Fighting Fraud During Extraordinary Times: Part 2 – Unlocking the Value of Data for Actionable Intelligence
October 12th, 2021
Thanks to the proliferation of digital channels, organizations have access to massive quantities of data that can be used to attract and retain customers, and mitigate risk. But understanding what to look for and how to interpret it is a challenge that financial services organizations (FSOs) are facing today.
These topics were a focal point of conversation during the recent NICE Actimize ENGAGE LIVE sessions, which included insights from leading industry experts, analysts, thought leaders, and practitioners on the current and future state of fraud prevention and detection as digital transformation continues to progress within a complex threat landscape.
Deriving insights from data requires specific capabilities, tools and skill sets. It’s also about understanding what data to look for, which data points are worth spending time on, and which data points aren’t as relevant. This isn’t a straightforward task and demands data management and fraud expertise, along with an industry-wide view of fraud trends in the form of collective intelligence. Fraud is dynamic and trends migrate, so being plugged into the industry helps organizations balance their fraud processes and the customer experience while proactively anticipating the challenges that other financial institutions are experiencing.
Data Segmentation and Categorization
FSOs don’t need years of data to accurately identify fraud trends. According to Ian Mitchell, Global Fraud and Financial Crime Executive, “Today the conversation is less about history. The intelligence and leveraging third-party sources and customer data across channels and products is critical. Balancing customer experience and stopping fraud – it’s a focus on getting as much intelligence from customers as you can.”[1]
To extract value from data, it must be segmented and categorized. There’s three key types of data that are particularly relevant for detecting fraud risks, and different data categories that can be used to identify specific fraud types for different scenarios.
Channel data covers information such as the type of device or communication in which the account holder is interacting with the bank, bank system, bank application or bank website. If it’s a web-based event, for example, this would include the IP address and browser information. If it’s a mobile device, then the information would include the mobile brand and mobile app version. This type of data is relevant in identifying account takeover or mule fraud, where a new device that’s been used for multiple different account holders would raise a flag.
Transactional data encompasses both monetary and non-monetary transactions, and includes all of the events that an FSO processes through their various banking channels. Information might include the transaction amount, login, time stamp and the event types, such as loan application, card application or wire transfer. This type of data complements channel data and helps identify payment fraud, social engineering, or authorized push payment fraud, for example, by examining changes in spending patterns such as unusual amounts for a particular customer that would raise the risk of a specific event.
Customer and account data includes customer and account information as it is represented in the bank’s CLM system, which might include names, addresses, phone numbers and account balances. This type of data is used to combat identity theft and new account fraud, for example, by determining if these data points or a combination of data points repeats itself with other customers and applications.
These three categories are crucial as organizations accelerate enterprise-wide digital transformation. Risk complexity, velocity and intensity necessitates that this data be captured, contextualized and leveraged to efficiently combat first and third-party fraud. “We have to keep up with that speed of fraud. I think where the industry is with the massive amount of data – not just data that can be breached, but just the sheer massive amount of data that’s available – that creates this perfect situation for identity fraud, account takeovers and synthetic identities,” Naureen Ali, Senior Vice President Fraud, Deposits & Payments at PenFed Credit Union shared.[2]
To understand the context of different threats, FSOs need the advanced analytics capabilities of an integrated fraud management platform that has the computing power and data availability to accurately contextualize risk and provide a single view of the customer across different risk types.
A Bigger Picture of Fraud
A common thread throughout fraud prevention and detection capabilities and best practices is the importance of data and collective intelligence. FSOs need high-quality, relevant, actionable data to help ensure success, as well as an industry-wide view of fraud trends and patterns defining the threat landscape in order to sharpen their approach to financial crime risk management. Ian Mitchell expanded on this, advising, “get plugged into the industry with groups that share this level of information, and proactively anticipate some of the experiences of other institutions that have a bigger footprint than yourselves.”[3]
Considering the shift to instant and faster payments, the growth of identity theft and synthetics, and the breadth of other fraud threats and digital disruption, cooperation across FSOs will play a critical role in the future of financial crime risk management.
Many European banks currently use a model of cooperation and data sharing. In Scandinavia and Nordic countries, financial integration and cooperation is facilitated via the Nordic Financial SUERF community. Member banks share non-sensitive data, such as mule accounts and login data, and other information that is essential to preventing attacks and promoting better financial crime risk management.
However, in the U.S., there are thousands of banking institutions, fintechs and community banks, and fraud is frequently addressed differently per institution. While common standards on fraud are continuing to be defined, many FSOs in the U.S. are eager to explore potential connectivity initiatives between institutions to communicate fraud trends and events more seamlessly than is currently possible.
NICE Actimize views cross-industry insight sharing as a strategic direction for the industry, and shares aggregated trends and benchmarking data. Sharing aggregated, anonymized data has been helpful in informing fraud strategies and priorities for participating institutions. For example, with information about merchant categories that are recently associated with fraud, a fraud strategist can build a fraud strategy that incorporates high risk merchant category codes (MCC), combined with transaction amounts and other out-of-band characteristics to maximize net fraud detection rates. Furthermore, they can analyze geo locations and compare with merchant category risk to develop stronger strategies.
Additionally, collective intelligence also enables FSOs to compare the effectiveness of their own fraud prevention programs against other financial institutions via insights into peer benchmarks. “It’s important to realize that risk appetite and transaction enablement vary across organizations, but there is still huge value in knowing how your organization compares to other peer organizations,” Yuval Marco, General Manager, Enterprise Fraud Management at NICE Actimize elaborated.
Accelerate Fraud Fighting in a Perfect Storm of Risk
Collective intelligence for financial crime management uses the power of many to transfer learnings and insights to fight crime faster than ever before. It gives fraud fighters a distinct advantage in staying a step ahead of the speed of fraud, and is a valuable asset in an environment of exacerbated fraud. “By the time that something hits the industry, it might not hit your individual organization, but because it will be on the collective intelligence, we will have that already accounted for. I think that’s very powerful,” Naureen Ali affirms.[4]
Be sure to check out Part 3 of this series, where we’ll continue our deep-dive into the top concerns for fraud and cybersecurity teams and the areas that will impact fraud management today, and in the coming years.
You can find Part 1 of this series here.
Explore this topic and more in our white paper Fighting Fraud During Extraordinary Times
[1] Ian Mitchell, Global Fraud and Financial Crime Executive. “Actionable Insights into Fraud Data.” Engage Live, Session 3.
[2] Naureen Ali, Senior VP Fraud, Deposits & Payments, Penfed Credit Union. “Advanced AI in Fraud Fighting.” Engage Live, Session 2.
[3] Ian Mitchell, Global Fraud and Financial Crime Executive. “Actionable Insights into Fraud Data.” Engage Live, Session 3.
[4] Naureen Ali, Senior VP Fraud, Deposits & Payments, Penfed Credit Union. “Advanced AI in Fraud Fighting.” Engage Live, Session 2.
