Hey, good morning everyone. It's an absolute pleasure to be here today. Today I will be discussing about scaling financial design systems with go by building high performance FinTech infrastructure in the cloud. Let's start the session. How many of you have ever been frustrated with slow and outdated financial systems? It may be a via transfer. Took long. A repayment got stuck without a clear reason. We have been there. Financial system should be fast, secure, and frictionless. But legacy structure and outdated technology often makes this a challenging. This is where go on cloud native architecture comes in. They enable us to build scalable. Resilient and high performance financial systems that can perform millions of transactions in real time. In today's session, I will walk you through how we process millions of transaction style using Go Power Microservices by leveraging AI and machine learning to predict risk, detect fraud, and optimize financial decisions, build secure. Scalable A PS that tell us seamless integration across banks on digital wallets and financial applications. Reduce infrastructure cost by 40% while some inte increase speed and security. Does it sound exciting? Now, let's deep dive in. now let's deep dive into our microservice architecture. Now I built a truly scalable financial system. We need a solid architectural foundation. Let's imagine a highway, let's imagine a highway. Where cars move smoothly without traffic jumps. That's exactly what we have built with our microservice architecture, cloud native process by distributing transaction. Processing. We present services, overloads and exits industry standards by 35% by using Go. Go is built for speed and con. While traditional languages like Java or Python struggle with high load processing with go goin enables us to handle thousands of requests per second with minimal latency coming to resilience distributor systems. Our architecture guarantees that 99.99% uptime by ensuring that even if a service fails, traffic is automatically re rerouted to backup notes. To put this into. Perspective, think about Black Friday or major stock market trading days when Dragon section volume score search. Our system scales dynamically to handle these spikes, ensuring a seamless experience for millions of users. But not only scalability, we also need intelligence in our systems because everywhere we see. Artificial intelligence is growing big and machine learning is dominating everywhere. So let's move to mission learning integration. Coming to mission learning, integration and artificial intelligence. These are revolutionaries in financial decision making. So how do we bring intelligence? Into FinTech. That's what our question. Over here with help of data ingestion, we process massive amount of structured and unstructured data, including transactions. Under histories on real time marketing feeds, customer spending patterns, and also with help of AI powered analysis, our module uncovers patterns that human might overlook, like such as predicting which customer are likely to default on loans, identifying trading. Opportunities in volatile market security and fraud detection, our AI reduced false positive by 78% by ensuring that legitimate transactions go through without unnecessary blocks. Quick caution for you all guys here. How many of you had. Had credit card transaction declined due to security concerns. Now, imagine if instead of blocking your legitimate transaction, AI could accurately differentiate between fraud and a normal purchase. That's exactly what our system does. But intelligence is only useful if it can be shared efficiently. That brings us API and backbone of modern financial systems coming to API ecosystem. Coming to API ecosystem, APIs are the glue that connects modern financial systems. Without them, banks and FinTech platforms would be isolated. Islands struggling to communicate with each other. Our API ecosystem handles over 15 million dial requests with 99.9 uptime, supporting both rest and graphical, offering flexibility for different clients. Accelerates integration, banks and FinTech companies can go live in weeks instead of months. Let's take a real world example. Imagine a startup company that wants to offer instant credit scoring with our a PS, they can tap into our AI engine, analyze the user's credit worthiness in real time, and approve a loan within seconds. API alone or in turnoff, we need strong, scalable cloud infrastructure to support them. Let's explore that next. Coming to cloud infrastructure revolution, migrating to the cloud is ingested trend. It's necessary for modern financial systems by ensuring zero downtime migration, be transactioned, enter bank system to the cloud without disturbing daily operations. 40% of cost reduction. By leveraging serverless computing, we pay only for what we use. Reducing the need for expenses on premises servers and also multi-cloud strategy utilizing multiple cloud providers, ensuring redundancy, prevents outage, and helps company to compile with regional data regulations. For example, a tradition bank that use it to take day two. The settlement payments can now process them in real time thanks to our cloud infrastructure. Now that we have covered scalability and cloud efficiency, let's talk about what really matters to customers. Personalized financial services. Let's move to it. Coming to personalized financial services, ai. AI driven financial is. Reshaping the way customers manage their money in by investment strategies. Our AI driven realtime investment recommendations. Customize the individual's risk profile. Coming to depth management clients using our platform. Save an average of 15% on interest payments. Through optimized repayment strategies, coming to financial planning, predictive modeling helps people prepare for life's financial uncertainties. To support these intelligent financial services, we need a rock solid DevOps strategy. Let's take a look at how we achieve that. we all know about DevOps coming to, for the. we all know about DevOps, right? DevOps excellence. Without DevOps, no one or none of these innovations would be possible. 95 percentage of test coverage before deploying any code by insuring zero downtime deployment, using blue green deployment strategies and also realtime monitoring allows us to. Detect resolve issues before customers even notice. The result is faster and innovation, greater reliability and happier customers. Another key technology driving trustees, FinTech in blockchain. Let's see how we are integrating it. Coming to blockchain integration, blockchain is transforming financial transactions by introducing greater trust and transparency. Smart contracts are like, it eliminates middleman and reducing cost by 30% on risk assessment. Every transaction is permanently recorded, preventing fraud and insured compliance. Adapt to market contracts, our system dynamically responds to market in fluctuations in real time. Speaking of fraud, let's take a closer look at how we can stop financial crimes before they happen. let's move to. Fraud detection systems fraud remains one of the biggest challenging in FinTech as all we know, and we take it seriously, to resolve this. Microsecond monitoring transactions are analyzed in real time to prevent fraud before it happens. AI powered detections. Our models continuously learn from millions of past fraud items and improve the accuracy. The fraud ion is by 60 th 63%. Banks using our systems help cut fraud losses by nearly two third, but stopping fraud isn't enough. We also have to meet strict regulatory. Requirements. So let's jump into regulatory Confluence. Compliance isn't just about following rules, it's about protecting business and all our customers, 99.7% accuracy. In EML screening, we flag suspicious transactions instantly. KYC in 40 seconds. Customers onboard. In under a minute. Instead of days, 98% less manual work. Compliance teams save hundreds of hours through automation. Now coming to measurable business outcomes, oh, 78% faster processing transaction happened almost instantly. 63% of road reduction, greater security, and low risk, 89% developer productivity boost more innovations and less maintenance. 42% cost savings by less infrastructure waste and more efficiency coming to conclusion. How do we make financial systems faster, smarter, and safer? The all out of this we can say is like with help of AI driven and cloud powered and go based infrastructure. Thank you everyone for attending the session and I would like to take any questions. Thank you all.