Announcing the paper’s release, HKMA Executive Director Carmen Chu noted that the key objective of the guidance is to support the greater use of data and technology. Specifically, Chu commented on the regulator’s aim for authorized institutions (AIs) to adopt a system that generates targeted alerts to deliver more actionable insights into the anti-money laundering and counter-financing of terrorism (AML/CFT) ecosystem.   

Updated Guidance

In Hong Kong’s 2022 Money Laundering and Terrorist Financing Risk Assessment Report, the government highlighted five focus areas to enhance its AML/CFT regime. The first relates to keeping pace with international standards by implementing updated standards and providing a legal framework for better implementation of risk-based regulation. The HKMA’s guidance paper follows this priority to improve the effectiveness of transaction monitoring, screening, and suspicious transaction reporting undertaken by AIs.

Transaction Monitoring

Practical guidance relating to the way in which firms adopt, design, and review their transaction monitoring systems consists of the following:

• Assessment: Before implementing a particular transaction monitoring system, AIs should conduct a robust assessment and document the rationale for adopting the system. This should include how compatibile the new system is with the AI’s existing IT infrastructure and how any necessary system changes will be executed and managed.
• Automation: A level of automation involving one or more rules-based or scenarios-based systems may help AIs produce alerts or management information system (MIS) reports to aid the identification of suspicious transactions that require further examination.
• Configurability: AIs are reminded that off-the-shelf systems provided by a vendor may not adequately take into account a firm’s specific risks. AIs should adopt a system that can be configured to their relevant contexts, such as the ability to adjust thresholds and customize rule sets to sufficiently meet legal and regulatory requirements.
• Customer segmentation: AIs are encouraged to have appropriate customer segmentation to allow the transaction monitoring system to operate effectively, and generate more targeted, higher-quality alerts. 

Screening

While the HKMA acknowledges there is no “one-size-fits-all” approach to customer screening, the regulator provides the following guidance to help AIs adopt a screening solution that is consistent with their risk appetite, and ensure compliance with relevant regulations:

• Up-to-date databases: Whether databases are maintained in-house or with support from a vendor, AIs should ensure they are complete, accurate, and updated in a timely manner. 
• Name matching: Appropriate settings should be applied to allow the screening system to identify common spelling alterations and variations, including the manipulation of names and keywords. AIs may also choose to use automated processes to handle names that use non-Latin script. 
• Ongoing review: Frequent monitoring, tuning and testing should be conducted on all aspects of screening systems, with testing results and analysis properly documented. Senior management should have sufficient oversight of screening systems and processes to ensure their efficiency and effectiveness. 

Suspicious Transaction Reporting

To meet their reporting obligations, AIs must maintain high levels of quality and consistency. When filing a suspicious transaction report (STR), the HKMA advises AIs to:

• Structure the content systematically
• Focus on the main subject and be concise
• Include digital footprints related to online banking activities
• Use of file attachments appropriately
• Avoid providing non-editable transaction records

Additional Focus Areas

The Hong Kong government’s four other priorities likewise respond to the risks and gaps identified in its 2022 assessment. These include:

• Strengthening the application of risk-based supervision to ensure targeted regulation is applied to high-risk areas, such as banking, money service operators, dealers in precious metals and stones, and trust or company service providers
• Enhancing outreach and capacity-building to promote awareness and understanding of money laundering and terrorist financing (ML/TF) risks by various sectors 
• Monitoring new and emerging risks to respond promptly to evolving patterns of predicate offenses or terrorism, and modes of ML/TF
• Strengthening law enforcement efforts and intelligence capability to tackle domestic and international ML/TF, and enhance confiscation of the proceeds of crime

Key Takeaways

Firms should review the updated guidance and implement any necessary operational, technical, and/or policy changes to align practices with those set out by the HKMA.

Additionally, compliance staff should review this guidance in conjunction with the Anti-Money Laundering and Counter-Terrorist Financing Ordinance (AMLO), the Guideline on Anti-Money Laundering and Counter-Financing of Terrorism (AML/CFT Guideline), and other guidance issued by relevant competent authorities. 

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While all of these are important, one often overlooked factor is implementation. How vendors implement their clients’ AML programs is critical. A slow implementation process risks undermining the customer experience and delaying the roll-out of new products and services. Poor support over time can become a chronic issue weighing compliance teams down if, for example, the ability to add new rules and capabilities is impacted.

So how can firms assess what ‘good’ looks like when it comes to implementation? Here are five top considerations.

