Better the devil you know: How AML technologies are giving banks insight into cybercrime

European Practice Leader, Counter Fraud and Financial Crime, IBM

For years, many organizations have accepted financial crime as an inevitable, albeit unwanted, side effect of doing business. But increasingly tight regulations are forcing companies to face crimes such as fraud and money laundering head on. Substantial penalties await those that fail to comply with new rulings such as the fourth anti-money laundering (AML) directive from the European Union (EU), which impacts a range of companies from financial institutions to gambling operators.

The AML directive, like similar regulatory instructions in the US, points to an increased focus on knowing your customer. But that part is just the beginning. Businesses need to determine who their customers are and, crucially, who they do business with. 

What’s in a name?

When it comes to cybercrime, regimented organization is the name of the game—80 percent of all incidents stem from organized criminal activity rather than opportunistic attacks. Businesses need to be aware of this fact and act accordingly. Creating false companies and using fake names are two of the most common weapons in a cyber criminal’s arsenal. Even something seemingly innocuous such as the alternative spelling of a name can mask the true identity of a customer—is it an innocent mistake or a ploy to create multiple identities? Businesses need to ensure that all customers are exactly who they say they are. 

Rule- or profile-based search engines employed by most organizations aren’t sophisticated or agile enough to keep up with—let alone stay ahead of—increasingly sophisticated cyber criminals and ever-tightening regulations. Entity analytics is a key tool for uncovering the duplicitous identities in your database, moving you closer to an unobstructed view of your customers. Entity analytics uses probability-driven party matching to identify duplicate identities and group them together, weeding out potentially fraudulent accounts and referring them to be identified manually. 

Know their networks you know who is whom, you can begin to determine who knows whom. With data scattered across innumerable accounts and geographies, finding patterns and links between identities is a daunting task—but it’s not insurmountable. Non-Obvious Relationship Awareness (NORA) technology was developed in Las Vegas and was initially designed to prevent fraud in the city’s casinos. The technology applies analytics to discover entities that share key attributes such as names, phone numbers and addresses to reveal relationships that might not have been picked up by conventional methods, such as between a dealer and a punter. This technology that forms the basis of entity analytics is now a core component in the IBM Counter Financials Management solution. It unites previously disparate data and provides context to enable organizations to uncover previously unseen relationships among their customers.

Visual link analysis tools such as IBM i2 Enterprise Insight Analysis also help dissect a customer’s network, enabling businesses to crunch large volumes of data and visualize a customer’s social network to spot anomalous links and relationships. 

Get a clear view

As organizations gain a clear picture of their customer base and their customer’s networks, red flags can be identified and handled. The benefits can be significant. For example, MoneyGram, an international money-transfer corporation, was struggling to keep up with ever-changing compliance regulations and wanted to tighten its antifraud strategy. The company used entity analytics to interrogate its customer base and preemptively tackle potential threats, halting fraudulent transactions totaling $37.7 million in just one year and shrinking consumer fraud complaints by 72 percent

Fraudulent activity and cyber crime are only going to become increasingly prevalent and sophisticated. For all businesses, ascertaining exactly who and what they are dealing with—including their wider networks—is crucial for tackling fraud and cyber crime quickly, consistently and effectively as they continue to keep up with regulation and compliance.

Businesses don’t have to accept financial crime; if they get to know it, they can minimize it. Read the IBM white paper, Gain superior clarity on identities and relationships linked to financial crime activities with entity analytics. Then learn more about using analytics to tackle fraud with IBM Financial Crime Management in a complimentary, customized workshop.