Eliminating low-quality alerts in Regtech: The case for smarter flag generation
Institutions face the challenge of balancing rigorous monitoring with managing an overwhelming volume of alerts in financial compliance. While erring on the side of caution, many firms find their compliance teams inundated with low-quality alerts and false positives. Rigid, rule-based systems often fail to capture the nuances between legitimate and suspicious activities, leading to wasted resources, alert fatigue, and the risk of missing genuine threats. Smarter, adaptive alert generation is now essential to ensure efficiency and strengthen regulatory confidence.
Employees are still a part of the process
Despite advancements in compliance technology, human oversight remains crucial as teams investigate flagged trades. However, surges in low-quality alerts can generate alert fatigue, whereby compliance professionals are overwhelmed by irrelevant notifications. Reducing these low-value alerts can help refocus resources on meaningful risks and improve overall compliance effectiveness.
For senior management, the need for smarter alert generation isn’t just about compliance—it’s a key driver of operational efficiency, risk management, and cost savings that directly impact the bottom line.
Challenges posed by low-quality alerts
The cost of managing overwhelming volumes of low-quality alerts can be substantial, impacting overall compliance budgets and diverting resources from strategic initiatives. The impact of alert fatigue on compliance teams should never be overlooked. Aside from the obvious time issue, alert fatigue can be detrimental in many different ways:
Drain on resources
Balancing the growing regulatory burden against investment in compliance teams is challenging enough without the need to investigate false positives. This diverts critical time and effort away from genuine compliance tasks.
Reduced effectiveness
Forced to constantly trawl through low-quality alerts and false positives, compliance teams can become desensitised and sometimes overlook genuine suspicious activity. The potential knock-on effect on the company and regulatory impact can be significant.
Employee burnout
Low-quality alerts can prompt job dissatisfaction, burnout, and a high turnover of personnel. The operational and personal challenges in this situation are not difficult to see.
Compliance costs
The cost of setting up a compliance team and providing them with the appropriate resources can be high. Consequently, time spent investigating false positives or low-quality alerts that should be ignored when put into context reduces compliance efficiency and increases expense.
Enhanced regulatory scrutiny
It is not uncommon to see compliance departments flooded by low-quality alerts, often prompting a switch to selective quality control or a risk-assessed bulk closure of alerts. This means that not all alerts are pro-actively considered, increasing the likelihood that significant compliance issues could slip through the net.
Criteria for “Smart” Alert Generation
In theory, the higher the percentage of true positive alerts a system can create, the more likely a firm is to remain compliant. However, it’s also important that systems are able to identify potentially low-quality alerts using a smart filter system. This form of filtering system can help in several areas:
Accuracy
Using sophisticated algorithms and data models, it is possible to differentiate between genuinely suspicious activity and benign transactions. This creates a batch of genuine alerts, which are passed on to the compliance team for further investigation.
Relevance
As mentioned above, it’s essential to put any potential alert into context, whether due to dealing size or the client’s trading history. If a client regularly deals in significant size, then the number of shares in a trade should not necessarily prompt a red flag.
Timing
If the alert system is filtered by accuracy and relevance, this should create a more focused set of alerts with a strong requirement for further investigation. While still a reactive trigger, a prompt response can reduce further damage, financial losses and regulatory breaches.
Regulatory requirements shaping alert standards
Ultimately financial compliance alerting systems are defined by regulatory frameworks. We have the Dodd-Frank Act in the US, while the Market Abuse Regulation (MAR) dominates the EU, with the UK operating a similar system post-Brexit.
These regulations impact alerting standards in several ways:
Risk-based approach
There is no one-size-fits-all approach to monitoring compliance obligations and liabilities, as each firm will have a different focus depending on products traded and trade processes and volumes. Consequently, regulators are very keen to take a risk-based approach that ensures alerts are related to the institution’s actual exposure and regulatory focus.
Documentation and audits
As you would expect, compliance monitoring systems must retain records of alerts, investigations and resolutions. This ensures that data is available in the event of a prosecution and also allows the regulator to audit, assess and investigate individual firms.
Real-time surveillance
Specific regulations require real-time or near real-time monitoring of transactions and communications where possible. Institutions operating in these areas must invest in advanced technology to process large amounts of data.
Continuous improvement
The innovative nature of those perpetrating market abuse means that financial institutions and regulators are on a course of continuous improvement. This includes introducing the latest technology and ongoing training of employees.