Implementation of Anti-Money Laundering Software: Five Top Considerations

1. Pre-built rules and collateral

While onboarding times will vary based on the complexity of the implementation and specific client requirements, there are steps vendors can take to make this smoother. For AML solutions like transaction monitoring and screening, one important feature compliance teams should look for is ‘plug and play’ capabilities that make the set-up process more efficient. Offering a pre-built library of rules and typologies is one good example of this. In addition to demonstrating what a best practice program looks like, these libraries can help teams get set up quickly, without the need to build everything from scratch. 

In addition to pre-built rules, firms should ask vendors about the collateral they provide to support implementation. This may include a rule library, API guide, dummy data for testing, and more. All of these help clients to get started more quickly and mean they can get up-to-speed in their own time.

Vendors should be realistic about the length of the implementation process, though. With cost-effective solutions and the right resources prepared on the client side, implementation times can be as short as two weeks.

2. A personalized approach

‘Out of the box’ features such as a REST API need to be supported by in-house technical and personnel skills to manage complex, customized implementation requests. Some clients will inevitably have bespoke rule sets they need to manage or particular challenges with the structure or quality of their data. This must be considered upfront to ensure the fraud and AML detection system works effectively post-implementation. To manage this complex array of requests, firms should ask vendors how they manage the implementation process. A best practice approach is for each client to have a dedicated implementation consultant who will support them through to go-live, ensuring continuity of service and a speedy response to inevitable questions and challenges. Ideally, this consultant will be flexible about working remotely or on-site with the customer, based on what will enable them to progress more effectively.

TransferMate, one of the world’s leading B2B payments infrastructure-as-a-service companies, enables individuals to make seamless, cost-effective cross-border payments. But operating across more than 201 countries and 141 currencies means the risks and typologies their team must monitor for are not always captured by pre-built rule sets. During its implementation process with ComplyAdvantage, the two teams communicated almost daily. Alex Clements, Global Head of Financial Investigations and Monitoring at ComplyAdvantage, described this as a “one team, two organizations” approach. The company worked with ComplyAdvantage implementation consultants to define its data model and scope out the bespoke rules it wanted to build for transaction risk management. ComplyAdvantage used its industry expertise to help TransferMate achieve its goals, sharing ideas and best practices.

3. Strong industry knowledge

Some regtech vendors will also specialize in supporting certain markets like digital banking or payments. Others have a broad suite of clients, with implementation and customer success teams dedicated to each. While both approaches can make for a successful business, firms should ensure their vendor has experience with relevant firms in their space. This will enable greater out-of-the-box thinking when solving inevitable challenges and roadblocks. This also empowers implementation teams to be proactive, offering creative solutions that can help firms get to their intended solution more quickly or efficiently than they had anticipated.

Hampshire Trust Bank (HTB), a specialist bank based in the UK that provides business finance, mortgage, and development finance solutions, has compliance challenges unique to its business model. By working with an experienced implementation team at ComplyAdvantage, the bank is able to, for example, look at how to optimize the application of its transaction monitoring rules for specific customer segments that may operate in particular ways.

4. Sandboxing and an iterative mindset

From day one of implementation, the best vendors will have a ‘test and iterate’ mindset. This should begin with a sandbox, enabling integration to start immediately. A sandbox approach also means implementation can be phased, with deliverables that are ready starting immediately while work on other areas of the solution is ongoing.

The intersection of implementation and customer success is also critical. Customer success managers will be their clients’ front-line representatives when explaining and working through the roll-out of new vendor features, or when managing client requests for new capabilities. A knowledgeable and engaged customer success manager can also proactively recommend optimizations based on their experience working with other similar clients. As Robin Jeffrey, Head of Transformation at HTB explained about working with ComplyAdvantage: “Other products we reviewed on the market were more rigid. ComplyAdvantage enables us to focus on continual improvement, adapting the platform as we learn and as the world evolves.”

5. Agile to changing risks

It’s also important for firms to remember that implementation is not a ‘one-and-done’ process. Compliance decision-makers should evaluate firms’ ability to support changes over time as new risks emerge. Look for a firm that offers features like the ability to build new rules quickly without the need to raise a time-consuming support ticket. Waiting for a vendor’s IT team to implement a change to risk thresholds based, for example, on new information from law enforcement could lead to criminal behavior going undetected for weeks, or even months.

