How to Implement a FRAML Strategy in Three Steps
By Rebecca Lindley
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Adopting a combined approach to fraud and anti-money laundering (AML), sometimes known as FRAML, has recently been gaining in popularity. The convergence makes sense, as the disciplines are inevitably related, given the fact that fraud is a predicate offence for money laundering, with the illicit proceeds subsequently being laundered. There are also numerous logistical and practical reasons for uniting these teams. Particularly for smaller companies with limited resources, combining teams to adopt a FRAML model can make sense where budgets are limited, or compliance expertise is spread thin. One potential challenge with this model is the different skill sets required when dealing with fraud and AML. For example, fraud may involve sensitive customer communication, especially when dealing with customers who have been victims, and so require team members with strong customer service skills. On the other hand, AML operations typically require staff to be proficient at investigating and interrogating transactions. To handle both functions confidently, team members may require upskilling or training for a successful FRAML model.
Despite these potential challenges, this type of collaborative approach has been advocated by regulators for a long while. For example, the United States Financial Crimes Enforcement Network (FinCEN) has stated that financial institutions should promote “communication and collaboration among internal AML and countering financing of terrorism, compliance, business, fraud prevention, legal, and cybersecurity departments”. Regulators are thus clear that collaboration is the cornerstone of any successful anti-financial crime programme.
Three steps for an effective FRAML strategy
To implement a FRAML strategy that successfully merges fraud and AML, financial institutions can follow these three steps:
Step One: Design a roadmap
The first step to implementing a FRAML strategy is designing your roadmap. Start by considering the basics of your firm, including its size and scale, current teams and operations, and common relevant typologies and trends. Use data to support your assessment. Some examples of data points that might feed into your roadmap include:
- Number or percentage of transaction monitoring alerts that are triggered due to money laundering
- Number or percentage of transaction monitoring alerts that are triggered due to fraud
- Percentage of total transactions over the last year that were fraudulent
- Total value of fraudulent transactions over the last year
- Planned customer growth over the next year
- Projections for money laundering or fraud rates over the next year
- Current number of staff dealing with money laundering and fraud
- Number of staff potentially needed considering growth projections of customer and transactions
|Considerations when designing your firm’s FRAML roadmap:|
– What is the size/scale of your firm?
– What products do you offer, and what are the corresponding fraud and money laundering risks?
– What common fraud and money laundering typologies, and associated trends, are affecting your firm?
– What do your fraud and AML operations currently look like?
Next, carry out an inventory of your current tools, systems, and processes and use key performance indicators to determine how they are performing. For example, look at false positive rates for alerts to assess the effectiveness of your monitoring programme. Additionally, you can analyse suspicious activity report output to identify your primary areas of risk exposure. This assessment, which is a snapshot of the present, is your starting point. Once you have all this information assessed in one place, the next step is to look at the future.
“When planning a FRAML strategy it’s important to review roadmaps from previous years, looking at your success criteria, what you achieved and didn’t achieve and understanding the why. You can look at what worked and ask, ‘how do we do it again?’ That will help from an operational perspective of staying on track” – Matthew Tataryn, Director of Financial Crime Risk & DMLRO at Tide
As part of future planning, begin by outlining clear, achievable, and incremental goals for your FRAML operations. Summarise these objectives, targets, and metrics in a concise but meaningfully detailed manner to guide your planning and work backwards to figure out what you need to achieve them. Before setting your goals in stone, communicate them to all your stakeholders and solicit feedback. Ensure that you involve the correct people in the planning stage, and stick to realistic timelines.
Step Two: Develop systems across the anti-financial crime process
A FRAML model requires breaking down silos within your organisation. Consider what your existing processes will look like across Know Your Customer (KYC), customer due diligence (CDD), screening and ongoing monitoring once this is done. Scrutinise how these processes will capture nuances for fraud, money laundering, and other financial crimes. Remember – when it comes to fraud processes must be fast, often requiring automated action to prevent losses by the bank. This may require some procedural variations or tweaks – for instance, holding payments which trigger a transaction monitoring alert because of a fraud typology, rather than flagging them for future review and possible Suspicious Activity Report filing.
Open source intelligence (OSINT) can assist with both fraud and AML processes, providing a meaningful and versatile tool in a FRAML model. Regulators have always expected adverse media screening to some degree, an expectation that is set to increase given the move to a risk-based approach where knowing your customer throughout all phases of the customer lifecycle is more important. In fraud, OSINT helps with proactive risk management, where screening subjects and cross-referencing against authoritative databases and lists can help stop fraudsters being onboarded in the first place. OSINT also assists with reactive fraud risk management, which complements the work of monitoring systems and advanced data analytics, allowing you to dig deeper into a subject and spot patterns and networks. OSINT as a tool can help you learn more about your subject and make your next move more strategic when combating both fraud and money laundering.
Once you’ve developed your anti-financial crime systems within a FRAML model, you’ll need to continuously monitor and evaluate them to ensure they’re effective and capture emerging threats and trends. Having set touchpoints to review critical metrics and analysis will ensure overall effectiveness. Like any anti-financial crime programme, you should be prepared to adapt your strategy as needed.
Step Three: Use the right technology
Once you’ve set out your anti-financial crime processes in line with a FRAML approach, consider which vendors will best support your programme. The optimal way to determine this is by being clear on exactly what you need to achieve and matching this with the most suitable vendor. When teams use the same technology, they can reinforce each other and create a better environment for collaboration and cohesiveness. It is also more cost effective to encourage consolidation and use the same tools for both fraud and AML processes. And when processes are siloed, you run the risk of one team adopting tools which other teams are not aware of or don’t utilise to the full, meaning you don’t get the best possible use out of them. However, not all vendors can do everything in your workflow. Finding a balance is essential.
As with processes, remember to tease out any specific requirements relating to particular areas. As mentioned previously, fraud requires almost immediate reactions and so tools that offer real-time detection are particularly important. However, overall fraud and AML efforts require similar information access and technological capacities, so the benefits to developing a joint tech stack are clear.
“Building tools and systems is hard work. It takes a huge amount of resources and time. And as you build systems, things are already changing. Vendors that are specialists can keep up much quicker, adapt to changes, and feed in multiple external data sources you may not have access to. Of course, no one-size-fits-all vendor can fix all your problems. Don’t fear using different vendors and combining them to build a process that is right for you.” – Matthew Tataryn, Director of Financial Crime Risk & DMLRO at Tide
How Videris Can Help
OSINT tools like Blackdot’s Videris help both AML and fraud teams streamline their research and investigation in a single interface. It allows investigators to search across multiple disparate data sources (e.g. search engines, news and social media, corporate records etc.) to quickly identify relevant information on their subject and stop fraudsters and other criminals in their tracks.
With AI capabilities that screen high data volumes and rank sources for reliability, investigators can speed up their processes and improve investigation outcomes.