Just as financial institutions aim to filter out low-quality alerts to focus their time, effort, and resources on appropriate issues, regulators do the same. The last thing they want is to be inundated with low-quality, non-contextualised alerts that divert in-demand resources.
The case for advanced AI and machine learning in alert generation
When we talk about advanced AI and machine learning systems, it can be tempting to focus more on time savings than on the broader benefits. It’s safe to say that new technology is transforming alert generation, enhancing accuracy and efficiency and filtering out low-quality or contextually irrelevant alerts.
There are many ways in which the accuracy of financial compliance alerts has been improved:
Adaptive algorithms
As we mentioned above, one of the fundamental problems with previous compliance monitoring systems was the relatively rigid rules. Complex algorithms constantly adapt their criteria, learning from new patterns and adapting to changing times.
Contextual analysis
Contextual analysis is critical for future compliance monitoring, whether examining market conditions or historic client trading activity. Considering potential alerts against the background of market trends and events, recent industry news and other timely information can put false positive alerts into context.
Pattern recognition
A further benefit is the ability to analyse significant amounts of data and recognise new patterns that rule-based systems could miss. This ability to recognise nuanced deviations further enhances more accurate alert flagging. The benefits of this can be twofold; both the recognising of new alerts as well as the ability to offer dynamic, contextual, parameterisation of a Trade Surveillance tools’ alerts.
Communication Surveillance
Natural language processing is central to analysing unstructured data. It allows the reviewing of emails, chats or telephone calls and puts the discussions into context. Often overlooked, unstructured data can, in some instances, flag potential regulatory issues before they commence.
Examples of successful implementation
There are many scenarios where smart flag generation has helped to both identify valid flags (which would have been missed by previous systems) and dismiss false alerts. These include:
- Adaptive algorithms in transaction monitoring
- Contextual analysis with client risk scoring
- Anomaly detection in market surveillance
- Natural language processing and insider trading
The flexible and in-depth nature of these elements has helped to significantly enhance compliance monitoring in the financial services industry. There will always be new challenges and threats emerging, and by definition, monitoring systems will often be playing catch-up. However, the introduction of AI and machine learning is supplying more innovative tools for regulators and financial institutions.
Impact on compliance efficiency and regulatory confidence
As an experienced regulatory technology company, eflow’s services have enhanced compliance efficiency and bolstered regulatory confidence for our clients. This is the practical end of the industry, the way we incorporate cutting-edge services into legacy systems.
We know from client feedback that reducing alert volumes can significantly improve compliance performance through a number of means:-
Enhanced resource allocation
We have a range of processes that reduce the number of false positives, allowing our clients to focus on genuine issues that require further investigation. This improves metrics such as return on investment, analyst efficiency, regulatory compliance, workload, and investigation quality.
Improved detection accuracy
Our ability to adapt algorithms and leverage contextual analysis has seen us refine alert accuracy by recognising trading and transaction behaviour patterns. This minimises the risk of compliance breaches and the associated regulatory consequences.
Reduced alert fatigue
As with so many critical factors, alert fatigue is an issue that is often overlooked and dismissed. However, a constant flow of low-quality alerts can prompt alert fatigue and increased errors. Enhanced trust in eflow systems reduces alert fatigue, allowing teams to remain focused.
For executives focused on optimising resource allocation, eflow’s solutions provide measurable savings by allowing teams to concentrate on critical alerts, reducing overall compliance costs and enhancing operational efficiency.
Linking improvements to confidence in regulatory audits and reviews
With investment markets, uncertainty breeds uncertainty, which is no different regarding regulatory compliance and trust. Some of the broader benefits of an improved alert system include:
- Strengthened regulatory relationships
- Detailed and traceable audits
- Increased regulatory confidence
- Lower risk of regulatory and financial penalties
If we drill down into the basics, it’s all about trust—trust in eflow services, information analysis, and the quality of alerts. These are conducive to a healthy respect for relationships with regulators and also strengthen and support your wider reputation with clients and third parties.
Conclusion
In financial compliance, effective alert filtering often hinges on context. What may initially seem suspicious can appear routine when viewed against a client’s typical trading activity and prevailing market conditions. Beyond the costs of investigating low-quality alerts, this contextual accuracy helps mitigate issues like alert fatigue, employee burnout, and morale challenges within compliance teams.
eflow’s adaptable surveillance systems are designed to continually improve accuracy. They offer a cost-effective, time-efficient, and future-proof approach to compliance. With our intelligent alert systems, financial institutions can enhance compliance at a lower cost, reduce risk exposure, and streamline operational efficiency—adding measurable value to the bottom line.