Overseas payments and foreign exchange provider Lumon found itself needing to react quickly in the early stages of the pandemic when it saw a sudden increase in COVID-related investment fraud. “ Within 48 hours of identifying this, Lumon developed and deployed new rule sets to combat the threat and prevent more customers from falling victim to scams” explains Alessio Giorgi, the firm’s Head of Compliance and MLRO.

The post Anti-Money Laundering Program: Why Good Software Implementation Is Critical appeared first on ComplyAdvantage.

This doesn’t just create frustrations – it wastes company time, financial, and energy resources, overloads personnel, and makes it more likely that teams will miss illegal activity. It can also lead to unwanted organizational costs and losses. For example, team burnout means high turnover rates and costs to recruit and train replacements. Poor screening can result in losses to fraud and resulting disputes. 

And most importantly, if a company is deemed to have insufficient risk management processes, it can face regulatory fines and legal action. In a particularly high-profile instance, one global investment firm was fined over $1 billion in 2022 for – alongside long-term fraud – “failure to implement key risk controls.”

How AI Solves the Cost vs. Risk Dilemma

Despite these rising pressures and risks, many financial institutions worry that a system overhaul would cost even more. But it’s actually possible to keep a firm’s core system in place and while overlaying artificial intelligence algorithms to enhance its abilities. Indeed, competitive firms have spotlighted their reliance on artificial intelligence and machine learning (ML) as key to their success. 

“Effectiveness and efficacy are key for scaling. We can’t grow our team every time we grow our customer base,” explains Valentina Butera, Head of AML and AFC Operations at Holvi, a leading digital bank. And in a recent interview, PwC Luxembourg’s Andreas Braun highlighted the tremendous data processing and analysis possible through AI, which helps solve traditional risk management efficiency and cost dilemmas. 

A 2022 report by Allied Market Research predicted that the market for fintech AI would reach over $61 billion by 2030. Once relegated to speculation, AI and ML are now practical realities – and judging by worldwide regulatory responses, their use is becoming ubiquitous. Key examples include: 

• The European Union’s proposed Artificial Intelligence Act
• US House Committee on Financial Services’ Task Force on Artificial Intelligence
• The United Kingdom Financial Conduct Authority’s AI Public-Private Forum and Artificial Intelligence Discussion Paper
• The Monetary Authority of Singapore’s Project Veritas 

In our annual State of Financial Crime report, 99 percent of surveyed firms expected AI to positively impact financial crime risk detection. Consider the three most-selected use cases for AI in transaction monitoring: 

• Alert Prioritization – 31 percent of respondents expected AI to help rank transaction alerts by risk. This enables transaction monitoring teams to catch more risky activity and do it faster. 
• Flexible Tuning – 26 percent thought they’d use AI to improve their alert system – helping to adjust thresholds and fine-tune alerts responsively. 
• Relationship Identification – 24 percent anticipated artificial intelligence would uncover new relationships between monitored entities and individuals. 

Using AI to Enhance Transaction Monitoring

How might an AI overlay work in practice?

Consider a scenario. A senior analyst, Allison, has been dealing with bloated and imprecise alert queues due to rigid rules and no triage by priority. Every day, she spends hours painstakingly working through individual alerts without an efficient way to tell which are critical and most worth her time investigating. When she does come across a high-risk alert, she has less time to research it because of wasted time clearing false positives. In fact, if the system is backlogged, alerts tied to actual financial crime may sit in the queue for days or weeks before they’re found. The team has lost several members recently, but Allison doesn’t have time to keep up with her queues and train new teammates effectively.

Then imagine her company adding a layer of artificial intelligence over its existing system to handle alerts more intelligently. The new AI overlay combines multiple powerful risk management techniques, allowing it to:

• Automatically triage alerts – The AI knows how to triage incoming alerts by risk level, assigning a high level of risk to those showing the most suspicious activity. It will also continuously improve based on analysts’ feedback. Allison immediately begins looking at the high-risk alerts queue when she comes into work. Meanwhile, the lowest-risk alerts are either resolved in bulk or used to train newer analysts. And when mentoring advancing team members, Allison can use the high-risk queue to illustrate how to handle risky alerts.
• Enable more effective tuning – AI also allows the team to improve and adjust underlying rules’ parameters and thresholds. This enables more risk-responsive alerting, which helps enhance detections and reduce false positives.
• Uncover more bad actors – Weak evidence related to one person alone may not lead to an escalation. But with the new AI overlay, Allison’s team can leverage weak correlates in their data pools to identify and disrupt clusters of criminal activity.
• Identify true actors working behind the scenes using identity clustering to seek out hidden relationships. The team can now see connections and red flags that were previously invisible to them.
• Get greater insights and explainability around the reasons for an alert being generated. Allison is more confident that she and her team can back up their decisions should they be audited or receive an inquiry from their senior leadership.

