Pattern Detection and Data Anaytics Play a Vital Role in Fraud Management

April 5, 2016 Sally Ewalt

Pattern detection

Most organizations are no stranger to the concept of data analytics and behavioral patterns to detect fraud. After all, those sorts have analytics have been applied to internal data and transaction monitoring systems for years. However, the ability to spot fraud patterns is often limited only to what can be detected within the organizations’ walls.

Fraud experts agree that detecting patterns with internal data alone is not sufficient. “In play” identities may be active in other organizations, and detecting patterns of potential fraud can stop compromised identities from spreading.

Technology for velocity and pattern detection is a powerful weapon in the fraud management arsenal. Simply put, velocity is the frequency that data attributes or relationships occur over a period of time. And, unusual spikes in frequency for various data elements or attributes can indicate suspicious patterns of activity. These anomalous applications can then be flagged and scored for fraud risk and sent for further investigation.

External velocity and behavioral pattern tools are critical to spot personally identifiable information that may be in play with fraudsters. In cases of synthetic identity fraud, for example, the tools provide an earlier warning of an identity with an anomalous volume of applications and inquiries. Tools like this can help prevent the kind of movement across victim organizations that fraudsters typically do to avoid detection.

When accessing these types of tools, look for something that avoids the following weaknesses:

  1. Insufficient volume of data: To realize the full promise of pattern recognition, massive data resources are critical. Few data providers have assets available to achieve the high capture rates demanded in this dynamic fraud environment.
  2. Stale data: Fraudsters move quickly because their assets, stolen identities for example, tend to degrade in value rapidly. Suspicious activity must be detected in a few hours or days of the occurrence, not weeks or months after the activity begins.
  3. Cumbersome tools for data analytics: Up to date  tools and the ability to quickly revise rules and models helps make sense of the information to stay ahead of fraudsters.

With access to millions of daily inquiries, Equifax is uniquely positioned to apply analytics, velocity detection and behavioral pattern detection to the problem of managing fraud losses with minimal damage to legitimate applicants. Leveraging our proprietary keying and matching technology, our solutions spot important anomalies in application and inquiry activity. Based on your rules, a suspicious application can be isolated and queued for additional review. Just as importantly, a greater population of legitimate applications can be passed through rapidly without the need for additional review, expense, and applicant fallout.

The post Pattern Detection and Data Anaytics Play a Vital Role in Fraud Management appeared first on Insights.

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