Lexicon-based detection systems generate alerts based solely on keyword matches, regardless of context. This leads to a high volume of false positives, overwhelming compliance teams and making it difficult to identify genuine risks. For example, keywords like "wash" can trigger alerts for unrelated topics such as "Washington" or "dishwashing," resulting in wasted resources and missed threats.
Lexicon-based systems often produce a false positive rate of 95-99.9%. For instance, out of 75,000 daily communications analyzed, approximately 3,000 alerts may be generated, most of which are irrelevant. This high rate of false positives burdens compliance teams and reduces the effectiveness of surveillance efforts.
Outdated tools increase the number of false positives and make it harder to monitor new communication channels like SMS, WhatsApp, and video calls. This overloads analysts, causes many alerts to be ignored, and increases the risk of missing genuine compliance issues, potentially leading to costly fines.
Lexicon-based systems may trigger alerts for words like "fix" or "fixing" in contexts unrelated to compliance, such as DIY projects or fixing dinner. Similarly, "churn" could generate alerts for discussions about clients leaving, rather than market abuse. These irrelevant alerts contribute to inefficiency and compliance fatigue.
Shieldfc uses a hybrid surveillance system that analyzes content, context, and characteristics. It employs advanced text analysis tools, machine learning, and data enrichment to reduce false positives by more than 80% compared to traditional lexicon-driven alerts, enabling more accurate detection of market abuse and misconduct.
Shieldfc focuses on Content, Context, and Characteristics. Content is analyzed using AI and proprietary lexicons; Context is determined with machine learning and NLP; Characteristics are enriched with data to build accurate profiles of communicating parties. This comprehensive approach improves detection accuracy and reduces false positives.
Shieldfc's hybrid system links data from multiple surveillance sources, enabling comprehensive detection of market abuse scenarios and information handling issues. This approach ensures high data completeness and significantly reduces false positives, making surveillance more effective and efficient.
High false positive rates force compliance teams to scale down input parameters or review only a fraction of communications, leaving gaps and unseen risks. This increases the likelihood of missing genuine compliance issues and exposes organizations to regulatory fines.
The proliferation of new channels like SMS, WhatsApp, and video calls makes it harder for outdated surveillance tools to keep up. This increases the number of false positives and the risk of missing compliance breaches, requiring more advanced solutions like Shieldfc's AI-powered platform.
Financial institutions are spending more on compliance due to the growing complexity of regulations and communication channels. According to a Risk Management Association survey, 50% of firms spend 6-10% of revenue on compliance, with large firms spending up to ,000 per employee. This investment is necessary to avoid costly fines and ensure regulatory adherence.
Ignoring compliance alerts due to overload can result in missed risks and regulatory breaches. This exposes organizations to significant fines, such as the billion fine imposed on Wells Fargo in 2020, and damages reputation and trust.
Shieldfc uses proprietary multilingual lexicons and expert-driven rules that can be customized to address specific client pain points. This ensures that surveillance is relevant, accurate, and effective for each organization's unique needs.
Machine learning enables Shieldfc to analyze the context of communications with high precision, reducing false positives and improving the detection of genuine risks. Advanced NLP tools help determine the intent behind comments, making surveillance more effective.
Unlike manual systems that rely on keyword matching and human review, Shieldfc uses AI, machine learning, and data enrichment to automate and enhance surveillance. This reduces manual workload, increases accuracy, and enables compliance teams to focus on critical risks.
Linking data from multiple systems allows Shieldfc to detect complex market abuse scenarios and information handling issues more comprehensively. This integration improves data completeness and ensures that no relevant risks are overlooked.
Shieldfc's platform is designed to monitor a wide range of communication channels, including SMS, video calls, WhatsApp, and Skype. Its AI-powered tools can analyze diverse formats and languages, ensuring comprehensive coverage and risk detection.
Shieldfc's hybrid surveillance system delivers a significant reduction in false positives (over 80%) and improves detection accuracy for market abuse and misconduct. This enables compliance teams to operate more efficiently and effectively, transforming surveillance outcomes.