With minimal upfront cost, AI-enhanced transaction monitoring maximizes Allison’s value to the company, empowering efficient and risk-based investigation while allowing her to train team members effectively. Meanwhile, layered machine learning models improve the effectiveness of her firm’s AML/CFT risk detection process.

Key Takeaways

For years, compliance teams have known that legacy AML software and processes have not met the financial crime challenges faced by their organizations. Rigid rules and tick boxes may capture some egregious behavior, but they miss much of the complexity involved in illicit activity. They also cannot see the bigger picture and broader connections between entities and people necessary to help law enforcement eliminate criminal behavior root and branch. The tools and technologies now exist for banks to meet this moment. 

Iain Armstrong, Regulatory Affairs Practice Lead at ComplyAdvantage, weighs in. “Many firms are already seeing success with AI, so it’s important to be agile, and avoid falling behind competitors who may soon be able to work in a much more sophisticated way without comparable increases in costs.” Indeed, ‘AI’ is no longer simply a buzzword – it’s an umbrella for many actionable programs that firms can implement today. Regulators worldwide recognize this and likely will soon ensure AML regulations reflect the innovations available to firms in their jurisdictions.

An artificial intelligence overlay can provide a simple, cost-effective option for companies that need AI’s benefits but aren’t in a position to make a major overhaul. Using an overlay also involves fewer unknowns, since the algorithms don’t replace existing processes but enhance them. With minimal disruption, firms can improve AML/CFT compliance efficiency with AI-enhanced alert prioritization, risk detection, and escalation – reducing risk and related costs while supporting employee retention rates and remaining competitive in an ever-changing compliance landscape.

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To remain compliant with these regulations while responding to emerging overseas payments threats, Lumon partnered with ComplyAdvantage for its customer screening and monitoring and transaction monitoring solutions.

A long-standing partnership

Lumon’s relationship with ComplyAdvantage stretches back many years. Initially, the company was looking to replace its legacy customer screening solution, having grown tired of the limited connectivity between the company’s compliance function and its systems. Lumon wanted a solution with API-led connectivity and the ability to manually upload transaction data.

Lumon found many of the products provided by incumbent providers were not suitable for FinTechs. But in ComplyAdvantage, Giorgi says the team “saw a business that knew there was a gap in the market to support FinTech businesses.”

Over the years, the two firms have scaled successfully together. According to Giorgi, ComplyAdvantage’s adoption of artificial intelligence (AI) and machine learning was key to solidifying the partnership. Automation at speed, accurate data, and the ability to categorize and organize relevant risk data allowed Lumon to generate better insights and apply them throughout its system more efficiently.

Game-changing solutions

ComplyAdvantage’s payment screening functionality in its Amazon Web Services (AWS)-based transaction monitoring solution was a “game-changer” for Giorgi, allowing Lumon to centralize its payment screening and transaction monitoring activities within one team, connected to one system via a single API.

The solution’s connectivity and ComplyAdvantage’s quick response times provide Lumon with peace of mind when managing its risk exposure. The reliability of ComplyAdvantage’s customer success team was also lauded by Lumon. Giorgi explained he’s able to share his concerns, questions, and problems with his dedicated customer manager, knowing a response with proposed solutions will be in his inbox the following morning.

“ComplyAdvantage is supportive, responsive, and has a solution that is at the forefront of RegTech.”

– Alessio Giorgi, Head of Compliance and MLRO at Lumon

Managing pandemic fraud risks

ComplyAdvantage’s transaction monitoring solution has allowed Lumon to uncover new insights into customer activity, enabling the payments firm to detect new or emerging typologies and then build rules to mitigate them.

“ComplyAdvantage’s solutions help us sleep better at night, knowing that we’ve got the right systems and controls in place and that they are effective.”

– Alessio Giorgi, Head of Compliance and MLRO at Lumon

For example, during the early stages of the pandemic, Lumon saw a sudden increase in COVID-related investment fraud. Within 48 hours of identifying this, Lumon developed and deployed new rule sets to combat the threat and prevent more customers from falling victim to scams.

“Deploying the ComplyAdvantage solutions has given us more control over our overall financial crime risk management framework,” said Giorgi. “I would definitely recommend ComplyAdvantage to other businesses, particularly those with ambitions to grow at pace.”

