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From Data to Defense: The Case for Data Orchestration in the Fight Against Financial Fraud
Home > Finance > From Data to Defense: The Case for Data Orchestration in the Fight Against Financial Fraud
Global Banking and Finance Review
Company
By Fang Yu, CPO and Co-Founder, DataVisor
Today’s fraudsters are sophisticated and determined. Their sole job is to relentlessly look for opportunities to exploit vulnerabilities in the fraud defenses of financial institutions (FIs). When FI fraud strategies fail to effectively leverage customer lifecycle data, they are doomed to be reactionary at best – only catching fraud after it takes place. To fight financial crime, FIs can and must work smarter, not harder. There’s a wealth of data at their fingertips, from customer IP addresses, to digital footprints, and customer behaviors across the various products within their offerings. If you’re not squeezing all of the “juice,” a.k.a intelligence, from your existing data, you are missing out on the low-hanging fruit that could be saving you valuable time, money, and resources on your fraud strategy in the long run.
The Problem: Fragmented Data
It’s not uncommon for FIs to organize their customer data in silos – not by choice, but out of circumstance. As an institution broadens its services and adopts digital banking solutions, it may need to implement various fraud prevention solutions to tackle different types of fraudulent activities. For example, a bank that adopts real-time payments (RTP) may at the same time adopt a fraud solution that is specifically designed to detect RTP fraud. That FI is also still working with another fraud solution, or even multiple solutions, to address fraud concerns across other offerings – from everyday banking to loans and investments. Without centralized intelligence across solutions, FIs leave themselves wide open to bad actors who can slip through the cracks.
While analyzing data in silos leads to fragmentation, so do linear approaches to data, or analyzing data in a sequential, one-dimensional manner. This approach prevents FIs from observing interactions between data points at different stages of the customer journey across various products, making it nearly impossible to detect sophisticated fraud schemes. As an example, envision a situation where an individual contacts the service desk to request a change in their phone number. Following this change, there’s a large money transfer to a new receiver. Viewed in isolation, each event in this customer journey might not trigger suspicions. However, when these actions are considered together, a red flag is raised.
When data is analyzed separately, anomalies or suspicious patterns may not be immediately apparent. In fact, fraudsters’ malicious behaviors can often go unnoticed when examined in isolation because many traditional fraud solutions lack the ability to correlate events across different channels.
Optimizing Fraud Defenses with a Modern Approach to Data
Modern-day fraudsters have access to the most up-to-date technology that makes it easier than ever to exploit the gaps in today’s FI fraud strategies. This is why creating a centralized intelligence hub is key to any modern-day fraud strategy. By integrating various data sources and efficiently managing the analysis and processing of this information throughout the account lifecycle, business units and channels, it’s possible to achieve a comprehensive understanding of customer behavior. This holistic approach significantly enhances the ability to detect and prevent fraudulent activities.
Consider a sophisticated fraud ring conducting large-scale coordinated attacks, involving account takeover (ATO) and mass registration. The patterns of such a ring could include the use of different IPs and device IDs, IP addresses traced back to VPNs or data centers, the consistent employment of certain payment instruments, and the recurrence of specific payee account numbers, among other signs.
Viewed individually, these subtle signals might not immediately raise concerns. However, the true strength of data orchestration lies in its capacity to weave these scattered indicators of different accounts together, constructing a detailed picture of the fraud operation. The more data at hand, the clearer the patterns become, facilitating the detection and linkage of multiple accounts involved in the ring. Data orchestration is pivotal in aggregating this vast array of information, enabling organizations to harness it in real time to uncover and dismantle the sophisticated networks of fraud.
The Strategic Integration of Third-Party Signals
Effective data orchestration transcends the mere consolidation of internal data, extending its reach to integrate third-party signals directly into the centralized intelligence hub. This integration is pivotal for FIs looking to enhance their fraud detection capabilities without multiplying their operational complexities or costs. By streamlining integrations and consolidating vendors, organizations effectively reduce the total cost of ownership, offering a more economical approach to fraud prevention.
Crucially, it gives organizations more control and the ability to discern when and which third-party signals are necessary, avoiding superfluous data calls that can inflate costs and complicate analyses. This use of third-party data ensures that FIs are not just collecting data for the sake of it. Strategically employing these external signals not only bolsters fraud defenses where and when it matters most but also minimizes unnecessary interventions, thereby preserving a seamless and positive experience for legitimate users.
The Real-Time Advantage
To meet the relentless demand for immediacy in today’s digitalized world, FIs are required to analyze vast volumes of data quickly and make precise decisions within milliseconds. The stakes are high, as errors in real-time transactions can incur substantial and irreversible costs. Real-time data transformation is a key advantage of a powerful data orchestration layer – giving FIs the ability to set their fraud strategy apart. It empowers institutions to respond immediately to emerging threats, offering a proactive defense that isn’t achievable with traditional batch processing.
A compelling case for data orchestration in modern-day fraud strategies is underscored by its ability to seamlessly ingest data from any source – whether internal or external, effectively integrating internal and third-party data, and providing real-time data transformation. As FIs leverage data orchestration to build a centralized intelligence hub, they not only strengthen their defenses against fraud but also pave the way for enduring customer trust, loyalty, and adaptability in an ever-evolving digital landscape.
Data orchestration refers to the automated process of integrating and managing data from various sources to provide a unified view, enhancing analysis and decision-making.
Financial fraud involves deceptive practices aimed at securing an unfair or unlawful financial gain, often targeting individuals or institutions.
Real-time data analysis is the immediate processing and evaluation of data as it becomes available, allowing organizations to respond quickly to emerging threats.
Fraud defenses are strategies and technologies implemented by organizations to prevent, detect, and respond to fraudulent activities.
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