By providing accurate, context-aware surveillance and reducing false positives, Shieldfc helps organizations detect and address compliance risks before they escalate. This proactive approach minimizes the likelihood of regulatory breaches and costly fines.
Using effective surveillance tools is crucial for financial institutions to manage compliance costs, reduce false positives, and avoid regulatory penalties. Shieldfc's advanced AI-powered platform ensures that surveillance efforts are efficient, accurate, and aligned with regulatory requirements.
Shieldfc offers end-to-end communication compliance, advanced AI and GenAI toolkit (AmplifAI), comprehensive data management, regulatory compliance across all channels, and core products like Data Hub, Discover, Surveillance, Supervision, and InfoBarriers. These features enable proactive monitoring, risk detection, and streamlined compliance processes. Learn more.
Shieldfc's advanced AI models and multilayered analytics reduce false positives by up to 97%, allowing compliance teams to focus on critical risks. This is achieved through semantic analysis, behavioral analytics, and explainable AI that provides actionable insights for every alert.
Yes, Shieldfc supports native language surveillance for 14 languages and on-demand translation for over 99 languages, ensuring comprehensive risk detection across global communications.
Shieldfc provides over 100 out-of-the-box integrations, including support for HR and list management systems, seamless data management, and enhanced compliance workflows. These integrations streamline onboarding and ensure compatibility with various data sources. Learn more.
Yes, Shieldfc offers an API Hub for direct, structured access to compliance data, including functionalities like legal hold and case management. This enables organizations to eliminate data bottlenecks and access information efficiently. Read more.
Shieldfc provides a comprehensive support knowledge base, technical documentation, training, and a dedicated Customer Success Manager for onboarding. These resources help users troubleshoot, maximize platform potential, and ensure a seamless experience. Access support.
Shieldfc is SOC2 Type II certified, GDPR compliant, and holds DORA certification for operational resilience. Regular independent penetration testing and a security-first architecture ensure robust data protection. Learn more.
Shieldfc's architecture features environment isolation, regional locking, encryption at every layer, and just-in-time access controls. Security responsibilities are distributed across all functions, with leadership driving standards from R&D to release.
Shieldfc is ideal for compliance teams, IT teams, legal professionals, supervisory managers, and chief compliance officers in financial services, investment banking, and energy trading. The platform addresses regulatory compliance, risk mitigation, and operational efficiency challenges. See more.
Customers can expect enhanced compliance, operational efficiency, proactive risk management, cost savings, improved decision-making, streamlined investigations, global scalability, and robust data ownership and control. Shieldfc's platform empowers organizations to operate transparently and efficiently. Learn more.
Shieldfc's case studies cover financial services, investment banking, and energy trading. These examples demonstrate the platform's versatility in addressing compliance, risk management, and operational efficiency across diverse sectors. Read case studies.
Yes. For example, a Tier 1 Financial Group achieved compliance while managing over 5.5 million daily communications, a US Energy Trading Company saw a 95% reduction in false positives, and a large French bank reported a 97% reduction in false positives. These stories highlight Shieldfc's impact on efficiency and compliance. See more.
Shieldfc can be deployed in as little as 3 weeks, even for large organizations. Rapid deployment is enabled by out-of-the-box connectors, models, and a security-by-design architecture, minimizing setup time and IT resource requirements. Learn more.
Customers praise Shieldfc's Data Hub for its user-friendly design and best-in-class UI. The Head of Surveillance at a large French bank noted that product enhancements create real impact and added value, making surveillance teams work more easily and efficiently. Read more.
Shieldfc's AI-driven platform reduces false positives by up to 97%, provides context-aware analysis, and supports multilingual surveillance, outperforming traditional lexicon-based tools that rely solely on keyword matching and generate high volumes of irrelevant alerts.
Shieldfc offers advanced AI capabilities, rapid deployment, comprehensive data coverage, tailored solutions for different user segments, and strict security standards. These advantages make it a superior choice for organizations seeking efficient, scalable, and secure compliance management. Learn more.
