There is a natural flow of data surrounding our digital life that is captured by entities and companies that we interact with. This data needs to be properly used, stored, analysed, and secured by online organisations, in a way that leaves the user experience is fast, frictionless, and secure.
This might create a situation when an organisation must stitch different solutions/technologies together to manage the user journey in terms of authentication, identity verification, onboarding, and transaction monitoring, while also being capable of detecting and preventing fraud from happening. As a result, the worlds of identity verification, compliance, and fraud detection are increasingly intertwined, and a close collaboration within different parts of an organisation (by sharing and bridging data) and with third parties (other banks, TPPs, law enforcement, etc.) can facilitate a more efficient and effective defence.
Sometimes technology, data, and teams are working separately, and inadequate means to integrate technology silos are preventing organisations from fully utilising their data. Strictly referring to banks, analysts could be challenged by huge amounts of data required for client activity reviews and because this data is often split across different silos, there is a lack of cohesion between systems and departments.
Financial institutions’ analytic and detection capabilities can be enhanced by aggregating customer information that comes from the close collaboration of groups addressing financial crime, fraud, and cybersecurity. After all, not helping each other is dangerous to consumers and it puts the fraud fighter community at a disadvantage, especially in industries where knowledge-sharing practices are lagging.
What is currently happening?
When it comes to financial crime, there are two parts that need to be thoroughly analysed:
- Theft – the obvious/direct/visible effect of fraud (e.g. authorised push payment fraud, account takeover, phishing, benefits fraud, etc.) and cyber-crime (e.g. data breaches, malware, etc.). It is a clearly defined financial crime with negative impact that can be directly measured.
In 2020 identity fraud losses climbed to USD 56 billion, with identity fraud victims disappointed by their financial services providers because they did not satisfactorily resolve their problems. The intense use of digital channels has caused an increase in fraud rates in social networks and bot attack spikes.
- Money laundering – which is not theft, nevertheless the effects are even more devastating. It happens when cash in flows on profits from (or payment for) drug trafficking, sex trafficking, or terrorist financing get processed by banks, to ‘clean’ it. So, despite huge amounts of investment and efforts focused on regulatory reporting, our global banking system continues to be an enormous enabler of crimes.
2020 has brought big penalties for banks, as these have been hit with USD 10.4 billion in global fines related to anti-money laundering (AML), know your customer (KYC), data privacy, and Markets in Financial Instruments Directive (MiFID) regulations. To compensate for these losses, banks had to reduce costs by cutting jobs and become better in data automation.
On top of these, fraud fighters are impacted by topics and regulations such as PSD2, SCA, Open Banking, AMLD6, e-KYC, data privacy and data protection, push payments, etc.
Human + machine
When it comes to fighting financial crime, many have placed their bets on the use of data and technology, but despite this, William Brown, Global Head of Watch list Screening, Bottom line agrees that ML/AI technology is not the silver bullet for AML compliance and risk mitigation. In truth, a successful AML compliance program requires a mixture of adequately trained staff, adaptable technology, formalised processes, pertinent data, and timely management reporting to implement acredible risk-based approach (RBA).
For instance, collaboration among teams improves threat prediction and detection while eliminating duplication of efforts and resources. By constantly updating customers’ risk scores, institutions can dynamically renew their view on the riskiness of clients and transactions. The integrated approach to fraud risk can also result in an optimised customer experience.
Alone we can do so little; together we can do so much
The concept of sharing data to spot fraud goes beyond groups within an organisation; when multiple entities combine their data, they can piece together a mosaic of criminal activity, which in isolation can be more difficult to spot, thus creating actionable insights. Many banks understand that one of the best ways to protect themselves against financial crime is by sharing intelligence to collectively learn from one another and set necessary measures to prevent and minimise future scams.
Examples of best practices on data sharing include UK’s Joint Money Laundering Intelligence Taskforce (JMLIT) - a partnership between law enforcement and the financial sector to exchange and analyse information relating to money laundering and wider economic threats – and the Transaction Monitoring Netherlands (TMNL) – an initiative developed by five Dutch banks (ABN AMRO, ING, Rabobank, Triodos Bank, Volksbank) focusing on identifying unusual patterns in payments traffic that individual banks cannot identify.
In Lithuania, Bank of Lithuania has taken the bold initiative to develop a Centre of Excellence in Anti-Money Laundering based on public-private partnership principles. The centre is set up to mobilise public and private AML/CTF efforts (combating the financing of terrorism) as well as to strengthen the prevention framework.
In the UK, FINTRAIL and the Royal United Services Institute (RUSI) created the FinTech FinCrime Exchange (FFE) - a strong community for fin crime fighters where participants share new typologies and trends, how criminal activity was detected (red flags), and the controls they have since put in place to manage the risk (best practice).
With the ramp-up of instant payments that has opened new doors for fraudsters operating across different countries, PSPs need to be capable of following fraud across borders and to allow relevant parties to join forces in fighting it. In 2020, the Euro Banking Association (EBA) launched a fraud expert group that aims to identify the minimum requirements for enabling a pan-European fraud intelligence approach. Currently, according to Thomas Egner, Secretary General, Euro Banking Association, the group is finalising a pan-European fraud taxonomy to help practitioners to categorise fraud cases in a harmonised fashion and provide a common basis for any intelligence and data sharing activities.
All in all, AML, fraud, cybercrime, internal corruption, trade compliance, and trafficking are often different departments, with different budgets, organisational focuses, and often with different technologies, thus always maintaining blind spots in the fight against financial crime. But by finding a common language, breaking down the silo mentality and developing cross-departmental ways of working, leveraging data and technology to support the integration of systems and operational transparency, financial institutions are better equipped to navigate the tumultuous sea of financial crime.
Like this story? To learn more about fraud prevention, identity management, digital onboarding and KYC, transaction monitoring, financial crime compliance, regtech, and more, download The Payper’s Financial Crime and Fraud Report 2021 - How to Fight Fraudand Master KYC, Onboarding & Digital ID.
About Mirela Ciobanu
Mirela Ciobanu is a Senior Editor at The Paypers and has been actively involved in drafting industry reports, carrying out interviews, and writing about innovation in payments and fintech. She is passionate about finding the latest news on AI, crypto, blockchain, DeFi and she is an active advocate of the need to keep our online data/presence protected. Mirela has a bachelor’s degree in English language and holds a master’s degree in Marketing. She can be reached at email@example.com or via LinkedIn.