Navigate new fraud threats and security challenges around the globe and quickly pivot your approach to protecting your business.
Our fast-learning, predictive risk algorithms ingest the data from billions of annual transactions to identify patterns and help mitigate risk.
Dynamic routing, retries, and granular data analysis ensure that legitimate transactions are approved at a higher rate and more often on the first try.1
Adapt to evolving fraud patterns without causing friction at checkout or increasing the risk of false declines.
Utilize our data security experts help businesses apply successful compliance and security strategies.
A secure vault and data sharing tools offer a sophisticated and streamlined way to build and maintain your payments system.
Easily and securely connect your payment infrastructure to third-party and security-services partners.
Lean on our powerful set of customizable solutions that use machine learning, automated decisioning, and decades of data-driven insights to help prevent fraud and reduce risk.
Movie-going is an interesting business where we have these moments of huge volume. To be able to handle this kind of scale is critical, and our integration has been great.
SVP, Chief Product Officer
Harness the power of billions of annual transactions on our network to help you spot risks before they happen so you can provide a safer experience for you and your customers.
Built on a foundation of operating at scale in over 200 markets, our network is comprised of over 400 million active users and more than 30 million merchants.
From people to platform, see how Kiva can manage risk, navigate operations, and accelerate growth without missing a step.Read the case study
From an evolving security landscape to mobile shopping, payments today are much different than they were just a few short years ago.Get the white paper
The coronavirus could be bringing more than loyal customers to your website—it may also be attracting fraud. Your payments platform must be able to scale and adapt.Read the article
1 PayPal Internal Data. June 2019. Methodology: Benchmarked against MasterCard auth data set for the month of June 2019. There is no de-duplication for any of the numbers (removing duplicates will give us higher auth rates in the range of 95%+)