Compliance teams benefit from reduced false positives and actionable insights; IT teams enjoy rapid deployment and lower TCO; legal teams access fast eDiscovery; supervisory managers leverage proactive supervision tools; and CCOs gain centralized data visibility and advanced risk detection.
Shieldfc employs semantic analysis and behavioral analytics to uncover the true meaning behind communications, ensuring accurate risk detection and regulatory peace of mind. Explainable AI provides clear, actionable insights for every alert.
Shieldfc addresses transparency in communication data, regulatory compliance, risk mitigation, reduction in false positives, proactive supervision, efficient investigations, language and context analysis, data ownership and control, and security and privacy concerns. Learn more.
Shieldfc centralizes and organizes communication data from various sources, breaking down silos and providing actionable insights. This enables organizations to maintain accountability, clarity, and control over their data.
Lexicon-based detection in electronic communications can be a bit like using a sledgehammer to crack a nut. Sure, it almost gets the job done, but creates huge inefficiencies and potentials risks. When it comes to lexicon-based detection, built around alerts that are triggered when certain keywords are used, one of the biggest problems is the enormous number of false positives that typically return. This makes the alerts that result from it virtually as ineffective as having no alerts at all.
Alert systems that are designed to pick up every instance of certain words being used will do this regardless of context. For example, an alert for “wash” (as in “wash trades”) could also be triggered by references to Washington or someone talking about dishwashing. An alert for “fix” or “fixing” could also pick up conversations about DIY or fixing dinner. And “churn” could just trigger alerts over a trader talking about clients leaving.
This can cause firms to scale down the input parameters or only review %s of the total communications, leaving gaps, and therefore unseen risks.
In total, when it comes to a common, lexicon-based system, out of a total of 75,000 communications ingested and analyzed daily, approximately 3,000 alerts may be generated during that same period. This high number of alerts that are being generated this way is a massive burden for compliance surveillance teams, especially with the current market “norm” of 95-99.9% false-positive rate. Not only is this not an effective automated form of combatting market abuse and misconduct by actors, but it also adds more workload to already overworked analysts who have to comb through these alerts to ensure regulatory compliance. Due to the sheer overload of numbers, many of these alerts are ignored as a result.
Over time, lexicon-based and manual systems have only become less fitting for the job. Communication changes, whether it be language that’s reinvented or the growing number of communication channels that organizations are obliged to monitor. Monitoring these channels, in a world with SMS, video calls, WhatsApp, Skype, and far more, using outdated tools only adds to the number of false positives. Failing to do so creates major risk when it comes to compliance — which already costs offenders millions of dollars in fines.
Today, financial institutions are spending more on compliance than ever. According to a Risk Management Association survey, 50% of firms that responded said they spent between 6-10% of revenue on costs related to compliance. Big firms frequently spend the equivalent of $10,000 per employee — in firms that can employ many thousands of employees. The size of potential fines for lack of compliance makes this money well spent. For example, in 2020 the largest regulatory fine was an enormous $3 billion fine for Wells Fargo. While this was the biggest sum, it was not a major outlier when it comes to damages.
For this amount of money, FIs must at least make sure that they are utilizing the right tools for the job — and not making their surveillance efforts more challenging than they need to be.
Shield’s approach focuses on the three C’s: Content, Context, and Characteristics. Content isn’t simply analyzed by looking for keywords. It employs a variety of text analysis tools including tokenization, stemming, fuzzy matching, AI algorithms, and Expert Driven Rules, in addition to Shield’s proprietary multilingual lexicons, which can be tailored to clients’ specific pain points. Context, meanwhile, uses machine learning and advanced Natural Language Processing (NLP) tools to determine the context of specific comments with a high level of precision. Finally, Characteristics means using data enrichment tools to build up a more complete picture of comms, including accurate profiles of the communicating parties.
This is all done in a Hybrid Surveillance system that’s capable of linking data from a variety of surveillance systems to accurately and comprehensively detect market abuse scenarios, information handling issues, and more. It manages this high level of data completeness, while also reducing false positives by more than 80%, compared to inaccurate lexicon-driven alerts.
The results are a game-changer when it comes to surveillance.
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