Hello everyone. Welcome to Con 42 Cube Native 2025. I'm S Ula. I work as a principal full stack engineers. Today my presentation topic is architecting resilient risk governance. Let's go to the today's agenda. Today we'll introduce the modern risk landscape and we will discuss. The challenge with the current system, and then we will discuss the three pillars of resilient risk governance. Once after that, we will discuss the implementation and adaption strategy. And finally, we'll discuss measuring success and the feature. Let's come to the introduction. So this presentation is about building a smart and strong immune system for the banks and for the financial companies. So we have three challenges as part of these like regulatory complexity, technology evolution, and third sophisticated threats as part of the regulatory complexity rules and reg regulation. Sir. Frequently changing. It is difficult to adapt. And also the second one, technology evolution, which is very first and very quick for adapting the digital transformation demanding architectural agility. Third one is sophisticated threats. The fraudsters are smart and they're exploiting system vulnerabilities. That is also another third challenging one. Let's come to the fragmentation problem. Majorly, we have a fragmentation problem in most companies. We do have the different departments like customer department, trading department, and compliance department. Each department, they're maintaining their own dataset. Because of that, we will have like major impacts and also nobody can see the full picture of the data flow. Because of this, it makes slow down to identify the risks, and it is very easy to miss some important rules and further to overcome. Enterprise architecture as a strategic backbone. Just think of it as a model blueprint for the entire company. It connects all the disconnected parts, making sure data rules and technology work together smoothly as one powerful system that is the. Main advantage with enterprise architecture coming to three pillars of resilient risk. Governances like first pillars, integrated data ecosystem. It means it's connected data, which everyone. Should share the information instantly. And second one is adaptive compliance. As part of that adaptive compliance, it's like nothing but automatic compliance. The system checks file rule breakdown 24 by seven. And third one is a driven fraud defense that is like smart software that learns to. Spot Nikki Freight. Let's discuss little deep for each pillar in our next slides. See here is the one integrated data ecosystems. One is a trading systems, and another one is a customer data. Another one is a compliance platforms and unified risk review. These all four are majorly. Further integrated data ecosystems like this is about breaking down the walls between departments. We connect the data from trading compliance and customers to create one single real-time dashboard that shows all the risks clearly. Breaking down data silos like traditional approach, isolated departmental database and manual data reconciliation and delayed risk vulnerabilities. Inconsistent reporting standards for this traditional approach. I can say the best example is that three people are in a separated. In separate rooms and each one trying to communicate, but they cannot because the wise is slow and because of that, walls and three people are in a different rooms. The wise is messy and the error in the prawn while talking, while discussing sharing, but that is a traditional approach, can say the example and. Architecture LED integration is unified data, fabric architecture, real time data synchronization, instant risk assessment capabilities, standardized government governance frameworks for that. Best example I can say is like everyone is in one platform and one room and live group chat with. Because of that, everyone are in one room. One group chat so that what is the outcome? It is very first and accurate, and everyone will be on the same page. That is what it's an perfect example for the architecture lead integration. Second one, adaptive compliance framework. Adaptive compliance framework, mainly like embedded controls. And automated reporting, continuous monitoring, regulatory adoption. These four are the major things for that. Here in, instead of having people manually checking thousands of transactions for rule breaking, we can build the rules directly into the system so that it automatically checks the rules. And everything. It generates a report and it gives alerts immediately if something is wrong. That is a major advantage with adapting or automating compliance framework. Let's go to the third pillar, which is most more interesting one AI driven fraud defense as part of the AI driven fraud defense. We have four. One is a. Pattern recognition. And third one is a realtime analysis. Third one is a legacy, SY legacy systems integration. And fourth one is a human oversight. So what is that pattern recognition? If anything happens abnormal behavior, like you know something differently, then we can identify using mission learning algorithms so that the pattern recognition plays a very vital role. Realtime analysis if anything is strange, the realtime analysis, it'll give the flag. Coming to the legacy integration, this AI driven fraud defense if you integrate our system with the ai, it automatically works with our world system. Says that final one is a human oversight. Human oversight is needed to make sure the final call on tricky cases. And what are the implementation challenges and solutions? So basically organization organizational resistance. Basically the people are not liking the change. They just want to continue with the established process. So that is one major challenge, how we can welcome. Such a challenge. Only solution is we need to train them and we need to roll out challenges slowly. Not like in not everything at once. Technical depth is another challenging Legacy systems integration is very complex compared to modernize technical things like what is the solution for legacy systems integration capability. Complexity is we need to use the modern connectors to link them step by step. Another one is cost justification. Cost justification. We need to show like how much we are saving from the less frauds and how much we are saving based on the lawyer compliance. That we need to overcome that. Another one is phase adaption strategy. Like we have first four phases. One is a foundation phase, which is a very key, and we need to establish data governance standards and basic integration capabilities. We all need to agree on how to manage data. And the second one is a integration phase. Integration phase is a, it needs to connect critical systems and important systems, which is a most powerful one. Another one is a intelligent phase. Intelligent phase. We need to turn on the AI and AI models. The fourth one is a optimization phase. It makes. Continuous improvements need to happen and it keep making it better and bigger. That's the one. And measuring the success, key outcome of this one, like I can say 60% faster complaints. Reports that used to take a weeks. With this, it can take only days. And GT 5% of the better fraud detection. We can catch almost all fraud attempt, and another one is 40% cost saving. It is a very huge success. I can say. We spent less on manual checks and mistakes, 99% system availability. The system is always up and running and reliable. Conclusion, the future of risk governance. Basically by using this blueprint, like enterprise architecture companies become strong, agile, and ready for whatever comes next. They can grow safely, follow rules easily, and stay ahead of criminals. Which gives, they may use advantage over competitors. Let's take the key takeaways. Like I can say, enterprise architecture is the key to managing risks and connector connect our data to see the whole picture. EI enhances fraud detection. And adaption ensures the success. That's all pretty much about my today presentation. It's time for the questions. If you have any questions, please feel free to reach out to me through LinkedIn. Thank you. Bye-bye.