Fynspot launches AI-powered fraud detection platform to help businesses reduce fraud without sacrificing customer experience
Cyprus-based cybersecurity company COWIN has unveiled Fynspot, a next-generation AI-powered fraud detection platform designed to help businesses identify fraudulent transactions while reducing the number of legitimate payments that are incorrectly declined.
The new API-first Software-as-a-Service (SaaS) platform combines machine learning, behavioural analytics and explainable artificial intelligence (AI) to deliver real-time transaction risk assessments within milliseconds, enabling organisations to strengthen fraud prevention without adding friction to the customer experience.
Addressing the limitations of traditional fraud prevention
As online fraud becomes increasingly sophisticated, many organisations continue to rely on static rule-based fraud detection systems that often struggle to distinguish genuine customers from fraudulent actors. These legacy approaches can lead to high levels of false positives, resulting in lost sales, frustrated customers and reduced revenue.
Fynspot has been developed to overcome these challenges by replacing fixed rules with adaptive AI models capable of analysing hundreds of risk signals simultaneously. Rather than relying on predefined conditions, the platform evaluates the complete behavioural context behind every transaction before assigning a dynamic risk score.
According to the company, this enables businesses to block more fraudulent activity while approving more legitimate transactions.
“Fraud prevention should not come at the expense of customer experience or revenue growth,” said Pavlos Karasamanis, Product Lead at Fynspot.
“Many businesses are unknowingly losing legitimate customers because traditional systems are forced to make broad decisions based on static rules. Fynspot introduces a more intelligent approach that understands context, adapts continuously, and delivers transparency into every decision.”
Fast deployment through API-first integration
Designed as a fully external SaaS platform, Fynspot integrates into existing payment infrastructures via a lightweight RESTful API, eliminating the need for businesses to replace existing systems or undertake extensive implementation projects.
Risk assessments are generated in milliseconds, allowing organisations to evaluate transactions in real time without slowing the checkout process.
This rapid deployment model enables businesses to strengthen fraud controls while maintaining a seamless customer experience.
Behavioural intelligence beyond device fingerprinting
Unlike many fraud prevention solutions that rely heavily on browser fingerprinting and client-side tracking technologies, Fynspot places greater emphasis on backend behavioural intelligence.
The platform analyses multiple transaction attributes, including transaction velocity, historical customer behaviour, BIN intelligence, card verification data, geographical inconsistencies, IP reputation, VPN and proxy usage, email authenticity indicators and bot detection signals.
By combining these data points, Fynspot builds a comprehensive behavioural profile for every transaction, allowing businesses to identify genuine threats with greater accuracy while reducing unnecessary payment declines.
Explainable AI improves decision transparency
A key feature of the platform is its use of Explainable AI (XAI), designed to address concerns around the transparency of machine learning models.
Using SHAP (Shapley Additive Explanations), Fynspot identifies the factors that contributed most significantly to each transaction’s risk score and presents them in clear, human-readable language.
This allows fraud analysts and risk teams to understand precisely why a transaction has been flagged, supporting more informed decision-making.
“Trust in AI comes from transparency,” said Fedros Avraam, Chief Technology Officer at COWIN.
“Our customers don’t just receive a score. They receive clear insight into the drivers behind every decision, empowering risk teams to make informed judgments with confidence.”
Continuous learning against emerging threats
Recognising that fraud tactics constantly evolve, Fynspot incorporates automated model retraining that continually learns from new transaction data and analyst feedback.
False positives and false negatives identified during day-to-day operations are fed back into the machine learning models, allowing detection accuracy to improve over time without requiring manual rule updates.
According to the company, this adaptive approach enables organisations to remain resilient against emerging fraud techniques while reducing ongoing maintenance requirements.
Human expertise remains central
While AI forms the foundation of the platform, Fynspot is designed to complement rather than replace human fraud teams.
Its integrated risk management dashboard includes transaction firewalls, blacklist and whitelist management, and manual review workflows for borderline cases, enabling organisations to combine AI-driven automation with human expertise.
This hybrid approach aims to provide businesses with greater flexibility when managing complex fraud scenarios.
Available now
Fynspot is available immediately for organisations seeking scalable AI-powered fraud detection through a SaaS deployment model.
Developed by COWIN, the platform forms part of the company’s broader cybersecurity portfolio, which includes penetration testing, cyber risk management, regulatory compliance and security consulting services.
Fynspot is intended to help businesses improve fraud prevention, increase transaction approval rates and protect revenue while maintaining customer trust in an increasingly complex digital payments landscape.
