Capgemini and Waylay have joined forces to present an innovative solution that blends the strengths of rule-based systems with the latest advancements in AI and ML, aimed at reducing operational costs related to fraud while simultaneously elevating customer experiences. Waylay's payment solution seamlessly operates across cloud, on-premise, and hybrid environments, fully leveraging the capabilities of modern cloud-native applications.
The Threat of Transaction Fraud and Its Impact
The risk of transaction fraud is more prevalent and sophisticated than ever before, causing significant financial losses and reputational damage with credit card losses predicted to hit $17 billion annually by 2030. Chief credit risk officers must develop better tactics to minimize fraud losses as payment fraud costs them 10% of their revenue whereas business users struggle to comply with regulations that take three to six months to update, leading to poor customer service and operational risk. This and more while fraudsters continue to exploit weaknesses and new tactics emerge regularly, leading to higher costs, lower trust, and legal risks.
Mitigating the Risks of Fraud in Transactions
Waylay's fraud monitoring solution uses a combination of rule based systems (that have been built and tested over the decades by finance experts), in combination with the latest advancements in AI. It reduces the operational costs associated with fraud while enhancing customer experience, making it easier to transition from a rule-based approach to a combination of artificial intelligence and business/compliance rules. It has a modular approach toward fraud management, allowing legacy modernization programs to evolve gradually. Waylay's payment solution seamlessly operates across cloud, on-premise, and in hybrid environments, harnessing the full capabilities of modern cloud-native applications.
Our cloud-native fraud monitoring solution offers many advantages over traditional payment solutions, making it an attractive option for organizations looking to improve their fraud detection capabilities, including:
Our solution is capable of processing up to 20 mil transactions per day in batches or in real-time with a response time of less than 1ms per transaction—quickly improving fraud detection and prevention capabilities while reducing operational costs and bettering customer confidence.
An AI-based hyperautomation fraud detection solution is cloud neutral and combines machine
learning with a business rules engine to minimize fraud losses while reducing false positives.
Fraudsters, armed with state-of-the-art technologies, are persistently targeting the finance sector. Consequently, these constant attacks contribute to the finance industry incurring hundreds of billions in losses annually.
Learn why by adopting a multifaceted approach—one including ML, AI, and a BRE with robust security measures—enterprises in the financial industry are able to build an even stronger protection and stronger trust with customers while also protecting themselves from significant financial losses and reputational damage.
With the extensive use of e-commerce, credit card fraud has become a major issue that every bank, payment processing platform or web-shop site is facing. Big loss in business is not only related to fraudulent transactions, but also in denying legit transactions, which are deemed to be fraudulent leading to loss in revenues, high levels of customer traveling and more.
Today, the competition in the financial services landscape is growing rapidly with entry from the non-banks. Small fintech companies are nibbling away at large financial institutions’ market share for their products and services. The major value proposition from fintech is top of the line end-to-end customer experience.
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