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Almost half of businesses globally have experienced fraud or a related economic crime in the last 24 months. What’s more, according to PwC, the risk of exposure grows as companies scale. 38% of businesses with less than $100m in revenue reported experiencing fraud, while the figure for firms with more than $10bn in revenue was 52%. 

Another compounding risk factor is innovation, with FinTechs such as neobanks and robo-advisers experiencing almost twice the rate of fraud compared to traditional banks. As newer entrants to the market, these firms are often less able to absorb the reputational damage that comes with negative news stories about defrauded customers.

Our State of Financial Crime report, based on a global survey of compliance professionals, also highlighted exceptionally high levels of concern about fraud during the pandemic. While the stimulus checks and relief payments that drove this have subsided, it remains a top predicate offense. 

Fraud detection and prevention is a vital tool in the arsenal of risk professionals looking to prevent fraud effectively. But in a dynamic environment where financial crime risks are increasingly bespoke to a firm’s business model and customer base, what does a best practice approach to transaction fraud look like? 

The challenge of fraud

Fraud analysts should consider their transaction fraud risk across three core areas of compliance:

Process: As new typologies emerge and criminal behavior changes, firms must align their enterprise risk assessments and identify any required changes to their business’ risk appetite. This may include evaluating new product lines, customer profiles, or regulatory requirements.

People: Fraud and anti-money laundering teams often work in silos. This can hinder effective financial crime risk detection. It may also leave patterns of illicit behavior that contextualize a potentially suspicious transaction undetected. Communication is critical, particularly as firms evaluate machine learning-based monitoring solutions. Data and information sharing across teams are essential to the success of these investments.

Platform: With an appropriate risk appetite set, and the correct internal alignment, fraud teams can take advantage of machine learning and behavioral analytics for fraud detection. In contrast to a rules-based approach, these solutions can project future risks and help teams anticipate threats. The straightforward configuration options offered by these tools mean it is possible to fine-tune alerts across various payment chains, responding to changing risks in near real-time.

Real-time fraud detection use cases

With the right approach across processes, people, and platforms, transaction fraud teams will be well placed to tackle fraud risks in their organization. ComplyAdvantage’s fraud detection solution underpins its Transaction Risk Management solution, providing real-time fraud detection across the key fraud typologies affecting financial institutions today.

In addition to rules that detect common fraud scenarios, we have an AI-driven approach that serves the risk and compliance team across a range of use cases. Here are some simple examples 

• A fraudster has a stolen card and wants to use it to withdraw cash. He uses the card in an out-of-pattern way, either withdrawing large amounts of money or using it in different countries. In this situation, the ComplyAdvantage solution will identify and flag the strange ATM transaction.
• A criminal buys a list of stolen cards online. Rather than attempt to use them for large purchases right away, she purchases small items first to ensure the card is still active and not flagged. Here, the ComplyAdvantage system detects the unusual pattern and flags the transactions.
• A customer typically only uses his account to buy clothes and groceries. Suddenly, there is a change in activity. A fraudster has used his card to buy designer shoes worth $500. In this scenario, the ComplyAdvantage solution detects the change in activity and flags the transaction.

Reducing fraud risk exposure: RealPage success story 

Fraud risk is nuanced and differs from industry to industry and even organization to organization. Working with ComplyAdvantage, financial institutions can target specific types of fraud through adjustable thresholds. Our fraud solution learns from the team’s actions and tunes the detection process over time to identify truly suspicious activity such as deviations in customer behavior or transactions that are physically impossible based on location. Our fraud solution will always explain why a transaction has been blocked or flagged for review so analysts can demonstrate the reasoning to regulators. 

For many firms, the data and risk scenarios their fraud prevention vendor uses are critical. Some solution providers have data sets heavily weighted towards one sector, such as banking. This can mean that potential risks in other industries are left out. That’s why RealPage, a leading global provider of property management software, chose to work with ComplyAdvantage. The flexibility to build custom scenarios helped the company implement unique rule sets needed to screen property managers and their tenants. The near-real-time results seen by RealPage enabled fraud alerts to be reviewed immediately and allowed team members to mitigate the risk of fraud losses for its clients. 

The post Protect Your Customers with Real-Time Transaction Fraud Detection appeared first on ComplyAdvantage.

The company processes approximately 100 million payment transactions per year across a portfolio of more than 19 million properties located throughout the U.S. As a payments provider, RealPage has an obligation to its banking partners, clients, and residents to monitor transactions processed through its payment services and to identify and reduce instances of fraud and other illicit activities.

