management
    • Expected decrease in false positives and the resulting savings in review time and resources
    • Expected reduction in potential risk of missing true hits (versus if steps are not taken to make data compliance-ready)

Bad data is a ticking time bomb of risk that can cause huge problems for your financial institution. For the first time ever, garbage data can now be identified and corrected, leading to great sanctions and PEP screening results. Contact us today at to learn more about what FinScan Premium can do for your company.