Measuring Screening Success

In today’s fast-paced financial world, screening plays a crucial role in preventing financial crimes, from money laundering to terrorist financing. As financial institutions and fintech companies grapple with increasing regulatory demands, understanding and measuring key performance indicators (KPIs) in screening becomes vital. 

Let’s explore the significance of screening and the transformative impact of new technologies such as artificial intelligence (AI). 

Behind the curtain – the mechanics of customer and transaction screening

Screening is a multifaceted process by which financial institutions ensure they do not engage in business with sanctioned individuals, entities or countries. Screening comprises two main components: customer screening and transaction screening. Customer screening is a key control in the know your customer framework (KYC) to identify individuals who may be politically exposed persons (PEPs) and entities targeted by sanctions. Transaction screening is a required control to identify and prevent illicit transactions by targeted entities or individuals seeking to access the financial system. Transaction screening is performed in real-time to stop payments or transactions that involve sanctioned targets from being processed. 

These processes are fundamental in maintaining the integrity of the global financial system by preventing the facilitation of illegal activities. However, the complexity of global financial transactions and the dynamic nature of sanction lists make effective screening a significant challenge. 

The KPI playbook – metrics that matter in screening

KPIs are crucial in assessing the effectiveness of screening processes. They provide measurable insights into how well an institution is performing at identifying and mitigating risks. Here are some critical categories of KPIs for screening: 

• Hit rate: The percentage of matches found against sanction lists during the screening process. A high hit rate can indicate more effective screening but may also reflect the need for better data accuracy. 
• False positive rate: The percentage of flagged items that are not actual matches. A high false positive rate can lead to inefficiencies and increased operational costs.
• Alert resolution time: The average time taken to resolve alerts. Faster resolution times indicate a more efficient screening process. 
• Compliance cost per transaction: This KPI helps in understanding the financial impact of compliance activities on each transaction. 
• System downtime: The duration for which the screening system is non-operational while updating lists. Minimizing downtime is crucial for maintaining continuous compliance. 

Navigating the challenges of screening

Despite advancements in compliance frameworks and efforts on setting best practices by compliance teams, both customer and transaction screening present significant challenges for financial institutions.

Customer screening challenges

• Data quality and completeness: Ensuring that customer data is accurate, complete, and up-to-date is a perennial challenge. Incomplete or outdated data can lead to incorrect risk assessments and missed red flags. 
• Evolving customer profiles: Customer’s risk profiles can change over time due to various factors such as changes in financial behavior, employment, or geography. Keeping up with these evolving profiles requires constant monitoring and re-screening. 
• Staying up-to-date with sanctions & regulations: Lists and regulations are updated frequently (locally & globally) and organizations must ensure their screening systems are current to identify all risks and maintain compliance.
• False positives and negatives: High rates of false positives can overwhelm compliance teams and lead to operational inefficiencies, while false negatives pose significant risks as they allow suspicious activities to go undetected. 

Transaction screening challenges

• Volume and speed of transactions: The increasing volume of transactions, especially with the rise of real-time payments, necessitates rapid and accurate screening. This can strain existing systems and processes, potentially leading to bottlenecks. 
• Complex transaction patterns: Illicit actors often use complex transaction patterns to evade detection. Identifying and analyzing these patterns requires sophisticated technology to facilitate continuous learning and detection. 
• Integration with legacy systems: Many financial institutions still rely on legacy systems that may not seamlessly integrate with modern screening technologies. This can lead to inefficiencies and gaps in the screening process. 
• Cost and resource constraints: Maintaining a comprehensive screening program requires significant resources (& cost) for training, implementation and investigation work. Risk and compliance teams may struggle to recruit and retain staff so it’s important to provide necessary training and support. 

By addressing these challenges through improved data management, adopting advanced technologies like AI and machine learning, and staying updated with regulatory changes, financial institutions can enhance their screening processes to better detect financial crime. 

Know your customer precision screening

Customer screening is an integral part of both customer due diligence and ongoing monitoring process. It involves checking customer data against various watchlists and databases to identify potential matches with sanctioned entities. 

KPI categories for customer screening

• Screening accuracy: The percentage of accurate matches against watchlists. Higher accuracy reduces the risk of false positives. 
• Re-screening frequency: How often customers are re-screened against updated watchlists. Regular re-screening is vital to catch new risks as customer relationships evolve. 
• Alert volume: The number of alerts generated during customer screening. Balancing alert volume is crucial to avoid overwhelming compliance teams while maintaining thorough checks. 
• Resolution time: The time taken to resolve alerts generated from customer screening. Faster resolution times contribute to operational efficiency and better customer experience. 

Real-time vigilance in transaction screening

Transaction screening involves monitoring financial transactions in real-time to examine the movement of money and to verify details of a financial transaction to ensure there are no ‘indicators’ of potential financial crime. This occurs before the transaction has been ‘approved’ and processed.

Organizations are required to screen individuals and entities appearing in the transactions as originator and beneficiary against designated sanction lists according to the jurisdictions in which an organization trades (including the currencies they trade in). It includes geographical controls involving any individual or entity transacting from/to prohibited countries or regions. It also can include sectoral sanctions that target specific goods or sectors.

KPI categories for transaction screening

• Transaction throughput: The system’s ability to handle high volumes of transactions without compromising performance.
• Alert volume: The number of alerts generated by the screening system. Balancing too few and too many alerts is critical. 
• Productive suspicious activity reports (SARs): The number of productive SARs filed and their outcomes. SARs provide insights into the effectiveness of the transaction screening process. 
• Alert escalation rate: The rate at which alerts are escalated for further investigation. Efficient escalation processes ensure timely response to potential threats. 

Future-proofing screening with AI

The financial sector has seen significant increase in real-time payments, which are expected to grow at a compound annual growth rate (CAGR) of 35.5% from 2023 to 2030. This growth demands more sophisticated and efficient transaction and customer screening systems. Leveraging AI, machine learning and other advanced technologies has become a game-changing strategy for financial institutions to keep pace with these demands. 

AI, machine learning and big data analytics are transforming screening by enhancing the accuracy and efficiency of compliance processes. These technologies can analyze vast amounts of data, identify suspicious patterns, and detect anomalies that traditional systems miss.

Impact of AI on KPIs

Financial institutions leveraging AI for customer and transaction screening have reported significant improvements in compliance efficiency and effectiveness. Furthermore, on the business side of compliance, automation reduces manual efforts and operational costs.

• Improved hit rates: AI and machine learning algorithms can analyze vast amounts of data to identify potential matches more accurately, and can also learn from the data, resulting in unbiased detection and improved hit rates. 
• Reduced false positives: Advanced machine learning algorithms can better differentiate between true matches and false positives, aiding customer onboarding and reviews, potentially improving customer experience and reducing the burden on compliance teams. 
• Enhanced efficiency: Automation and real-time data analysis enable faster alert resolution times and more efficient screening processes. 

Industry research indicates that banks using AI-driven compliance solutions have seen a reduction in false positives by up to 70% and an increase in detection accuracy by 50%. Furthermore the integration of AI in compliance processes has led to a 30% reduction in operational costs and a 25% improvement in compliance staff productivity. 

Charting a course with KPIs and tech 

As financial institutions navigate the complexities of screening, adopting new technologies and leveraging KPIs will be crucial for continued success. Adopting an AI-driven approach not only enhances the accuracy and efficiency of screening processes but also provides a competitive business edge and secure growth in the fast-paced financial sector.