Payment Risk Platform

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Availability

The information in this document is subject to change as development proceeds and is not a guarantee of future functionality.

Galileo’s multi-layered approach to fraud mitigation expertly combines the power of people, technology, and data, with direct access to Galileo’s trained fraud analysts for comprehensive fraud-mitigation strategies. The Payment Risk Platform (PRP) enables you to configure risk rules to block fraudulent events in real time and address complex fraud challenges. For instance, PRP effectively identifies and mitigates risks from potentially compromised merchants and abnormal transaction behaviors, showcasing its adaptability in dynamic fraud landscapes. By harnessing fraud intelligence derived from the spend patterns within the Galileo ecosystem, PRP adeptly pinpoints both operational and transactional fraud risks, thus enabling you to save an average of 35%* in fraud costs. PRP targets every corner of the payments ecosystem by utilizing Galileo consortium data for in-depth risk and fraud insights, a real-time decision rules engine, and backtesting capability. PRP support extends across multiple Galileo products including debit and credit cards to Buy Now Pay Later (BNPL), customer onboarding, and money movement. Moreover, PRP's optional self-service environment, coupled with a case-management system that includes a knowledge graph for manual review, offers a comprehensive, user-friendly solution for fraud mitigation.

_{*Based on a review of Galileo clients using Galileo fraud mitigation services - conducted in July 2022 and November 2022}

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Note

PRP regularly receives and analyzes post-transaction data, including fraud and disputes. Detailed information on how this data refines fraud rule performance and policies is outlined below.

Integrated PRP Solutions

Fraud dashboard

• Utilize data insights from the Galileo consortium to identify and mitigate fraud risks.
• Access advanced analytics for monitoring fraud patterns and assessing risk, backed by Galileo’s expertise.

Risk decision rules engine

• A real-time fraud decision engine to block fraudulent events as they occur.
• Optional user-friendly UI for easy risk feature configuration, including velocity features setups, with no need for engineering changes.
• Test fraud rules using historical or mock-up data before implementation.

Artificial intelligence and machine learning applications

• Global AI/ML models for real-time transaction risk scoring.
• Regularly re-trained AI/ML models based on the latest fraud patterns and consortium insights.

Fraud rule management and optimization

• Ensuring the efficacy of fraud rules through rigorous backtesting.
• Streamlined processes for modifying, removing, or adding fraud rules without infrastructural changes.

Proactive fraud detection

• Includes proactive algorithms like the Common Point of Compromise (CPC) feature.
• Leverage a global black/graylist from consortium data for enhanced security measures.
• Leverage insights from over 100 million spend patterns to quickly identify potentially compromised merchants.

Integration and maintenance efficiency

• Work with Galileo to integrate PRP with your existing systems, requiring minimal infrastructural changes and resource maintenance.

Post-transaction analysis and strategy

• Galileo performs regular assessment of fraud rule performance and calibration of fraud policy based on systematic post-transaction data.

Use cases

These use cases provide examples of how different PRP features can benefit a fraud manager of a fintech company who is responsible for monitoring fraud patterns, performing fraud investigations, and making changes in the fraud policy to systematically block risky transactions.

Use case 1: Detect abnormal transaction behaviors

A financial institution utilizes PRP to safeguard their customer’s accounts by continuously monitoring transactions. On a typical business day, transactions are received and processed without any issues. However, at 2:30 PM, the system registers a significant and sudden spike in transaction volumes, particularly for electronic check (e-check) payments.

PRP’s velocity feature immediately identifies this unusual pattern and raises an alert with a list of the affected accounts, as well as the transaction details, count, and velocity, and the recommended action to take. The alert data indicates that the spike involved a high number of e-check payments, which is unusual for this time of day. Additionally, none of the transactions appear to have typical authorization codes or descriptions, but the transaction amounts are consistent with normal transactions, making it less likely to be a simple error. Based on the evidence, the security team immediately decides to temporarily freeze all accounts involved, then contact the affected customers to verify which of the transactions were legitimate and which were fraudulent. From there, they can take the appropriate actions, including refunding affected customers and pursuing legal actions against the fraudsters.

Use case 2: Detect potentially compromised merchants

A retail banking organization relies on PRP to identify and mitigate risks associated with potentially compromised merchants. On a busy shopping weekend, PRP observes an unusual surge in credit card transactions at a particular electronics store across different states. This rapid pattern of high-value purchases triggers an alert within the system.

PRP’s advanced algorithms analyze these transactions and assign a risk score to each, factoring in the velocity of transactions and historical data on typical purchasing behaviors. PRP also employs the CPC feature to identify and analyze the electronics stores as potential points of compromise. This information can then be used to quickly isolate these transactions and block further purchases from the identified merchants, as well as generate a report that lists all active accounts that have interacted with these merchants to conduct a focused investigation. From there, the bank can reach out to the affected cardholders to confirm their transactions, helping to differentiate between legitimate purchases and fraudulent activities. Through these swift actions, the retail banking organization not only prevents further fraudulent transactions but also aids in broader fraud investigations, ultimately safeguarding both their assets and their customers’ financial security.

Use case 3: Use data points to queue risky transactions

A multinational e-commerce company integrates PRP to enhance their transaction monitoring capabilities. Despite having a robust online transaction system, the company faces challenges in identifying and managing high-risk transactions, especially during peak shopping seasons. To address this, the company's fraud prevention team decides to leverage PRP's user interface (UI) to set up a more nuanced approach for handling risky transactions.

Utilizing the PRP UI, the team configures a series of parameters to queue transactions that exhibit suspicious characteristics. For instance, during a major sale event, PRP detects an unusually high volume of transactions from newly created accounts, all purchasing high-value items. PRP’s risk scoring mechanism, combined with merchant and account velocity features, highlights these transactions as high-risk. The queued transactions are reviewed by the fraud prevention team, who scrutinize each transaction’s details, such as account creation date, transaction amount, and frequency of purchases. Based on this analysis, the fraud prevention team categorizes the transactions: legitimate transactions are processed, while suspicious transactions are added to a graylist for closer monitoring or a blacklist for immediate blocking. This proactive approach enables the e-commerce company to mitigate potential fraud while minimizing disruption to genuine customers, ensuring a secure and trustworthy shopping experience.

Use case 4: Get performance data for fraud policies

A leading online banking service utilizes PRP to continuously refine and enhance their fraud detection strategies.

The online banking service regularly accesses the Risk Dashboard within PRP, utilizing its sophisticated Snowflake querying console to analyze extensive fraud data. This enables their security team to generate customized raw data files (RDFs), which provide detailed insights into fraud incidents and patterns specific to their operation. Additionally, the bank schedules routine consultations with Galileo to discuss and refine their fraud strategy based on these insights. During these meetings, the team reviews the performance of existing fraud policies, gaining valuable recommendations on optimizing risk features and policy adjustments. The AI/ML models employed are continuously re-trained with the latest data, ensuring that the banking service stays ahead of recent changes in fraud patterns. Furthermore, the benefits from aggregated trend analyses shared across the Galileo platform, enabling them to benchmark their performance and strategies against industry standards. This comprehensive approach not only bolsters their ability to combat fraud but also enhances the security and trust of their customers in their digital banking services.

Galileo setup

Reach out to Galileo to inquire about setup and initiate fraud-strategy consultation sessions with the Galileo Risk Ops Team. Prior to deployment, you work with Galileo to test PRP in the CV environment on your behalf.

If you want to use a third-party risk vendor as part of your fraud policy, ask your Galileo representative to assess the vendor to provide their risk assessment within PRP.