Good morning. Good afternoon. Good evening, everyone. This is Vinod Dupatturi. I had more than 11 years of experience in financial domain. Currently, I'm working as a senior software engineer in one of the largest card based company. Thank you for joining us today. Today's topic is financial fraud. We are at a pivotal moment in the evolution of the financial sector in a world where digital transactions are omnipresent and the threat we face are not only growing in number, but also in a sophistication. Today, I'm excited to share how artificial intelligence is not just enhancing our ability to combat the fraud, but also revolutionizing it. Let's discuss the elephant in the room, financial fraud, which is a massive issue, costing business and consumers globally around like a 5. 4 trillion annually, which is a significant drain on a global economy that affects everyone from small business to large institutions. Is the financial fraud what it is? country, it impact would rival the GDP of a major economic power, showing both the idiosity of the fraudsters and the weakness in our traditional systems. Talking about the traditional systems, fall short in identifying the fraud detection, but AI powered systems are transforming the field by achieving AI powered 97 percent accuracy in the detection of the fraud. These systems also reduce the false positive by 63%, saving millions in transactions and building trust, which is an essential asset in the financial sector, where trust drives customer engagement and loyalty. Behind the statistics are the real people, businesses and economies. False positive disrupt legitimate transactions while undetected fraud leads to financial loss and eroded trust. This discussion highlights AI as a necessity for the modern financial security with a dual goal, reducing economic losses and enhancing operational trust and efficiency worldwide. Let's discuss about the fraud detection followed by Prevention and finally implementation. Let's jump into the fraud detection. There are like multiple ways of fraud detection such as supervised learning, unsupervised learning and deep learning neural networks. First we will cover the supervised learning. What is the supervised learning? Supervised learning is Key AI technology for combating financial fraud. Using labeled historic data to teach models how to detect fraudulent patterns. Picture an ever vigilant agent analyzing over 100 million, millions of records carefully, categorize the transactions. These Training enables AI to detect fraud with 99. 9 percent accuracy. Supervised learning works in real time, identifying fraud as it happens and preventing fraudulent transactions from completing. This not only safeguards the assets, but also boosts efficiency, allowing financial institutions to handle high transaction volumes securely and without any delays. In essence, supervised learning turns data into practice. Powerful fraud detection tools. It adapts and evolves with the new data and emerging fraud tactics and staying ahead in ever changing threats. Now super, we are done with the supervised learning. Let's jump into the unsupervised learning. What is unsupervised learning? Unsupervised learning plays a pivotal role in exposing hidden fraud patterns, detecting emerging threats without relying on the labelled data. Unlike traditional systems, it identifies irregularities in unclassified data by uncovering new fraud elements. tactics as they arise. This ability enables early detection of unknown threats with a 42 percent improvement in the fraud identification rate, which is a transformative leap in the financial security. By proactively addressing fraud, unsupervised learning prevents significant loss and strengthens customer trust in financial systems, constantly evolving. This technology learns from everyday transactions and anomalies staying ahead of increasingly sophisticated fraud strategies. Finally, deep Neural networks are the advanced brain power enabling us to analyze data on an unprecedented scale. Each transaction becomes a detailed data point, crossing through multiple layers of analysis. These networks analyze over 10, 000 data points per transaction in a millisecond, detecting patterns, anomalies that smaller systems or similar systems can't detect. might miss. Beyond identifying known fraud patterns, deep learning uncovers complex signals of emerging threats, achieving 70 percent, sorry, 76 percent reduction in the card. present fraud. This technology provided robust, scalable, and real time fraud detection systems that not only reacted to the fraud, but also anticipate and prevent it. Integrating deep learning into fraud detection is a key. Game changing leap solidifying our position as the leaders in the financial security and ensuring unmatched protection for millions of users worldwide. Real time fraud prevention system. One, our real time fraud protection, system Process an incredible 100k transactions per second, delivering unmatched speed and accuracy, which is critical for the financial sector. Transactions are analyzed under 50 milliseconds, faster than a blink, ensuring smooth processing for legitimate activities