Everyone, good afternoon, good morning, and good evening. Whatever the time is on today. I'm pretty much so happy that we are going to discuss about the quantifying RIRI, TE management and how AI implementation transform of financial in 2025. So this is the one of the pretty good topic, which I'm pretty much looking forward and looking pretty much interested. To see how it's going to help the human kind or humans or whatever, whoever is going to get the more benefits using this ai. Okay, which one of the primary example is myself? Which I'm getting benefit through AI all the time with respect to the system. At the same time, how is helping me in the real time at the same time, how is helping me in both personal and personal ways? Which we can discuss in this making decision. The primary focus should be on the financial services, how AE is helping the banking sector or other, any other tech sector, which we are going to discuss in this meeting. Okay, thank you. Let's delve into this one. If we can see the, my first slide quantifying RI. If you see the synopsis here, the financial service industry has witnessed unprecedented. Transformation through strategic AI implementation with the global enrichment facing 1 42 0.83 billion. This is reflecting year's crucial to in aging traditional financial operations and driving industry enhancements why AI tion so rapidly simply, let's put the next slide. Okay. Yeah, simply put it delivers tangible deals. A driven automation has imposed operational efficiency by 35%, streamlining the routine process such as account creation, consolidation, transaction processing, and data entry. Financial institution like JP Morgan Chase, for example, have successfully deferred a to automate loan approvals and account verification process, significantly reducing manual labor and human error. Just think about this. Within this year itself, we are seeing 33% of operational efficiency, as we discussed about right now. The example of JP Morgan Chase has a split A to automate loan approvals and the verification process, it used to take so much of time. Previously we go for any loan approval. The initial process surface, they used to take minimum two weeks, the maximum of four weeks or five weeks. Now it came down to less than a week. It is saying so much of time for the bank at the same time saying so much time for that end user customer. Also at the same time ation process, but this having so much of manual labor and human error that is cutting so much of term. Okay, coming back to the next finance, what I'm saying is much of 15%. Okay. In general, the financial forecasting will be done by the most of the companies across the world. Out of that. We can see right now in this effect 25 25, we are seeing the 15% with ai. Like for example, if they take Goldman Sachs, but it's one of the biggest company to market fluctuations and budget needs unprecedented. Additionally, a systems have reduced data processing errors about 20%. Is your team taking example of Goldman Sachs? Everyone will follow. The Goldman says Complete what? They provide their predictions about the market, either or contract India, sorry, these are Nasdaq here. Do here about the New York where we, everyone eagerly wait to see what's going to the predictions for tomorrow or day after the next week. Other we everything. So instead of Goldmans has used to spend so much of manual hours, now they onboard with a. They're able to provide the accurate information with AI and then the pressure also so accurate and so good. That's the reason a is going to be the game changer or the path breaker, whatever your name, it's going to help the humankind in much better ways. Okay. Let's go to the next slide. Okay. Ex, exactly. And then let's go to. When we are talking about all this technical architecture about how A is going to help, I dive into three parts. Generative A and security protocol. That's because I was a. How it going to help central to these achievements is sophisticated technical architecture anchored by the generator. A systems capable crossing over 1.2 million tokens per second. We're talking about 1.2 million tokens per second, transform customer interactions and ending into deeply present experiences. Banks like HSBC's now employ advanced chart bots for customer service, providing immediate tire response based on a real time, and also customer profiles and financial behaviors. Okay, so think think about what we are doing with the h SBCs Bank and they have any number of transitions, all time going on the general way we can validate and monitor, we can remove the analysis and we can develop so many agents. I can talk about so much of AA agents, which we are right now, the going on across the world. That agency is going to help. And then with the agents, we are going to processing 1.3 million to per second. It being said, it cannot be done with the human, can be done with the A only. So with the help of aa, because we see a kind of, banks are using the third parts. For customer service. I'm saying a agents, which is going to change, but we can talk about chart parts or agents, whatever you name it. Those going to provide that providing immediate tire responsibility on the real time of customer