Hello, everyone. Today I'm going to talk about revolutionary cloud based fraud detection systems and how they are saving financial institutions 43 billion annually. As fraud costs institutions billions of dollars globally, cloud enabled fraud detection solutions are rapidly becoming a game changer. By leveraging advanced machine learning, the systems offer unprecedented levels of accuracy in detecting suspicious transactions. Thank you for listening. Throughout this presentation we'll explore how cloud integration is reshaping fraud prevention, handling millions of transactions per second, and providing unmatched security. Let's begin with the evolution of fraud detection. Traditionally, fraud detection systems relied on rule-based methods. The systems were slow, often processing transactions and batches, taking hours, sorry, one days to identify potential fraud. As a result, these legacy systems had a high false positive rate. With fraud detection, accuracy sometimes as low as 50%. This posed a significant challenge in balancing security and customer experience. Fast forward to today, cloud based fraud detection systems powered by machine learning have revolutionized the space. These systems can analyze millions of transactions per second using vast amounts of data and sophisticated algorithms. Their accuracy in detecting fraud has surpassed 90 percent and their ability to self learn means They can adapt to new fraud patterns without manual intervention. The power of machine learning. Now, let's take a deeper dive into the power of machine learning in fraud detection and data collection. Cloud based platforms aggregate massive amounts of data in real time, pulling from transaction logs, historical customer interactions, and even global threat intelligence. This enables the system to build a comprehensive fraud detection ecosystem. Pattern recognition. Machine learning algorithms sift through billions of data points, detecting subtle correlations and emerging fraud patterns that traditional rule based systems often miss. With an accuracy rate above 90%, the systems can spot complex fraud schemes that would otherwise go unnoticed. Real time risk assessment. These systems provide near instantaneous risk covering, identifying suspicious transactions within milliseconds. This allows financial institutions to block fraudulent transactions before they are completed, and it dramatically reduces false positives compared to the older system. Accelerated response times. Moving on to response times, which have also drastically improved with cloud based systems. Traditional systems. Legacy systems often took anywhere from 30 minutes to several hours to process transactions. And during peak periods, the delay cloud extend to several hours. the delay could extend to several hours. This created a window of vulnerability that fraudsters often exploited. Cloud based systems. In contrast, modern cloud systems operate in real time. With processing speeds of just 20 to 50 milliseconds per transaction by utilizing parallel processing They can analyze thousands of transactions every second catching fraudsters before they can act Slashing false positive a critical benefit of cloud based fraud detection is its ability to reduce false positives Reduction. Our system has reduced false fraud alerts by more than 70 percent, which means fewer disruptions for legitimate customers, allowing them to transact without unnecessary delays or interruptions. Customer Satisfaction. As a result, customer satisfaction scores have significantly improved. Financial institutions that use these solutions report a customer satisfaction rate of over 85 percent due to faster transaction approvals and fewer disruptions. Let's take a case study, a fortune 100 credit card provider. Let's look at a real world example. One of the fortune 100 credit card providers We worked with processes more than 1. 5 million transactions per second, which is more than the New York Stock Exchange. The system handles peak holiday periods without any degradation in performance. By deploying this cloud based fraud detection solution, the institution saw a 71 percent reduction in fraud losses. Which translates to a saving of 1. 5 billion dollars annually. This has not improved their, this not only improved their bottom line, but also enhanced their risk profile and customer trust. Addressing data security. Let's talk about how data security is maintained in the systems. Advanced encryption. We use military grade encryption to protect sensitive financial data with 256 bit AES encryption and quantum resistant protocols to safeguard both data in transit and at rest. Multi layered security. Our security strategy includes AI powered firewalls, intrusion detection systems, and biometric access controls, which have prevented over 99 percent of unauthorized access attempts. Regular security audits. We conduct monthly penetration tests and quarterly third party security audits to ensure compliance with industry standards and maintain certifications such as SOC 2, Type 2, and ISO 27001. Measurable benefits of cloud based fraud detection. And let's now examine the return of interest of these cloud based systems. Traditional systems. Legacy systems typically offer a low return on investment with ROI ranging from only one to two times the investment. They also incur high maintenance costs, often in the millions annually, and cause significant operational delays taking hours to process transactions. Cloud based systems. On the other hand, cloud solutions deliver a much higher ROI, often 10 times the initial investment within the first year. These systems not only cut fraud losses by over 50 percent, but also reduce false positive and dramatically improve processing speed and uptime. With real time processing under 100 milliseconds, financial institutions experience immediate financial benefits. The future of fraud prevention. It is extremely exciting quantum enhanced security as quantum computing advances. We will see real time pattern recognition across billions of transactions while blockchain based smart contracts will automatically flag and prevent over 99 percent of fraudulent items, predictive intelligence. Using advanced behavioral biometrics and machine learning will be able to detect fraud patterns weeks before they become widespread. Global threat network. A unified security ecosystem will allow financial institutions to share anonymized threat data globally, reducing industry wide fraud losses by an estimated 30 percent by 2030. Key takeaways. To summarize, here are key takeaways. AI powered fraud detection. Cloud based systems are leveraging machine learning to transform data. Fraud detection, offering faster speeds and higher accuracy. Data driven security. Data analytics play a vital role in identifying fraud patterns and predicting future threats, allowing for proactive fraud prevention. Collaborative approach. Collaboration among financial institutions and security vendors is essential to stay ahead of fraudsters and enhance overall industry defense. Next steps in transforming your fraud prevention strategy. What can you do next? Evaluate cloud options. Begin by evaluating cloud based fraud detection platform based on key metrics like detection accuracy, processing speed, and integration capabilities. Implement a phased approach. Start with a 30 day pilot program to test system performance, gather user feedback, and fine tune parameters before full deployment. Develop a data strategy. Create a data governance framework to ensure secure and high quality data collection and enable advanced analytics for systems improvement. Foster collaboration. Engage with industry groups to share threat intelligence and help develop a collective defense strategy against emerging fraud threats. Thank you for your attention. I hope this presentation has shed light on how good, how cloud based fraud detection systems can revolutionize the way financial institutions combat fraud. I'm now happy to take any questions you may have. Thank you.