The challenge

“The biggest challenge we have is keeping up with constantly growing levels of fraud. Just when you get used to certain patterns and volumes, they change again,” explains Blanca Rojas, Transaction Risk Manager at RealPage. The risks and typologies RealPage need to account for are driven by its atypical business model. For example, it has to screen across business-to-business and business-to-business-to-consumer relationships – both real estate firms and their customers – while also analyzing how money moves between them.

RealPage designed specific scenarios designed to capture illicit activities such as card testing fraud. However, the COVID-19 pandemic also introduced new fraud typologies that also had to be considered. As outlined in a FinCEN report (FIN-2021-NTC1) released on February 24, 2021, financial institutions, including payments companies, had to comply with reporting requirements on COVID-19 fraud activity. With such complex, fast-changing requirements, speed is essential. As a result, a reliance on manual reviews of customers and transactions would not deliver the scalability and efficiency RealPage requires.

The solution

While RealPage did engage in a “buy vs build” debate, the firm quickly made the decision to partner with an external vendor. “We felt it was important to work with a company that had expertise in transaction monitoring, could understand our regulatory requirements, and how to apply these to our unique business model,” explains Rojas.

ComplyAdvantage appealed to RealPage because its transaction monitoring client base extends beyond traditional financial institutions. “Other software providers we looked at just had generic scenarios that were geared towards traditional financial institutions, rather than payment companies. Our business model is different even to other payment providers,” said Rojas. “The flexibility to build custom scenarios was important for us. Many vendors do not have the same level of flexibility.”

During the implementation process, RealPage met with ComplyAdvantage’s development team to explore the best way to implement its unique rule set. This included the need to follow individuals across different properties and state jurisdictions, as well as identifying connected individuals. “One of the ComplyAdvantage developers suggested a way to achieve our rule objectives which was eye opening. It helped us to see our challenges in context,” Rojas noted.

Once live, the RealPage team worked with ComplyAdvantage to tune the logic of its rules, simplifying the number of data points they were screening. This included a range of above and below the line testing and assessing the potential impact of raising/lowering risk thresholds.

“I am seeing the activity in close to real-time – seconds. I have worked with different software providers at different institutions, and the rapid response to alerts is the biggest benefit I have seen.”

– Blanca Rojas, Transaction Risk Manager, RealPage

For Rojas, the biggest benefit of the ComplyAdvantage transaction monitoring platform is its near real-time capabilities. “I am seeing the activity in close to real-time – seconds. I have worked with different software providers at different institutions, and the rapid response to alerts is the biggest benefit I have seen.” This means RealPage can immediately review alert activity and act as necessary to prevent significant losses for its clients. Rojas’ team tracks cases and bad actors frequently and can see what they are able to achieve with the platform, and which rule sets are most effective at preventing illicit activity.

The case management functionalities in the transaction monitoring platform are also “streamlined and easy to use,” improving the efficiency of Rojas’ team and ensuring that all investigation documentation is properly logged and easily accessible.

Managing and triaging alerts effectively, escalating from junior analysts where necessary, is also seamless. “The dashboard reporting helps us to monitor the whole department so we can make sure alerts are cleared on time and we’re not getting behind on anything,” said Rojas. “The color coding means we can immediately see if there’s something that’s past due.”

Ongoing support provided by ComplyAdvantage’s customer success manager is critical. “She is hands-on, she has learned our system, and knows the ins and outs of RealPage’s business model. This means she can produce innovative ideas, communicate those to development, and explain why we need them,” said Rojas. Regular scheduled meetings enable the team to review issues and plan for new scenarios the team would like to implement. Quarterly success meetings provide RealPage with reporting on how its scenarios are performing, providing an external set of checks and balances on internal tests.

Next steps

RealPage is now working with ComplyAdvantage to ensure its transaction monitoring program scales with its rapidly growing business. The firm recently integrated a new segment of its business into the platform and is working with its customer success manager to assess next steps based on projected dollar and transaction volume amounts. Above all, Rojas says, we are “ensuring there’s room for growth, so the product can grow with us.”

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For example, a recent report by ComplyAdvantage and the FinTech FinCrime Exchange found soaring levels of concern about smurfing and money muling. Yet asked if they felt confident in their firms’ ability to identify and mitigate attempts at smurfing, 77% answered only ‘Yes – for the most part’. This suggests there are potential gaps and weaknesses in current approaches, including transaction monitoring rules. 

