With the fourth EU Directive on Money Laundering coming into force in June this year and instances of financial crime becoming increasingly frequent, it is more crucial than ever for teams within Financial Institutions (FIs), as well as across the industry, to collaborate to tackle financial crime and fraud. In 2016, more than 75 cyberattacks were reported to the Financial Conduct Authority (FCA) in the UK compared to just five reports in 2014; the challenges of managing and combatting financial crime risk are becoming more and more difficult. The need to mitigate financial crime is particularly prudent given that statistics from CEB Tower Group show that fines from financial crime have increased by 55,000 percent over the past 10 years, thanks to more frequent and higher value attacks.
In order to tackle financial crime and to lessen the impact of fraudulent attacks, organisations need to ensure that they have the correct infrastructure in place. Anti-Money Laundering (AML), Know Your Customer (KYC) and fraud prevention solutions are all key to reducing and managing financial crime risk, yet knowing which one to prioritise can prove a challenge. Financial crime is unpredictable, therefore FIs need to implement prevention strategies and share resources between teams so that comprehensive customer profiles can be created. These profiles can make a huge difference in identifying unusual behaviour indicative of money laundering, tax evasion, human trafficking and instances of fraud. Ultimately such an approach helps FIs reduce the amount of overall investment required to manage financial crime risk whilst enabling more accurate detection of fraud and money laundering.
Data remains crucial
Implementing customer-centric infrastructure is only one benefit of collaborative work between teams and within the industry. The new EU AML Directive heightens the attention that FIs must pay to reputational risk and moral imperative. If a company is found to be a vehicle for money laundering activities for criminals, the reputational damage to that organisation is substantial. Customers will often feel exposed and take their business elsewhere. As CEB Tower Group found that only 14 percent of fraud departments amongst FIs have a complete customer-centric view, much more work needs to be done to ensure that more organisations invest in sharing valuable KYC and AML data.
Not only do these customer centric solutions ensure organisations manage risk, they also enable them to stay ahead of competition. If an organisation does not know and understand their customer fully, it is impossible to understand the risk associated with them. Combining customer centric profiles with data collected from consortiums of FIs can enable organisations to differentiate between what could be crime and what is just a slightly unusual transaction. With more accurate detection, we see greater operational efficiency.
The benefits of a customer-centric view
The way that customers interact with their institutions and manage their money is constantly changing. They want access to their financial assets through multiple channels and across multiple devices, whenever and wherever it suits them. Therefore, it is crucial that FIs gather data on every aspect of their customers’ behaviour no matter how they choose to interact with their institution. Cross-divisional work and collaboration ensures that thorough customer profiles can be compiled with threats identified more quickly and acted upon more efficiently.
Traditionally AML and fraud prevention teams have been siloed with each team gathering information on customers separately. However, research has shown that there is an 80 percent overlap in AML and fraud detection tools and processes, demonstrating the effectiveness of leveraging these assets across multiple groups to make financial crime risk management and prevention more effective and reliable.
Through collaboration and the integration of assets and processes, teams are able to leverage data more efficiently. In the case of fraud, the fraudulent behaviour is more likely to be recognised in time to prevent it with reduced losses and no negative impact on customers. Organisations need to determine what information to capture on customers to define the risk associated with each person. By automatically collecting and analysing data, companies are able to gather this type of information, evaluate it through a scorecard system, and quantify the risk each customer brings.
Being able to bring AML and fraud teams together creates a comprehensive KYC risk management strategy and ensures that suspicious behaviour is detected. Now more than ever, a common infrastructure that displays customer-level risk data at an FI level is essential if institutions are to pinpoint and tackle increasingly sophisticated criminal activity.
The key to success
FIs often have a rich pool of data covering customer behaviour which they can leverage, and often this data is included in systems like the FIs AML system. The richer this pool of data, the more informed and valuable the analysis of the data becomes, in particular the value of analytic models. Customer checks on fraud and AML risk typically happen as customers are on-boarded to identify their risk level. However, they also need to continue to carry out due diligence on customers and look for any unusual activity throughout their time as a customer. Joined-up AML and fraud teams and technology can compare customer behaviour relative to other customers and leverage best practices to accurately detect fraudulent activities, while also providing FIs with operational efficiencies.
Adding data from consortiums allows institutions to build a detailed picture of customer behaviour across entire industry segments. This more comprehensive understanding of customers ensures that organisations can recognise and flag unusual behaviour, allowing fraudulent activity to be detected accurately and immediately. In addition, it is also important for FIs to understand when a transaction follows typical customer behaviour to avoid halting legitimate transactions, and therefore leading to a damaging customer experience.
It is important to recognise that there cannot be a ‘one-size fits all’ mentality. Integrating assets and data needs strong management to make sure that anomaly detection systems are versatile and allow both AML and fraud teams to see problems in their entirety. Taking a risk-based approach ensures that an organisation’s compliance lens can focus on genuine suspicious activity and reduce disruption to legitimate customers. By progressively renovating systems, KYC data will stay up-to-date, flexible and constantly in action. This implementation approach acknowledges the necessity for converged data to make sure that organisations fully understand the customer and can manage financial crime across all channels.
In light of the EU AML Directive coming into force in June, and organisations working hard to use data to know their customers better in order to combat fraud and money-laundering, there is clear willingness from companies across the industry to explore the opportunities of collaboration. By collating and analysing data across the industry, it means a broader picture of customers can be seen and regulators can work with everyone to tackle money laundering and fraudulent behaviours; the sharing of information is something that is mutually beneficial to the industry as a whole. Both internal and consortium data enables organisations to create a clear view of customers and automatically analyse for suspicious activities in real-time. By knowing customers better and working with regulators and competitors alike, companies can adhere to these new regulations promptly whilst also providing a positive experience for customers.
Jameson White is a millennial attorney, law professor, entrepreneur, writer, and speaker on privacy, cybersecurity, A.I., AR/VR, blockchain, and digital monies. He has written for many outlets, and contributed to cybersecurity and technology publications.