Rapyd Protect: Machine Learning That Works For You
Rapyd Protect uses AI modeling, unique data sources, and our proprietary rules engine to identify high-risk transactions across bank transfers, cards, and ewallets. Rapyd Protect requires no additional coding or integration and is already built into our platforms and network. Why Use Rapyd Protect? Rapyd Protect helps to identify fraud and help to prevent future instances of fraud by flagging bad actors that engage in high-risk transactions. Machine learning is used to analyze transaction data and identify anomalous patterns that may indicate illicit financial activity. Rapyd Protect Features There are a variety of helpful features for Rapyd Protect. The major features are summarized below: Machine Learning - Benefit from Rapyd’s best in class models informed by unique data sets fine tuned to identify new fraud trends and keep your business safe. Rule Building Engine - User friendly drag and drop rule builder for additional protection from fraudulent transactions. Users can create rules based on IP addresses, card types, countries, activate 3D Secure, and more. Manual Reviews - Set up manual reviews for high risk transactions such as large purchases, specific countries, or for special orders. Velocity Engine - Prevent fraudulent transactions by monitoring purchase frequency and usage patterns for numerous payment methods. Lists - Access Rapyd’s rich data set listing known fraudsters, dubious IP addresses, blocked countries, high risk bin numbers and ranges. Reports - Create comprehensive transaction reports, plus access an extensive management system for alerts, rules and reviews. Fraud Rules Fraud Rules are conditions that can be manually created that set parameters for machine learning. It allows transactions to be flagged if a certain rule is triggered – when the conditions outlined in the rules are met. One example of a fraud rule might be: flag transactions where the number of transactions is greater than or equal to 50 transactions over a 24 hour period. This fraud rule is helping to identify excessive transaction volume. A high transaction volume over a short period of time can be an indicator of fraudulent activity. Transactions can be simulated using Rapyd Protect. This would allow you to create scenarios, and stress test the fraud rules that you create. This can empower the user to refine their fraud rules to meet their business’s specific financial needs. Transaction Review When a transaction violates a specific fraud rule, the transaction is “quarantined” and placed under review. The user can then manually review the transaction. The transaction can then either be accepted, declined, or blocked. A transaction that triggers a fraud rule may still be manually approved if the transaction is an edge case for the rule, or has specific mitigating circumstances. Transactions can be blocked if the fraud rule is set to block them. A blocked transaction will not go through. A fraud rule can be set to block the transactions when triggered. Blocked transactions can also be reviewed manually. In addition, transactions can be reviewed in manually generated reports, which can provide a concise format to summarize key financial data. Rapyd Protect Benefits Rapyd Protect has many benefits to offer, including: increased accuracy for fraud detection, automated transaction monitoring, adjustable parameters controlled by the user, and the ability to quickly identify red-flag transactions across large amounts of transaction data. Using Machine Learning to protect yourself against fraud can be a game changer. It shifts the burden away from human staff, and can allow a greater degree of freedom over one’s finances and their financial safety. Rapyd Protect can be accessed via the Client Portal, Rapyd’s no-code solution designed to meet your financial needs. Sign up for the Client Portal and try experimenting with Rapyd Protect to use the best in fraud detection.
Rapyd Protect uses AI modeling, unique data sources, and our proprietary rules engine to identify high-risk transactions across bank transfers, cards, and ewallets. Rapyd Protect requires no additional coding or integration and is already built into our platforms and network.
Why Use Rapyd Protect?
Rapyd Protect helps to identify fraud and help to prevent future instances of fraud by flagging bad actors that engage in high-risk transactions. Machine learning is used to analyze transaction data and identify anomalous patterns that may indicate illicit financial activity.
Rapyd Protect Features
There are a variety of helpful features for Rapyd Protect. The major features are summarized below:
Machine Learning - Benefit from Rapyd’s best in class models informed by unique data sets fine tuned to identify new fraud trends and keep your business safe.
Rule Building Engine - User friendly drag and drop rule builder for additional protection from fraudulent transactions. Users can create rules based on IP addresses, card types, countries, activate 3D Secure, and more.
Manual Reviews - Set up manual reviews for high risk transactions such as large purchases, specific countries, or for special orders.
Velocity Engine - Prevent fraudulent transactions by monitoring purchase frequency and usage patterns for numerous payment methods.
Lists - Access Rapyd’s rich data set listing known fraudsters, dubious IP addresses, blocked countries, high risk bin numbers and ranges.
Reports - Create comprehensive transaction reports, plus access an extensive management system for alerts, rules and reviews.
Fraud Rules
Fraud Rules are conditions that can be manually created that set parameters for machine learning. It allows transactions to be flagged if a certain rule is triggered – when the conditions outlined in the rules are met.
One example of a fraud rule might be: flag transactions where the number of transactions is greater than or equal to 50 transactions over a 24 hour period. This fraud rule is helping to identify excessive transaction volume. A high transaction volume over a short period of time can be an indicator of fraudulent activity.
Transactions can be simulated using Rapyd Protect. This would allow you to create scenarios, and stress test the fraud rules that you create. This can empower the user to refine their fraud rules to meet their business’s specific financial needs.
Transaction Review
When a transaction violates a specific fraud rule, the transaction is “quarantined” and placed under review. The user can then manually review the transaction. The transaction can then either be accepted, declined, or blocked.
A transaction that triggers a fraud rule may still be manually approved if the transaction is an edge case for the rule, or has specific mitigating circumstances.
Transactions can be blocked if the fraud rule is set to block them. A blocked transaction will not go through. A fraud rule can be set to block the transactions when triggered. Blocked transactions can also be reviewed manually.
In addition, transactions can be reviewed in manually generated reports, which can provide a concise format to summarize key financial data.
Rapyd Protect Benefits
Rapyd Protect has many benefits to offer, including: increased accuracy for fraud detection, automated transaction monitoring, adjustable parameters controlled by the user, and the ability to quickly identify red-flag transactions across large amounts of transaction data.
Using Machine Learning to protect yourself against fraud can be a game changer. It shifts the burden away from human staff, and can allow a greater degree of freedom over one’s finances and their financial safety.
Rapyd Protect can be accessed via the Client Portal, Rapyd’s no-code solution designed to meet your financial needs.
Sign up for the Client Portal and try experimenting with Rapyd Protect to use the best in fraud detection.
