Payment Risk Platform
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 combines the power of people, technology, and data with direct access to trained fraud analysts to inform your fraud-mitigation strategies.
How it works
The new tools and platforms the Payment Risk Platform (PRP) provides make it easy to configure risk rules that block fraudulent events in real time. With access to fraud intelligence derived from more than 100M unique spend patterns that pinpoint operational and transactional fraud risks on top of that, Galileo clients save an average of 35%* in fraud costs. PRP targets every corner of the payments ecosystem by combining Galileo consortium data for risk and fraud insights, a real-time decision rules engine, a case-management system that includes a knowledge graph for manual review, backtesting capability, support for multiple product types (debit card, credit card, BNPL, customer onboarding, Money Movement, and more), and an optional GUI self-service environment.
*Based on a review of Galileo clients using Galileo fraud mitigation services - conducted in July 2022 and November 2022
What this means to your customers
Efforts can be made to improve the fraud dispute process and strengthen account take-over controls. Additionally, utilizing the resources and protection provided by a consortium such as Galileo may also aid in detecting and preventing fraudulent transactions. This can help increase customer confidence in the ability to detect and protect against fraud.
What this means to you
PRP will include a premium real-time risk decision engine, custom risk feature configurations, artificial intelligence/machine learning model risk scores, a case-management system with UI, and more. Fraud-strategy calibration is streamlined through a centralized system for monitoring, with regular consultation sessions with fraud-strategy Galileo’s Risk Ops Team. Access your self-service dashboard to view fraud insights and make changes to your fraud policy based on real-time risk scoring, or consult with the Galileo Risk Ops Team to manage your fraud rules.
Price varies by the volume of traffic generated by the product.
- Risk decision rules engine with optional self-service UI Access
- Easy risk feature configuration from simple data transformations to complex velocity features setups
- Back-testing capabilities before pushing the rule into production, using the historical data and/or a mock-up data
- Modifying, removing, or adding a fraud rule does not require any engineering configuration changes. Every change can be initiated and completed by the user
- No integration, no infra changes, no resource to maintain transaction decision rules engine
- Optional real-time artificial intelligence/machine learning transaction risk model scores
- Provides the riskiness level of an event in real-time, such as debit/credit card transactions, card applications, money movement transactions, and more.
- Continuous artificial intelligence/machine learning model retraining once a quarter
- No integration, no infra changes, no resource for maintenance
- Access to optional case management system with knowledge graph
- Easy changes in manual review queue on the UI
- Flexible access controls
- Quick fraud ring investigations using knowledge graph visualization
- Real-time fraud rule performance monitoring
- No integration, no infra changes, no resource for maintenance
- Fraud protection leveraged by Galileo consortium data
- Galileo consortium artificial intelligence/machine learning model to provide insights into fraud patterns identified by other Galileo clients
- Sharing merchant insights from across the consortium's spend patterns to identify compromised merchants
- Negative database (global black/graylist) from Galileo consortium data
- Proactive fraud detection algorithms such as common point of compromise (CPC)
- Flexibility to support multiple product types, including debit card transactions, credit card transactions, card applications, BNPL transactions, money movement (ACH transaction), mobile wallet provisioning events
- Pick and choose desired product types to receive Galileo’s risk assessment
What you provide
Reach out to your relationship manager (RM) or technical project manager (TPM) and inform them that you want to sign up for PRP. If you want to use a third-party risk vendor as part of your fraud policy, ask your RM or TPM to assess the vendor to provide their risk assessment within PRP.
What Galileo provides
Your RM or TPM will set up a series of regular fraud-strategy consultation sessions with the Galileo Risk Ops Team and test PRP in the CV environment on your behalf, prior to deployment. After the product overview call and PRP is enabled on your system, your fraud controls are active right away.
PRP service options
- Galileo consortium fraud insight data
- Global fraud features and fraud rules
- Galileo-managed fraud rule backtesting
- Real-time fraud decision engine
- Global artificial intelligence/machine transaction risk scores and global velocity features
- Risk/fraud dashboard and fraud pattern analysis managed by Galileo
- Additional proactive fraud detection algorithms
- Galileo proprietary artificial intelligence/machine transaction risk score
All basic services plus the following additional capabilities:
- Access to risk/fraud dashboard with pre-reserved seats
- Self-service fraud feature creation and fraud rule modification
- Self-service fraud rule backtesting
- Custom artificial intelligence/machine transaction risk scores and custom velocity features
- Case management system
- Knowledge Graph for Case Management System
- Additional seats available for purchase
These use cases provide examples of how each PRP feature 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
This model detects abnormal transaction behaviors. When a transaction is flagged as suspicious, you can decline the transaction and/or freeze the account in real-time, preventing the potential fraudster from accessing the account and protecting your customers' funds.
Additionally, you can detect suspicious patterns in transaction volumes and take action to prevent fraud with a velocity feature tailored to your specific use cases.
Use case 2: Detect potentially compromised merchants
Help protect your program from automated fraud attacks and BIN attacks. Rapid spend patterns are detected in real-time and transactions with compromised merchants are blocked. Each rapid transaction is given a risk score, which you can use to improve your fraud rules.
Common-point-of-compromise gives you visibility into which merchants are likely to be compromised for fraud investigations and a list of all active accounts that have ever touched these risky merchants.
Use case 3: Use data points to queue risky transactions
Log into the PRP user interface (UI) to configure the logic for queuing and reviewing risky transactions. While optional, this UI allows you to monitor the volume of risky transactions and determine the appropriate post-transaction decision actions, such as adding the card holder to the black/gray/whitelist. By reviewing all of the available data points within PRP, including the risk score, merchant velocity features, and account velocity features, you can make informed decisions about which transactions to queue and how to handle them.
Use case 4: Get performance data for fraud policies
To determine the effectiveness of your fraud policies, you can access your Risk Dashboard, the Snowflake querying console, or create an RDF to send you fraud master data that is customized to your needs. Meet with Galileo’s Risk Ops Team on a regular basis to consult on your fraud strategy. Get insight on your fraud events and patterns, recommendations on appropriate risk features or fraud policy changes.
Artificial intelligence/machine learning models are re-trained by the Risk Ops Team to provide continuing insights on recent changes in fraud patterns. Aggregated trend patterns across the Galileo platform are shared.
Updated 3 months ago