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What is Corgi Labs?

Corgi Labs is an AI-powered platform designed to help businesses optimise payment processing and detect fraudulent transactions. It analyses payment data in real-time to identify patterns that indicate fraud or problems affecting transaction success rates. The tool combines fraud detection with payment analytics, helping companies increase revenue by reducing false declines (legitimate transactions wrongly rejected) while simultaneously blocking actual fraudulent activity. It's built for e-commerce businesses, digital banks, gaming platforms, and other companies processing high volumes of online payments. Rather than using a one-size-fits-all approach, Corgi Labs lets you customise fraud detection rules to match your business needs and risk tolerance.

Key Features

Payment analytics

Detailed dashboards showing transaction data, decline rates, and performance metrics across payment channels

AI-driven fraud detection

Machine learning models that identify suspicious patterns and flag high-risk transactions

Customisable rules engine

Set your own fraud prevention rules rather than relying entirely on automated decisions

Integration with payment providers

Connects with major payment gateways and processors to analyse data across your systems

Real-time transaction monitoring

Immediate analysis of incoming payments to catch problems as they occur

Pros & Cons

Advantages

  • Addresses both sides of the problem: reduces fraud losses and recovers revenue lost to false declines
  • Flexible fraud rules let you balance security with customer experience rather than accepting fixed thresholds
  • Works across multiple payment channels and providers through integrations
  • Freemium model means you can test the platform before committing budget

Limitations

  • Effectiveness depends on data quality; businesses with limited transaction history may see less accurate fraud detection initially
  • Customising rules requires some payment operations expertise to avoid creating either too lenient or overly strict policies
  • Pricing details for paid tiers are not publicly listed, requiring direct contact for quotes

Use Cases

E-commerce retailers reducing fraudulent chargebacks whilst maintaining fast checkout experiences

Gaming platforms detecting account takeovers and fraudulent spending patterns

Digital banks and fintech companies monitoring payment behaviour across customer bases

Subscription services identifying fraud in recurring billing whilst minimising legitimate customer rejections

High-volume merchants analysing payment trends to optimise acceptance rates by geography or customer segment