The Reveal Platform
This form of illicit activity entails the concealment of the source and origins of illegally acquired funds, usually conducted through money transfers with foreign banks or legitimate businesses.
Gurucul Fraud Analytics provides a comprehensive and robust platform for detection and prevention of cyber frauds involving cross-channel anomalous activities and patterns.
The Platform Provides:
“With the range of different and disparate channels of funds transfer such as online and debit channels, it is extremely critical to look at cross-channel fraud patterns to detect and prevent frauds.”
Such early detection of any change in the behavior due to risky transactions or patterns, enable organizations to investigate and respond to such fraudulent activities before any significant brand damage or financial loss.
Threat actors ceaselessly pursue methods to breach, phish and trick their way into getting a customer’s usernames and passwords.
Stopping malicious actors before a breach requires advanced security analytics capabilities including:
Gurucul provides 4000+ out-of-the-box threat, fraud and behavior models to enable organizations to detect any customer account compromise attacks. It also provides resident and real-time risk scores based on historic and current behavior respectively. Organizations can leverage the risk scores generated by the platform to enforce risk-based access control such as elevating the authentication level by enforcing out-of-band authentication for high risk user as oppose to simple id/password based authentication for low risk user.
One challenge of managing transaction fraud is having the visibility into all stages and elements of a given transaction across disparate and disconnected systems.
Gurucul’s fraud analytics solution can flag any process related control failures due to inconsistent / abnormal transactions across disconnected processes or systems such as core banking and SWIFT. This enables banks to potentially prevent and block significant financial frauds.
Gurucul Miner, a natural language-based search engine, provides a simple but powerful tool to analysts/auditors to gain 360° identity-centric visibility across all systems. It also pivots on any of the data elements such as account number, type of transactions, amounts and so on for any further investigation or periodic risk assessment.
Multiple channels for interaction with retailers and e-commerce continues to increase, creating new opportunities for threat actors. This growth of channels as well as increasing customer and transactions volume, presents a heightened risk of credit card payment fraud going undetected under massive number of alerts generated by typical rule-based fraud analytics solutions. These challenges require accurate detection of anomalies, risk-based alerting and response automation capabilities.
“The only UEBA solution to be recognized by Gartner for Fraud Analytics in the 2018 Online Fraud Detection Guide.”
– Saryu Nayyar
– CEO, Gurucul
Gurucul offers an advanced fraud analytics solution which uses a combination of supervised and unsupervised algorithms to detect any outlier risky behavior such as:
Banking environments vary and complicate the ability to address the variety of fraud problems that might imperil the specific payment types an institution might offer.
A comprehensive payment fraud security solution should address a broad variety of payment types such as:
Gurucul Fraud Analytics solution links transactions from various stages of the entire payment lifecycle providing a comprehensive and contextual view into all activities. Gurucul STUDIO enables customers to tune OOTB fraud models to look for any deviation with respect to specific transaction attributes or values. It also allows customers to create their own fraud models by simply leveraging OOTB model templates.
A growing tactic of mobile fraud is SIM-swap fraud where malicious actors get a new SIM card issued for a registered mobile number of a legitimate customer at a financial institution. The legitimate users’ SIM card is deactivated. The criminal actors then authenticate themselves to carry out transactions with the legitimate users’ bank account, initiating money transfers, withdrawals, and purchases.
Gurucul provides a robust security and fraud analytics platform which leverages advanced machine learning algorithms, to detect any mobile fraud cases including:
An organization’s insiders, especially those with privileged access to sensitive systems / data, pose a serious risk to financial organizations. Gurucul’s advanced security analytics solution analyzes and creates user baselines based on various data elements such as identity profile data, system entitlements and activities performed by users.
It looks at activities from disparate data sources including:
In case of any deviation from the normal baseline behavior such as suspicious loan applications submission or approvals, transaction overwrites, emails to competitor domains or self-personal emails, unusual physical access to sensitive areas, etc. an alert is generated with appropriate risk score.
Based on the risk score, data criticality, resource and transaction risk levels, the system provides automated response workflow to ensure rapid action and risk remediation.
A form of insider fraud, Customer Service Representative fraud consists of insiders in customer service who have privileged access to a wide range of customer accounts, performing fraudulent activities which impact an organization’s brand reputation or cause financial loss.
The Gurucul Fraud Analytics flexible data integration framework allows ingestion of data from a wide range of sources including ticketing systems, VoIP phone data, badge access data, workstation events and network events which are linked to the user identity. This allows detection of CSR fraud scenarios including abnormal data transfer and unusual pattern of activities, such as customer profile changes without corresponding ticketing or service request, malicious in-bound or out-bound phone activity, session time, etc.
Gurucul’s Next-Gen SIEM leverages AI-driven data pipeline management to normalize, enrich, and analyze third party telemetry—reducing risk while increasing insight.