profiles and financial bills. Seriously, if you're doing something right previously, if you send any request to the bank, it'll take 24 to 48 hours or more than that. To get a response with the chart parts, what we are going to develop with the generative AI and agents, what we are going to go and discuss more of what we're going to see much more in future. Those will change the banking sector completely like how the processing like one point million tokens per second. Let's go to the one more called creative analytics. Where predict actually in general water about what's going to happen with the data water we have with the actuals, what we call the actuals. So with the actual set we can see, okay for three years or four years, it used to take so much of time and the human interactions at the same time, lot of labor and then everyone need to spend so much of time to analyzing the what happened for the past three years and then come up with the numbers. What's going to happen in the next three years. And then we don't know how much that with the ai, if you're providing that predictive analytics. Okay. Approximately, there's 2.5 petabytes of data financially, daily. In respect of any bank, the number you can at number 2.5 petabytes, it's equal to thousands of digital libraries for entrance enrichment. Firms like BlackRock utilize breakthrough analytics to swiftly identify emerging trends, anticipate marketing shift and manage risk culturally securing a robust portfolio performance. Even market, BlackRock is one of the biggest emission firms, which they're using a breakthrough analytics they used to do previously as well, but with a lot of human intervention. The lever now with leveraging this analytics with a. It's pretty much game changing. And then the title also so good and accurate. And if you need to think about that as a language, you're doing the everything like generative ai, creative analytics, you should not forget about security. Security is one of the key factor where whatever things you're doing, you need to be under secured. Otherwise you'll see so much of anomalies and their data and everything will go to the other spaces and it'll be. The world as well. So that's the reason we need to consider security. It's a paramount in financial services, AI implementation in corporate advanced, multi-layered encryption and quantum algorithms to secure sensitive information. Institution like Visa have AI driven cybersecurity protocols, drastically reducing security breaches and enduring strict compliance with the global financial ions. So we need to make sure if you're using generative AI or analytics, the security must be for all the time. So that means you need to think about security when you're thinking about generative aid. Either it's chat bot or agents, whatever you are going to use. To ease the process, you need to think about security because you're talking about the individual PI data. We need to always should be SOX compliant and then we should make sure we are under security guidelines, like how each company is spending some billions of data and security. That's where we to make sure our end users are stakeholders that should be much more secure and nothing can be done with them, any of these anomalies. Okay. The next one, anti money laning impact. So maybe right now we are seeing some AI has notably anti-money Laning AM practices a power a m Returns now bo, over 83.5. Catalyst accuracy in threat detection, identifying social security financial crimes that previously went unnoticed. We are, right now, we are seeing so, so we're seeing so many financial crimes. But even we don't know what's going to ha what's going to happen, what happened previously because of, we don't have a at the time, but the AI is on board now. We are seeing 83.5% of the protection identifying so sophisticated financial crimes that previously went unnoticed. Financial institutions such as CD Bank have significantly reduced false by 65% stimulating complaints, operations, and improving customer experiences. Additionally, risk assessments at major banks have accelerated by two 40% turning lengthy investigation into efficient rapid response process. Okay, this, we need to talk about this A ML anti-money laundering practices. That's where we know about money landing, what kind of so many things we had previously with the ai. We can get rid of all this money landing practices because AI is more powerful and secure if you follow all the security process with that. We can see that 83.5% of the reduction and followed by the identifying the financial crimes, which previously completely unnoticed even. We don't know some financial crimes are happening because of how much good there are about all these things, but with the a for should we can get rid of all of these things so that the transactions should be pretty clean and. All the way we have transparency in the address between the banks to the customer B2B, B2C are technical companies, whoever the companies is going to leverage this. A entry, money landing practices that will help them a lot. And then looking forward let's go next one. Okay. What will be the future of the banking system? That's one thing. Pretty much I'm looking forward. Okay. The