As a baseline, the report highlighted the three foundational categories of an effective transaction monitoring system:

1. Value: The overall value of funds transferred over a specific time period 
2. Volume: The overall number of transactions in a given time period 
3. Velocity: Rules designed to identify rapid movement of funds, typically over a shorter period of time than volume focussed rules

But with typologies changing rapidly and many firms – especially FinTechs – faced with large volumes of customer data to structure and process, how can compliance teams achieve the dynamic risk scoring they need to stay ahead of emerging risks?

Developing effective rules can also be difficult and labor-intensive. In some instances, firms may have to rely on template-based rules built by their vendor, which are highly restrictive and risk generating higher volumes of alerts. 

That’s why ComplyAdvantage offers a self-serve rules builder platform for its customers. This means compliance teams are able to create their own efficient and complex rules without writing any code. They can also test them in a sandbox before deployment, following a robust approval process. Defined roles and permissions for rule editors and approvers are included. 

Customers also have access to an in-house team of rule specialists who work on the construction and optimization of rules for businesses across the financial services industry. They bring their expertise on variations in a dynamic range of typologies to their work. Such experience can compliment internal rule building teams, delivering an effective ongoing partnership. Where firms don’t yet have rule building expertise in-house, support from ComplyAdvantage can serve as a valuable alternative. 

In addition, customers can search and add specific risk-related rules from a categorized library aligned to AML/CFT industry risk typologies. 

The benefits of this approach for compliance analysts include:

• View rules by status – Analysts can now see and understand their live rules, and how these have been applied across different segments using a risk-based approach 

• Edit existing rules – The autonomy to respond quickly to specific scenarios and continually improve their systems

• Flexible risk thresholds – Focus only on genuinely suspicious activity by setting different alert thresholds and treatments across a range of risk-based segments
• Fill coverage gaps – Meet evolving business needs without the need to design a new rule logic, and build custom rules where standard rule libraries don’t address a specific risk

Success story: Multipass

Multipass, a multi-currency business account designed for managing international bank transfers, has improved its compliance processes through using ComplyAdvantage’s rules builder. 

“The ability to see the details and conditions of each rule gives us a much better understanding of our performance,” said Anastasija Marusjaka, Senior Compliance Analyst. She added that “we can do this independently and understand the reason why alerts trigger, and how we can improve our system.”

“The best thing about ComplyAdvantage’s rules builder is that there is the ability to use previous data and create new rules. This helps me understand our rules and improve them. Day by day, we get better.”

Request a Demo

Discuss how the ComplyAdvantage self-serve rules builder can help meet your team’s transaction monitoring solution requirements

Request a Demo Today

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Download the guide to explore questions including:

• What are KYC and Digital ID processes, and why do they matter?
• What is the latest on the regulatory landscape in the UK, US and European Union?
• How should firms look to appoint an MLRO?
• How can the ComplyLaunch program help early-stage firms?

The post Anti-Money Laundering Essentials for Startups appeared first on ComplyAdvantage.

Because of this, money laundering is a high priority for the legislators and officials who oversee the world of finance. New anti-money laundering strategies are constantly being created to track down and stop money launderers, and the technology used to do so is evolving at a rapid pace.

What is money laundering?

The Financial Action Task Force (FATF) defines what is money laundering as “the processing of criminal proceeds to disguise their illegal origin”. Some of the major contributors to money laundering are organized crime, drug trafficking, and smuggling, all of which can generate a substantial amount of money that requires “cleaning” before the criminal can use it in a legitimate financial system without being detected.

Across the globe, financial institutions such as banks, capital market firms, and insurers are some of the most favored channels used to launder illicit funds. One reason that money laundering can be so difficult to track down is that it is necessarily related to other crimes. Criminals will often attempt to transfer money through several countries to obscure its illegal origin, involving multiple people and multiple bank accounts. 

Of course, this means that criminals typically committed another crime through which they obtained the illicit funds they then sought to launder. When multiple counts of money laundering and interrelated criminal activity become interwoven like this, a complex network of illicit activity is created that is problematic to fully track and break down.

How Does Money Laundering Work?

While the ways criminals can launder money are diverse, the methodology remains generally consistent. The three stages of money laundering are:

Placement

The initial placement stage refers to the introduction of illegal cash or money obtained through illegal activity into a legitimate financial transaction system. Cash deposits, wire transfers, and other financial instruments are used at this stage to move the funds away from being directly associated with the crime.

