From Reporting to Rejecting Suspicious Transactions – Balancing Financial Crime Risk Management and the Customer Experience

Trying to prevent financial crime before it occurs is not a new concept for the financial services industry. In instances of fraud, for example, there is a clear obligation for financial institutions to do whatever is required to prevent the completion of these transactions. This helps ensure that the financial institutions protect themselves, but more importantly their customers. However, in the case of suspected money laundering, the waters are somewhat murkier.

While there are clear policy objectives to avoid facilitating corruption, bribery, terrorist financing and tax evasion, anti-money laundering (AML) transaction monitoring programs have traditionally followed an “observe and report” process. Increasingly though, international compliance teams are choosing to stop transactions before they are executed – based on suspicions of money laundering activity. More and more, the industry has been asking itself if this approach of rejecting suspicious activity is a more effective strategy to prevent money laundering. And if so, what are the impacts on legitimate customers?

Is ‘observe and report’ enough?

From the Financial Action Task Force (FATF) down, regulators appear to be focused on gathering financial intelligence more than preventing the successful movement of the proceeds of crime in to the financial system. The general guidelines are to report suspicions to a local FIU (Financial Intelligence Unit) and collaborate with law enforcement without tipping off the suspects.

When looking more closely at the specific language and structure of the FATF regulations, it becomes apparent that there is room for interpretation. For example, the fourth recommendation concerning Customer Due Diligence (CDD) as defined in the FATF Recommendations outlines that if a transaction is not consistent with what you would typically expect for an individual customer, the transaction should not be performed. That is not, however, the prevailing interpretation adopted by most FIs or expected by regulators in today’s paradigm.

Besides gathering intelligence into large databases to support law enforcement investigations, a business argument for “observe and report” is that blocking transactions which are in fact legitimate will alienate loyal customers. This inherently raises the question of where the “burden of proof” lies. While historically that burden of proof has often laid with the financial institution and local law enforcement organisations to demonstrate that the transaction is in fact nefarious, lately we’ve seen in some instances that there is a shift towards customers being required to demonstrate that the transaction is in fact legitimate.

Managing customer risk while upholding the customer experience

To what extent this proactive approach will be adopted to avert money laundering is still uncertain, but it brings to the fore key questions about how financial institutions can strike the balance between both managing customer risk and the customer experience.  

Certainly a key priority of financial institutions is their customers, and in particular the customer experience. Finding the middle ground between preventing financial crimes and providing fast, convenient services is something many financial institutions are working toward. How do you balance these two seemingly opposite business requirements so as not to lose valuable customer loyalty, whilst also protecting the business as a whole? How far can you go either way before emphasis in one direction affects the other component negatively? If compliance teams can utilise behavioural profiling and the ability to quantify risk mitigation through investigation, the threat of losing good customers due to the negative impact of an investigation can be minimised.  

New capabilities help balance AML prevention and the customer experience

The latest generation of behavioural monitoring and analytics help financial institutions transform AML “observe and report” operations into proactive monitoring of suspicious activity with a new level of precision that protects the rights of the vast majority of good customers. In addition, new capabilities for case investigation help expedite legitimate transactions to minimize any negative impact on the customer experience.

Introducing data analytics into AML programs drives significant improvements in the customer experience because analytics can learn from the deep activity history of legitimate transactions, confirmed money laundering activity, and “normal” activity for each customer to do a much better job of flagging suspicious transactions than ever before possible. Predictive models built by analysing historical data and joining it with the outcomes of previous alert and case review can discover hidden patterns indicative of money laundering risk.

These predictive models provide deeper insight into money laundering and other risks and give financial institutions more reliable information regarding which transactions require further investigation and which can be safely processed to ensure a positive customer experience. Behavioural profiling can also be used beyond just the initiating customer to evaluate any entity including counterparties, which helps better identify unusual or suspicious activity patterns. Other types of crimes, including human trafficking and elder abuse, can also often be detected through similar pattern recognition models and behavioural profiling that analyse funds movement and the various entities involved in financial transactions.

AML solutions that provide analytic models specifically built for false positive reduction (false positives are legitimate transactions that score high because of unusual but not nefarious customer behaviour) can be particularly helpful in balancing the need to investigate suspected money laundering activity with protecting the rights and experience of good customers. Well-built analytics can also demonstrate a transparent data driven risk-based approach to regulators.

This more sophisticated behavioural monitoring also enables financial services companies to expand their real-time interdiction capabilities. Financial institutions are well-versed in real-time interdiction as it relates to sanctions screening and watch lists for drug trafficking and terrorist financing. Now, with advancements in the precision of behavioural monitoring, real-time interdiction can be also be applied to suspicious transactions to increase money laundering prevention while preserving a positive customer experience for the vast majority of customers. Together, predictive models for more precise suspicious activity detection combined with real-time decision-making enables instant decisions to block suspicious transactions, where appropriate, before funds are released. On the flip side, real-time decisions also release genuine transactions for funding right away.

Is real-time right for all organizations?

There are some aspects of implementing real time AML detection which require some additional consideration, including specific regulatory considerations in certain jurisdictions. Clearly high-volume retail payments, such as a cash deposit at an ATM, do not lend themselves well for investigators to review prior to the completion of a transaction. In this instance, considering the time necessary to investigate is vital. This approach is more suitable for electronic payments, where sanctions screening also requires a window of time for analysts to decision the alerts. It is also important to consider the feasibility for an individual organisation and if leveraging the same solutions and personnel for AML monitoring sanctions screening and fraud prevention is the best technical solution for that operation. Vitally, real time detection requires an IT and operational investment for which the benefits (to the institution and/or to society) must outweigh the cost.

Moving forward

With spending on AML programs still growing, it is important to address the impact that such growth has had on the industry and its customers. The public is aware that financial institutions have structures in place to counter money laundering, so can it really be justified as a “tip off” when we scrutinize financial activity?

One argument against an open fight has always been that it would drive criminal financing underground, where it will be even harder for law enforcement to find. However, the sheer scale of the problem makes it hard to fathom that all the Hawala (money transfer without money movement) operations and virtual currencies in the world can accommodate such massive amounts of money.

Though it is a complex issue without one answer, it is perhaps time to accelerate the pace of the conversation and analysis. The technological capabilities to evaluate financial behaviour in real time and to detect unusual and suspicious transactions before funds are moved exist today, and there are a number of valid use cases for this capability, even if as an industry we are not yet ready to fully embrace preventing suspicious transactions from being completed. These same technologies also help us protect and expedite transactions for legitimate customers protecting their rights to prompt and convenient services.

With payments continuing to get faster, the financial industry has a long, complex road ahead when it comes to money laundering. The industry should look to re-evaluate the cost of the current AML approach versus its benefits, and compare that to the alternative of implementing preventative measures to combat money laundering, while always considering the convenience and safety of the end customer.