looking forward is influence will continue to expand by 2027, maybe nearby, or it may take much little bit more time, but A is projected to handle approximately 85% of 14 banking transactions. For example, Wells Fargo, for instance, is actively moving forward this future. Implementing advanced automated systems to manage routine transactions. Freeing financial advisors to focus on personality, financial planning, and complex customer needs. So right now, if you go to any of the bank, you may see multiple people and each person have that so many responsibilities. And sometimes you may feel that, okay, why am these guys are not helping me a lot? Because they have so many other things to take care because they're working for the bank. The bank will have so much of protocols they to follow each and every protocol. Then only they can be secure. With the help of aa, like routine banking transactions, like the tele transactions, the other customer questions either you can go, we can send it to aa, like chat bots or agents. The other way around you can directly go to the kiosk or directly talk to the kind of robo, which I'm expecting. You may see be 20%. For example, like Wells Fargo is actively working with the future. Implementing advanced automated systems to manage routine transactions. Freeing the financial advice, like if you want to go for the bank, for the loan process, okay. It should take so much of paperwork, the initial discussion, everything. Now the advisor, not only to what you approve the time he or she can spend so much of time with you currently, or personal finance planning, and. Customer needs, complex customer needs. The complex customer should be anyone. If you're trying to do something different and you want to understand about how the bank is working on everything, maybe you might not get the information right now with the A, with the bots and everything, but you can get the same information with the from the in human, which they're able to focus only on those things. That is a groundbreaking and changing for the banking sector, which we may see by 2027. That's one thing I'm pretty much looking forward. And not only Wells Fargo, which I'm thinking about the Bank of America, chase, our key bank, or what are the bank, you name it, across worldwide. We have almost more than a hundred thousand plus banks, which I am giving you some pretty much gold some information of contract banks. But where we have one 90 plus countries, each country will have different banks and the common bank, private bank, whoever they need to follow the guidelines of. Cary Rules, bank Rules, and with that all the financial advisor will have so much of button on them. So if you're able to automate the routine task so that they can concentrate mainly on this advising the end user customers like you and me will go to the bank. We'll get all the information, or if you call them Financial Advisor, you can take the card, they can provide you all the information. Pretty much I'm looking forward to see, going to help. Exactly. And then the same thing about the risk models. The risk models issued extraordinary accuracy, which so many of lms are going to see in future. Right now we are pretty less, this means still companies are working on the lms. With that, we can get 97% of enabling fair lending practices. For example, FinTech companies like Aman Square use advanced models to accurately assess clear risk, offering equitable financial products to historically deserved populations. See this? So what are the transactions? What are the take an exam? If I'm going to apply for the loan, okay, I need to fill all recommendation by default. Our banks are tied with the Affirm are square. They'll pull all the information off you and they'll send us to the bank so that bank can do the, all the ities and everything with the A immediately. Right now all Affirm are Square is leveraging the advanced AI models so that once they get the information, they're doing all the checks right away so that the banks are able to spend pretty less time on this, in this, on this application, everything. The ation making will be much faster. With this, we can find anomalies or something or someone is trying to do some bad things or anything with AI can pretty much easily so that the bankers cannot approve the loan or the persons who are in the pretty genuine information so that they can get the loans pretty much easy and even we need to talk about the, a social benefits as well, how it is going to help the V and operational enhancements. YAYA driven initiatives have actionable banking service to 1.7 billion previously unbanked users globally. Mobile payment platform like AM and Kenya, which is a one of the country in Africa. Maybe some part, maybe still into the old traditional ways there to go with the advanced technology, but still come. Some banks are coming back and saying that, okay, we are going to leverage ai, which helped them pouring millions with secure and can banking services. Okay. What about the community impact? So this is one of my sector where we can see the community, how it's going to help. The AI has strengthened consumer protection with advanced fraud detection systems preventing approximately 15.4 