Financial crimes continue to surge. Criminals are getting more sophisticated, and the stakes are higher. According to a recent report by Nasdaq Verafin, global losses in 2023 due to fraud scams and bank fraud schemes totaled USD 485 Billion. Kroll’s Fraud and Financial Crime Report reveals that 67 percent of the survey respondents anticipated a significant increase in financial crimes in 2024 compared to 2023. In response, Fraud and Anti-Money Laundering (FRAML) convergence is emerging as a game-changer in how financial institutions combat financial crimes.
Traditionally, banks and financial institutions have distinguished fraud from money laundering. Fraud detection happens at different points, from customer-level disputes and chargebacks to system-level transaction monitoring, data analysis, behavior analysis and anomaly detection. Conversely, money laundering often requires a more direct approach, with systems spotting and triggering alerts for illegitimate customer activities.
However, this distinction can lead to missed opportunities and inefficiencies. By integrating AML and fraud detection systems, financial institutions can enhance crime prevention while reducing costs – especially when financial crime compliance costs in the U.S. and Canada alone are hitting USD 61 Billion annually.
Benefits of a Unified FRAML Approach
So, what value does a unified FRAML approach deliver? Let’s look at some of the significant benefits:
Enhanced Detection and Prevention
When fraud and AML teams work cohesively, they can detect suspicious activities that might otherwise slip through the cracks when operated distinctly.
Reduced False Positives
By integrating fraud and AML systems, you can more accurately distinguish between legitimate transactions and potential threats, saving time and resources.
Streamlined Investigations
Combining fraud and AML functions can reduce duplication, accelerating the accurate detection and escalation of fraudulent activities.
Comprehensive Risk Profiles
A unified approach lets you analyze customer behavior across products and services. This helps create complete risk profiling, translating into stronger defenses against financial crime.
Regulatory Support
Regulators encourage collaboration between money laundering and fraud prevention teams to improve regulatory compliance and reporting outcomes.
Cost Efficiency
Integrating fraud and AML investigation teams reduces the need for distinct systems and processes, creating cost efficiencies for enterprises.
Advanced Technologies
Artificial Intelligence (AI) has a vital role to play, sifting through mountains of data to create accurate risk profiles and identify potential threats before they become full-blown problems.
Challenges in Implementing a FRAML Solution
Implementing a unified FRAML solution has its challenges. Here are some of the potential roadblocks:
- Data Integration: Integrating existing tools and data from different systems can be complex, especially in traditional banking environments. This challenge requires robust technological solutions to ensure seamless integration and effective operation.
- Cultural Shift: Changing how fraud and AML teams operate isn’t about technology alone – it’s about mindset. Getting everyone on the same page can be challenging but necessary for success.
- Navigating Regulatory Hurdles: Different countries have different rules for reporting fraud and money laundering, which can complicate things. Institutions must carefully navigate these complexities to ensure compliance.
- AI Explainability: Ensuring AI systems can provide clear and understandable explanations for their decisions is crucial, particularly for compliance and internal audits. This transparency is essential for maintaining trust in the system's outcomes.
- Cost and Resource Allocation: Upgrading to a combined solution that addresses fraud and money laundering irregularities can be resource-intensive. It demands significant investment in technology, training and ongoing maintenance of systems and algorithms.
The Industry Perspective
When adopting this unified approach, there could be a noticeable difference between traditional banks and digitally native institutions like FinTechs and neo-banks. The newer players tend to be more flexible and collaborative, making it easier for them to integrate fraud and AML efforts. Traditional banks, on the other hand, often face more significant challenges due to legacy systems and entrenched silos.
Ultimately, an institution’s decision to adopt a converged approach to fraud and money laundering must be based on its unique circumstances. However, as financial crimes continue to evolve, the benefits of convergence are becoming harder to ignore. By embracing this unified approach, financial institutions can effectively shield themselves, their businesses – and customers – from the ever-growing threat of financial crimes.
Read the second blog in this three-part series that dives into the technology aspects of FRAML – focusing on the six transformative benefits of adopting a unified technology platform.