Good morning everyone. I'm happy to be here today. I'm Navin Kado. I've been working in the field of automations and cloud technologies for many years, and I'm excited to share with you how AI is revolutionizing financial reconciliations. In today's work where speed, accuracy, and complaints are paramount, AI plays a critical role. But also the human expertise is still very necessary. We are gonna explore how AI and human collaboration can drastically improve our financial processes. Let's jump right end. So let's start by looking at where we are today. Large enterprises rely on complex ERP systems, and this systems make reconciliation a tough processes because they don't always integrate smoothly. I. You have teams handling a different systems manually, which often causes bottleneck. For example, a 30% delay in month end closing is not uncommon, especially in companies that is still heavily on manual processes. As global digital transactions grow exponentially, the volume of data the companies needs to reconcile will become overwhelming. Without automations in this rapidly evolving landscape, the traditional approach to reconciliations simply can't keep up. So how AI come into the play. First, AI can actually detect patents like spatting, duplicate invoices faster than human ever could do. AI driven patent recognitions through mission learning and natural language processing can identify issues within seconds that would otherwise take days or even weeks to detect. And we also can have RPA robotic process automation tool pair with ai, and this automations can reduce MA many manual touch points by 60%, which speeds up processes and significantly reduces human errors. Imagine a system where a routine reconciliations are happening in the background without constant human oversight. And finally, AI shines in exceptional handling. With predictive analytics, AI can forecast animal with up to 85% accuracy, drastically cutting down the time needed for resolutions. This allows your human team to focus on more complex value added task. Now let's talk about the benefits of combining human intelligence with ai. And this is not about AI replacing jobs. It's about empowering humans to do more meaningful work. First, we see improved accuracy. AI can reduce false positives by 40%, which means fewer errors and cleaner financial records. In a world where we, even a small mistakes can cost million, this is crucial in terms of efficiencies. The AI power reconciliation systems can reduce month and close cycles from 10 days to just three days. That's a huge time saver, especially for larger organizations where even delays can have ripple effects. And finally, ai. With the risk management, regulatory compliance risk drops by 50% because AI assisted audit catches potentials issues before they become more major problems. It ensures your always head of the CO when it comes to the compliance. Let's dive into the technical implementation strategy. To implement a AI in a financial reconciliations, you need a clear strategy. First, we start with a system. Integrations. We can utilize IPAs tool like MuleSoft with the API LED architecture and queuing mechanism enables a faster and real time reconciliations across ERPs. This ensures seamless communications between different systems. Next, as training programs resulted in a 91% eruption rate, this shows how with the right training, the teams are benefited. Phase implementation is a key where we can achieve a scalable deployment. And with the AI driven proof of concept, we can accelerate the go live time by 64%. Lastly, the feedback loops are essential. We found that biweekly sprint reviews improve system utilizations close to 67%. This iterative feedback ensures the system is always improving and adapting to their business needs. This numbers really sparks for themself. The companies that have adopted AI for reconciliations, I've seen of 45% of cost reductions, saving millions of dollars annually by automating their reconciliation processes. Reconciliation times, which used to take five days are now reduced to just hours, gaining almost 67% in efficiency. So this matrix shows how AI is not just nice to have, but a must have for companies looking to stay competitive. Looking forward for ai, AI will continue to have a transformative impact on financial reconciliations. Processing times will drop by 70%. Making gig, making it easier to manage even larger volume of transaction without overwhelming the team. However, the key to the success is man, maintaining a balance approach. While AI is incredible at handling data, it still requires human insights to make sure AI outputs align with business needs and regulatory requirements. That human oversight is crucial in maintaining accuracy and relevance as regulatory evolve. AI systems will also need to evolve adapting to new laws and guidelines, which ensures long-term compliance. Thank you all for your time today. I truly hope this session provided a valuable insight into powerful potential of AI in financial reconciliation. I. My goal was to highlight not only the technical possibilities, but also the real world benefits of leveraging human AI collaboration. As we move forward. I encourage you to explore how these technologies can transform your workflows and help your organization thrive. I'm excited about the future of AI driven finance, and I look forward to seeing the innovation we will create together. Thank you.