billion in consumer financial losses, like pay for instance, and plus AI ActionAlly to in a time safeguarding millions of ways in ware from sophisticated digital threats. If you're talking about the global financial inclusion where we are talking about the Kenya Bank, which they're going to leverage a enable financial access and pouring with secure banking services, so we know about so many people in the operating don't about the banking and everything. With this, they can understand easily how AI going to help them in their own language. In their own understable language so that they can go through each and everything in the, and they can listen and they can take ation instead of going for the middle mass. And the middleman can simply take everything. And if they left okay, that they can simply, whatever they have, the mobile or anything, they can go to the bank and with all these things with the air. And one more thing about the small business medium and business entrepreneurs. How it's going to help the small and medium business? Business success is right now we are seeing with the a enhancement, we are seeing 40% of increase loan approval. Enhancements, like companies like Kaba or Fund Box utilize a efficiently SME credit witness supporting academic growth and innovation in our understand communities, undeserved communities. Okay. That's the thing. Finally how it is going to implement effective aid deployment in must s planning clearly find objectives, measurable outcomes, and comprehensive talent and skill. Government, robust governance and ethical guide in due responsible use, continuous monitoring and adaptive improvements aligned with evolving regulated frameworks all the time we are talking about how we can improve the ai. At the same time, we need to think about how statistically it's going to be planned. Clearly identified objects, measurable outcomes, and comprehensive talent and skill development. These are the things we need to think about is AI improvement, robust governance and ethical guidance in general, responsible use, continuous monitoring, for sure, how you monitor the all the services in the cloud infrastructure the same way we should have wanting about the A and implement evolving frameworks. Finally, in conclusion, what I want to say is. Strategic a deployment is fundamentally transforming financial services, delivering measurable, ROI miserable, ROI and RI. Enhancing human roles and positively impacting communities globally. A, the parents a unique opportunity, not mely as a technical advancement, but as a powerful tool of creating a fair, more inclusive financial level. And what if you see the compliance automation, a motor religion is across justification, complaints, documentation, generation, audit, ation, this scanning, if you see about documentation, we to spend so much of time previously to create a document the meaningful way with the help of a in less than our, I don't know, not an hour, less than 10 minutes. We are able to create a document, which is helping everyone. Okay. I'm one of the example where I'm going to, I'm using it right now with the a. Previously I need to spend hours and hours on the documentation to put everything in a proper order. Now I'm ING synopsis and everything. What I want to create a document, the A, is helping me to create a document so that I don't need to spend hours and hours, like every day, like two, three hours. I need to spend a documentation. No, I'm spending less than hour or maybe less. And that's the way how the document generation has changed over period of last two years with the AI audit practitioner. Previously for the audit, we used to spend so much of time to putting all the documents in one place and go to each every document. And the boring and worrying and all the time, okay, yeah, sorry. We need to document instead of that. Now with this ai, those activities much more. Easier and I can spend much more time on how I can improve the other financial systems, how I can help the other stakeholders and everything. I can spend some more time there instead of sending the, doing the routine activities. Yep. Finally, the key measurable impact. How is going, how ROI, how is the a going to implement ROI across multiple financial domains? S implementation, how, implementation strategy. Define clear optics. Envision talent. Okay. How I going to envision the talent? Like enhancing the human growth and points impact in community. And then stablish governance. Measure RI continuously. Other. We need to measure the how. What is the R way with the A. That will help a lot. These are the key takeaways, which I always benefit. Measurable impact, strategy, implementation, human, a partnership and community benefit. A implementation, RIA success request through all the global planning come from combining a capital expertise, a transformation beyond ROI to create a broader social impact. Finally, thank you. Thank you for joining this con particular session. Let's continue Leveraging yes, transformative power to shape a brighter, more equitable financial future for everyone. This is what I want to discuss with you all about this AI implementation with respect to the financial world. Hope this helps everyone. Thank you.