Financial Crime

How to Improve Watchlist Screening Process Effectiveness

Watchlist screening refers to the process of identifying and checking the customers, such as individuals and entities, against global watchlists. The purpose is to detect and prevent financial crimes and risks, such as fraud, money laundering, terrorism financing, and other illegal activities.

These watchlist databases are created and maintained by regulatory bodies, inter-governmental or international organizations, and law enforcement agencies across the globe. Some examples of notable watchlists are as follows:

  • The US Office of Foreign Assets Control (OFAC) Blocked Persons and Specially Designated Nationals (SDN) List
  • The UK’s Office of Financial Sanctions Implementation (OFSI) UK Sanctions List
  • The EU Sanctions List
  • Office of the Comptroller of the Currency (OCC)
  • Australia’s Department of Foreign Affairs and Trade (DFTA) Consolidated List
  • Canada’s Consolidated Canadian Autonomous Sanctions List
  • The UNSC Consolidated List

These lists contain details of individuals and entities involved in fraud, money laundering, terrorism financing, and criminal or prohibited activities, posing a high risk to the global banking process and the U.S. financial system.

With an effective Watchlist screening process, banks or financial institutions can efficiently identify high-risk individuals or entities and prevent potential financial crimes.

Importance & Benefits of Watchlist Screening Process for Banks

Watchlist screening is a crucial part of the Know-Your-Customer (KYC) process for banks and financial institutions for stronger financial crime compliance (FCC), including AML/CFT compliance and financial crime risk management.

Financial institutions must adhere to anti-money laundering compliance by verifying the details of the potential customers, such as name, aliases, date of birth, fingerprints, address, criminal history, nature of business, etc.

The watchlist database contains the details of –

  • Suspected terrorists
  • Politically exposed persons (PEP)
  • Sanctioned individuals
  • Narcotic dealers or traffickers
  • Money launderers
  • Human traffickers
  • Specially designated nationals (SDNs)
  • Individuals or entities in countries subject to economic sanction
  • Masses involved in the proliferation or sale/purchase of weapons of mass destruction

Further, optimizing the watchlist screening process assists financial institutions to –

  • Safeguard organizations from financial crime risks
  • Streamline customer screening and onboarding
  • Stay compliant with watchlists and regulatory norms
  • Reduce manual efforts and workload for compliance departments
  • Avoid non-compliance, penalties, sanctions, and legal consequences
  • Build a reputation by gaining customers’ and stakeholders’ trust

Watchlist Screening Methods

The watchlist screening process involves reviewing the customer information against the global watchlist database, which requires attention to detail. There are two approaches that banks and financial institutions can leverage.

1. Manual Watchlist Screening

Manual watchlist screening is a traditional screening method where humans manually review customer information against global watchlists. It requires significant expertise and experience, with high attention to detail.

Manual watchlist screening can provide a comprehensive customer review as human reviewers can make decisions based on context and intuition. Humans are also better at detecting false positives, which is a major issue with automated watchlist screening.

Challenges with Manual Watchlist Screening

Human error is one of the major challenges with manual watch list screening, which occur as follows:

  • Mistakes in data entry
  • Incorrect matches
  • A higher rate of false negatives
  • Increased risks of missed matches.

Additionally, manual screening consumes significant time and effort.

2. Automated Watchlist Screening

Automated watchlist screening has become popular due to its advantages that help banks and financial institutions efficiently combat financial crimes and streamline the compliance process.

It uses artificial intelligence and machine learning algorithms to process and analyze large datasets with high accuracy and quickly detect high-risk individuals or entities that match with the global watchlists.

Unlike manual watchlist screening, automated watchlist screening is faster, more efficient, and can process large volumes of data faster.

Challenges with Automated Watchlist Screening

Automated watchlist screening is technology-dependent and works based on rule-based programming. It does not have any ability to factor in the context. This can lead to issues, such as,

  • Incorrect flagging of legitimate customer
  • Adversely impact customer experience due to incorrect flagging
  • Prone to errors in programming
  • Missed potential risks due to technical shortcomings

Ways to Improve Watchlist Screening Effectiveness

Keeping pace with the rapidly updating global watchlists and compliance environment could be challenging, especially for small and medium-sized banks and financial institutions. Besides, it is not possible to detect or mitigate every risk irrespective of a manual or automated watchlist screening process.

5 Key techniques to improve watchlist screening infographic

However, banks and financial institutions can apply the following techniques to improve the effectiveness of the watchlist screening process.

  1. Standardize the Data
    Data standardization refers to the process of converting the data into a standard format, making it easier for the systems to understand and compare the data to match and find high-risk individuals. By standardizing the data and ensuring quality data across all sources, banks can significantly boost their watchlist screening process.
  2. Improve the Matching Algorithms
    Matching algorithms, including fuzzy matching algorithms, are the core components of an effective watchlist screening process, as they help reduce false positives and false negatives, and can detect matches with high accuracy. Banks need to continuously work, refine, and redefine the matching algorithms to improve watchlist screening effectiveness.
  3. Integrate Multiple Data Sources
    By integrating multiple data sources, such as those from government, financial institutions, commercial databases, etc., banks can create a more comprehensive and up-to-date watchlist. Data consolidation can help them reduce false positives and false negatives, thereby improving the overall effectiveness of the watchlist screening process.
  4. Use Artificial Intelligence (AI) & Machine Learning (ML)
    AI and ML technologies can help improve the efficiency and accuracy of automated watchlist screening systems. They can assist in identifying potential matches that traditional watchlist screening methods may fail to detect. By training the AI and ML-powered watchlist screening model, banks can recognize patterns and identify matches while reducing false positives and false negatives.

AI-Powered Automated Global Watchlist Screening

Anaptyss as a strategic partner assists banks and financial institutions in co-creating and implementing cutting-edge solutions for enhanced watchlist screening. Banks can leverage our exclusive enterprise-grade solution—’ALFA’—powered by AI and ML technologies for real-time transaction monitoring, watchlist screening, and KYC risk profiling.

Our next-gen KYC and AML screening solution, ALFA empowers banks to transform their manual processes for effective watchlist screening and compliance with AML, KYC, and CDD regulations.

Interested in learning more ways to increase the effectiveness of the watchlist screening?

Write to us: [email protected].

Tasneem Abdulrahman

Manager - AML Compliance

Tasneem is an accomplished professional with 15+ years of experience in the global financial crime compliance industry. Her expertise spans Regulatory Compliance, AML Risk and Governance, Project Management, and Control Testing and Remediation, including audits and strategic management of operational risk events.

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