Slamming the Scammer

We are living in the age of the scammer. From fraudulent Covid Bounce Bank Loans costing the UK Government some £4.9 billion, to online romance scammer “The Tinder Swindler” and real-life con artist Anna Delvey in Inventing Anna, we can’t go a day without a new story on financial crime. The temptation of easy money has never been so mainstream, so why is fraud becoming an ever-increasing struggle for businesses and proving so hard to crack down on?   

There has been a revolution in banking over the past few years. Fast payments have become the norm, making real-time liquidity a vital part of corporate banking strategy. In an age where customers expect instant payments, easy account setup online, and frictionless banking, technology is forced to constantly evolve. But the potential threats they pose are evolving too.   

Scammers’ methods are changing, now able to con even the savviest online customers and businesses with the latest tech. Banks are having to find the balance between giving customers the intuitive, convenient banking experience they desire, whilst ensuring they meet the levels of security now required in the new economic landscape. They must invest in the right infrastructure and solutions to ensure they remain one step ahead of the new wave of online criminals. 

Who is today’s scammer? 

It’s no longer just a case of whispering in the ears of investors, colleagues or potential customers to hoodwink and defraud them. Today’s scammer lives online, building ever-sophisticated methods to dupe their victims. In the past two years alone, there has been a 43% increase in fraud and computer misuse, cementing this threat as now greater than all other crime put together. 

The Financial Conduct Authority refers to it as ‘a multi-layered threat landscape, enabled by a low-risk-high-reward model’, with each cybercriminal posing their own unique method or threat, such as phishing, pension liberation scams or money laundering. With sprawling online estates and endless data to process, financial crime has become a massive challenge for banks, as it proves more and more difficult to ensure that all threats are detected, and bases covered. It is easier than ever to trick people online – you no longer need to be technologically sophisticated, nor do you need the charm of the Tinder Swindler. You can simply log in to online tools and let the technology do the work for you. So, how can financial organisations fight this new breed of scammer and protect their customers’ assets? 

Innovators fight back 

Fortunately, the fraudsters aren’t the only ones to have become more advanced in their methods. With hundreds of millions of transactions, thousands of customers, and a wide variety of complex entities run under different directors to contend with, this is where innovations in cloud, Artificial Intelligence (AI), and Machine Learning (ML) come in. The first step is to combat the complexity with this technology and streamline your data estate, making it easier to pinpoint problems and apply solutions organisation-wide. 

Tackling financial crime is a volume game. In the past, firms may have looked to up their headcount to handle an increase in transactional volume and complexity, seeing no other option than to draft in more recruits to fight crime. However, banks are now turning to technology to do the heavy lifting, with automation solutions now able to take some of the burden off overstretched finance teams.  

Cloud-based AI and ML solutions can sift through exponential financial data to build a 360-degree view of the customer, gain a centralised view of any suspicious events, and detect new schemes and entry points. This technology also allows financial organisations to run Anti-Money Laundering (AML) scenarios across all channels, lines of business and customer lifecycle stages, all in a fraction of the time that their human counterparts can. In other words, you can keep your headcount consistent, whilst teams increase their output and assign themselves more value-add tasks.  

Externally, banks are always striving to satisfy the regulator and ensure that they are falling within regulations. Processes must be rapid and accurate to provide regulatory bodies with the data and evidence they need, and the regulator must be able to test a system’s capabilities, pushing it to its limits. Using AI-powered, institution-wide investigation and case management reduces the volume of suspicious activity reports and ensures total transparency For instance, ML can help to identify money launderers and comply with Customer Due Diligence (CDD) and Know Your Customer (KYC) regulations throughout the entire customer lifecycle. Once all data is brought together in one place, it makes finding and reporting information to the regulator a breeze. 

These technological advancements in AML software allow organisations to quickly and accurately assess risk and compare customers to global sanctions and watchlists across a massive dataset. It becomes easier to identify and deal with fraudsters and criminals through the entire industry, regardless of location, and act faster to save customers’ assets. 

Laying the foundations for the fight against fraud 

It’s a given that combatting financial crime in 2022 depends on a financial organisation’s ability to manage and analyse data effectively. However, banks must ensure that they make the right choices when they bring new software in-house, and take the right steps towards shutting it down.  

Financial institutions must look to modern crime detection software from trusted, third-party accredited suppliers that are levelling the playing field in the fight against scammers. This is an essential investment to enable CDD, transaction monitoring, investigations, and regulatory reporting – and partnering with the right supplier to cover all bases is crucial. With the right cloud infrastructure and applications in place to cope with the vast amounts of data passing through each day, banks and financial services firms can tackle financial crime at scale. Through leveraging ML on such a large dataset, it becomes easier to identify common patterns and keep pace with changing regulations. 

ML models can automatically adapt to these ever-evolving criminal behaviours, keeping up to speed with the latest patterns and identifying hidden criminal groups that could have remained hidden for months or years to come. This technology works in tandem with the workforce, using automation capabilities to reduce mundane tasks, and free up employees to add more value through detailed or strategic work. For instance, backed by intelligent automation that lightens day-to-day workloads, financial investigators can then spend less time searching for customer information and sifting through false positives. Armed with automatically collated customer profiles, they can spend more time doing what they do best -catching offenders.  

Future-proofing protection 

The velocity, complexity, and expanded opportunity for financial crime requires financial services organisations to rethink and retool their approach. Remaining compliant, secure, and protected in this new era of financial crime can be tricky. The bad actors have evolved, but so have the tools to fight them, with cloud, AI, and ML proving mighty opponents. To stay one step ahead, the finance sector must turn to cloud solutions for the capabilities and flexibility to adapt to threats as they continue to evolve, confronting fraudsters head on.  

With the right solutions and infrastructure in place, banks can not only protect their customers from today’s risks, but also prepare themselves for the fraudster of the future. Whatever these scammers come up with next, banks will be ready.