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The past, present, and future of AI, with Stripe

How machine learning fingers credit card fraud, how approaches have evolved over the years, and what is new in AI, with Stripe's Emily Sands.

How Stripe is using AI to create personalized checkout experiences

The Optimized Checkout Suite uses AI to personalize the checkout experience—dynamically adjusting everything from payment method ordering to fraud interventions in order to maximize conversion and boost revenue.

Using AI to create dynamic, risk-based Radar rules

Last month, we improved our AI tooling to give you even more flexibility when combating fraud. Now, Radar’s new rules combine our machine learning models with the issuer’s CVC and postal code response in real time.

AI enhancements to Adaptive Acceptance

Stripe’s AI-powered Adaptive Acceptance increases payment acceptance by recovering false declines. Recent AI upgrades improved transaction retry accuracy, leading to a record $6 billion recovered in 2024—a 60% year-over-year increase.

The past, present, and future of AI, with Stripe

How machine learning fingers credit card fraud, how approaches have evolved over the years, and what is new in AI, with Stripe's Emily Sands.

How Stripe is using AI to create personalized checkout experiences

The Optimized Checkout Suite uses AI to personalize the checkout experience—dynamically adjusting everything from payment method ordering to fraud interventions in order to maximize conversion and boost revenue.

Using AI to create dynamic, risk-based Radar rules

Last month, we improved our AI tooling to give you even more flexibility when combating fraud. Now, Radar’s new rules combine our machine learning models with the issuer’s CVC and postal code response in real time.

AI enhancements to Adaptive Acceptance

Stripe’s AI-powered Adaptive Acceptance increases payment acceptance by recovering false declines. Recent AI upgrades improved transaction retry accuracy, leading to a record $6 billion recovered in 2024—a 60% year-over-year increase.

The ML flywheel: How we continually improve our models to reduce card testing

Card testing is one of the most significant fraud threats to Stripe users and the broader financial ecosystem. Stripe’s machine learning–based approach has led to successful card testing attacks on Stripe decreasing by 80% over the last two years.

Using ML to detect and respond to performance degradations in slices of Stripe payments

With our slice monitoring program, we use machine learning to spot small pockets of performance declines amid the sea of global payments.

Using ML to comply with SCA requirements

By applying ML to the process of navigating SCA requirements, we’re helping users reduce checkout friction while lowering fraud and increasing authorization rates.

The past, present, and future of AI, with Stripe

How machine learning fingers credit card fraud, how approaches have evolved over the years, and what is new in AI, with Stripe's Emily Sands.

How Stripe is using AI to create personalized checkout experiences

The Optimized Checkout Suite uses AI to personalize the checkout experience—dynamically adjusting everything from payment method ordering to fraud interventions in order to maximize conversion and boost revenue.

Using AI to create dynamic, risk-based Radar rules

Last month, we improved our AI tooling to give you even more flexibility when combating fraud. Now, Radar’s new rules combine our machine learning models with the issuer’s CVC and postal code response in real time.

AI enhancements to Adaptive Acceptance

Stripe’s AI-powered Adaptive Acceptance increases payment acceptance by recovering false declines. Recent AI upgrades improved transaction retry accuracy, leading to a record $6 billion recovered in 2024—a 60% year-over-year increase.

The ML flywheel: How we continually improve our models to reduce card testing

Card testing is one of the most significant fraud threats to Stripe users and the broader financial ecosystem. Stripe’s machine learning–based approach has led to successful card testing attacks on Stripe decreasing by 80% over the last two years.

Using ML to detect and respond to performance degradations in slices of Stripe payments

With our slice monitoring program, we use machine learning to spot small pockets of performance declines amid the sea of global payments.

Using ML to comply with SCA requirements

By applying ML to the process of navigating SCA requirements, we’re helping users reduce checkout friction while lowering fraud and increasing authorization rates.

The past, present, and future of AI, with Stripe

How Stripe is using AI to create personalized checkout experiences

Using AI to create dynamic, risk-based Radar rules

AI enhancements to Adaptive Acceptance

The ML flywheel: How we continually improve our models to reduce card testing

Using ML to detect and respond to performance degradations in slices of Stripe payments

Using ML to comply with SCA requirements