that, and instant actions against potential threats. This performance is powered by advanced algorithms and high performance computing, like comp, quantum computing despa designed to handle continuous and high volume traffic effortlessly the systems operate 24 by 7 with constant monitoring and instant alerts and providing the round the clock protection and vigilance by detection and responding to the threats almost instantly we enable customer trust reducing disruption and significantly lowering the risk of financial loss from the fraud Till now we have covered detection. Let's dive into the fraud prevention methods. Behavioral biometrics and device fingerprints combines the technology and human behavior to create a robust shield against fraud. Behavioral biometrics analyze a unique pattern such as Typing rhythms, mouse movements, and the scrolling habits to continuously authenticate users and reduce unauthorized access. For example, unusual changing the typing speed or patterns during the transaction can signal the potential fraud, enabling a quick action. Device fingerprints add another layer of the security by Explaining the device details such as the operating system, hardware, IP errors, and identifying the suspicious and or unfamiliar devices. Together, this technology reduces the account overtake attempt by 89 percent accuracy. Seamlessly security that protects without disrupting the user experience. By understanding this behavior, this device integrations, we deliver a high security while maintaining a personalized and smooth journey. Synthetic identity detection. What is a synthetic identity detection? Synthetic identity detection or a theft is a sophistication form of fraud where Criminals combine fake information to create a new identity, making detection more challenging. Our advanced learning algorithms, and analyze data from multiple sources, identifying inconsistency in the data like social security number, credit card history to detect the fake, identities. With 94 percent success rate in identifying synthetic fraud, Before they you, they are used our system protects financial institutions and prevent broader economics and harmful of personal information. This approach has saved estimation of 3. 2 million billion dollars have avoiding both the direct cost for the fraud and lengthy investigation and legal processes that follows. By leveraging the data science and mission learning, we are setting a new standards in the fraud. Prevention, staying ahead of evolving threats. We also prioritize ethical data use and compliance with the global regulations, ensuring the balance between the security and the user privacy. Last one. NLP. NLP stands for the Natural Language Processing. Natural Language Processing is a powerful AI tool in combating phishing, which is a common and deceptive cyber threat. Phishing attacks mimics legitimate communication to steal sensitive information. Our NLP system analyzes over a million daily interactions. to detect suspicious patterns and contents. NLP understands the language modulations identifying the red flags like urgent calls to action or unexpected requests for personal information with high precision. With a 98 percent success rate in blocking phishing attempts, our technology safeguard users identifying financial institutions from sophisticated scams. As phishing tactics evolve, so does our NLP technologies and continuously learning and adapting to them. to detect new threats by integrating NLP. We proactively anticipate and neutralize phishing attacks, ensuring a trust and security in our digital age. Okay, so far we are done with the detection and the prevention. Let's dive into the implementation of it. Implementing AI in the fraud detection requires a comprehensive approach, starting with the strict regulatory compliance to ensure the transparency and adherence to the global financial regulations. User experience remains a top priority with AI systems designed to provide robust security with maintaining seamless and user friendly interactions. Continuous learning is a center for our strategy, enabling AI models to adapt to the new threats, learn from the real time data, staying ahead in ever changing financial fraud landscape. Cross functional interactions is a key. innovations involved, collaboration across IITs, ITs, security, business units to ensure a unified innovation approach to fraud preventions. This holistic strategy combines compliance, user focus, adaptability, and the net teamwork to efficiency. effectively leverage AI in safeguarding financial systems. Results and future outlook. Our AI powered fraud detection systems have delivered outstanding results with a 91 percent customer satisfaction rate reflecting trust in our security measures. Fraud investigations have been cut by 73 percent showcasing the efficiency and effectiveness of our AI Looking ahead, we envision the future of AI driven, adaptive, and customer focused security that not only is responsible for a fraud, but also predicts and prevents it proactively. As leaders in this journey, we are shaping the future of financial security with AI advancements. Thank you. Have a great day.