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Checkout.com Uses AI To Boost eCommerce Acceptance Rates
Intelligent Acceptance leverages the company’s global data network to increase acceptance rates, lower fees, and improve merchant’s profits.
Global payments solution provider, Checkout.com, has launched a new feature called Intelligent Acceptance. The system uses an AI-powered optimization engine that can monitor billions of transactional data points, with early beta testing showing a 9.5% average improvement in checkout acceptance rates.
“We believe in abstracting complexity for businesses and empowering them to optimize their payments with ease. Machine learning enables us to […] leverage our expansive global transaction data to provide real-time insights. Meanwhile, an adaptive AI-powered payments engine constantly optimizes acceptance rates, unlocking more revenue, saving time, and offering greater cost controls,” says Meron Colbeci, Chief Product Officer at Checkout.com.
False declines — legitimate transactions mistaken for fraud attempts and subsequently blocked — are a $50.7 billion problem globally. Intelligent Acceptance can route card payments through the system much more smoothly, using continuous adaptation while leveraging Checkout.com’s global network and direct relationships with card acquirers to deliver incremental improvements.
Also Read: A Guide To Digital Payment Methods In The Middle East
Intelligent Acceptance can also drive down a merchant’s costs by dynamically routing transactions to the network with the lowest fees. Furthermore, if a transaction requires 3DS authentication, data can be automatically added to a payment request to ensure compliance.
The launch of Intelligent Acceptance comes as business leaders seek new ways to drive revenue and improve cost efficiencies to reconcile increased expenses. Research conducted by Checkout.com in partnership with Oxford Economics recently revealed that up to 25% of consumers abandoned an online purchase due to too much checkout friction, resulting in significant lost revenue for merchants.
News
ESET Bets On Specialized Security AI At 0.5% The Training Cost
ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.
A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.
To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.
Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.
NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.
ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.
Also Read: Dubai Says Its Deepfake Detector Needs Just 7 Seconds Of Video
“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.
As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.
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