Layering

The next stage is where legally sourced money is “layered” or entwined with the illegal funds that have been placed in the financial system. The intent at this stage is to obscure the audit trail of the financial sum involved, which can look like the criminal buying and selling stocks, commodities, and real estate, often across multiple borders. 

Integration

The final money laundering stage is reached when the “dirty” money and the “clean” money have been combined to the point that all of the funds appear legitimate. When the criminals have a seemingly legal explanation for the placed and layered financial assets, the funds can be received from their original illicit source through means that do not draw attention, allowing them to use the funds freely in the regular monetary system.

Examples of money laundering

When it comes to money laundering, criminals can utilize a variety of methods, schemes, and techniques to move or conceal their illicit funds. Compliance teams must be able to effectively recognize money laundering typologies to mitigate against the risk of financial crime and ensure regulatory compliance as a regulated entity. Common money laundering typologies include:

Money mules

A “money mule” is an individual who has been recruited by criminals — whether wittingly or unwittingly — to act as a proxy in the placement of criminal funds into the system. Things to look for include small transaction amounts and young people who may be less aware of the legal implications of their actions.

As money muling networks are often made up of large numbers of individuals across jurisdictions, when suspicions arise, firms should try to build a picture of any relevant associates. 

Smurfing

The typology of  “smurfing” involves moving large amounts of illicit money through the financial system by making smaller transactions. “Smurfs” will often spread these smaller transactions across multiple bank accounts to avoid detection and remain under regulatory reporting limits. 

As networks are extensive enough to move large sums of money quickly, smurfing is likely to be used in conjunction with money muling. To mitigate against this risk, transaction monitoring thresholds must be appropriately calibrated to the bank’s risk-based approach.  

Virtual assets

Although the vast majority of placement and money laundering layering is still undertaken in fiat currencies (i.e., the Euro, the US dollar, etc.), virtual assets (especially cryptocurrencies) are emerging as a growing component in the complex process of layering funds. 

Over the last few years, money laundering involving cryptocurrencies has become increasingly common. For example, the proceeds of cyber fraud or blackmail could be initially collected on Bitcoin, but then traded through several cryptocurrency exchanges for a variety of other cryptocurrencies, including privacy coins, before being cashed out.

Is money laundering illegal?

Whilst the illicit origins of the funds being laundered are what make money laundering schemes illegal, the act of money laundering is an offense in its own right. In addition to receiving a sentence for the predicate crime (a component of a larger crime that generates monetary proceeds), criminals can receive up to 14 years in custody for money laundering offenses, in addition to mandated fees and restrictions.  

However, some countries, including Germany, have made a legislative shift to separate money laundering from predicate offenses, thus expanding criminal liability beyond what was previously outlined in the country’s catalog of suitable predicate offenses.

Comply with AML regulations

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How is money laundering prevented?

Anti-Money Laundering (AML) refers to the procedures, policies, programs, and technologies that financial institutions must put in place to monitor fraudulent activity. Some AML controls include Know Your Customer (KYC) policies, record management and software filtering, holding periods, and sophisticated new technologies such as AI to monitor financial risk in real-time. 

Technological innovations have made it substantially easier to discover when the financial system is being abused, as well as to gather information about the individuals who are abusing it. Manually searching for data and monitoring accounts is tedious, inefficient, and often ineffective. Fortunately, screening systems have replaced this old-fashioned process, and have made it easier than ever before to monitor clients and determine if someone is laundering money.

To aid the fight against money laundering, many governments now legally require all financial institutions and many companies to report any suspicious activity that they notice among their customers. These institutions include banks, payment and insurance companies, casinos, money exchange companies, and numerous others. It would be impossible for governments to catch all the criminals involved in money laundering independently, and the same can be said for business and financial institutions. But when both the private and public sectors work together in order to combat this ubiquitous crime, their success rate dramatically increases. 

If a company or financial institution inadvertently completes a transaction that pertains to money laundering, it can face extensive legal and financial repercussions. Even if the mistake is entirely accidental, it may still be prosecuted. If corrupt employees actively aid money launderers, the employees are dealt with very harshly on an individual level and the institution may still incur liability. Because of these risks, most institutions go to great lengths to make sure that they properly monitor clients and their accounts. For businesses and banks, it is simply not worth the risk to be negligent and accidentally wind up involved in money laundering.

In order to further mitigate the risk of money laundering, updated and enhanced AML regulations are due to continue throughout 2022.

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