Hi, everyone. Hope everyone is doing great. I'm Jayakrishna Vemuri. I'm having more than 14 years of experience in IT industry in implementing high volume, high performance, large scale investment banking products using multiple database technologies like Oracle, Sybase, Snowflake, Microsoft Azure. I have a strong expertise in front to back trading applications on how they work and how you just perform the reconciliation process for the regulatory and reporting needs. As part of my job responsibilities, I was primarily involved in building multiple applications using on prem, hybrid and cloud technologies with strong domain allies. Today, we're going to talk about driving precision and efficiency of cloud based reconciliation applications in investment banking domain. as you all know, investment banking industry operates on massive scale of processing millions and billions of transactions daily. accurate and timely reconciliation of financial data is essential for compliance, risk management, and strategic decision making. So this presentation will explore the transformative power of Cloud based reconciliation applications and their impact on the investment banking and IT industry. Let's get into that. So first, I'm going to talk about the current challenges with traditional reconciliation process. So Let's talk about how much time consuming it's going to take. So the legacy reconciliation often involves, significant manual effort. user has to perform the data analysis and then prepare the data in the spreadsheet, ingest the data, and once the data has been loaded, so they have to perform the Matching of the transaction between source and target and identifying the expenses and finally they prepare the reports. This is so time consuming because most of the process is manual and even though they use tools, those were not integrated properly. So this can lead to delays in. Closing the financial periods many times. Second thing human errors as we all do mistake at times. So manual intervention always increases the problem of errors. such as like when you're adding some data. You do some mistakes and we miss some transactions and then sometimes we perform the matching incorrectly and then we may miss loading some data. So whenever we do this can result in delaying the process, this and all human address. And this can even potentially Go into inaccurate financial statements. The third one is disjointed systems. So when we say disjointed systems So this legacy systems, will have there'll be multiple systems. You have to integrate the systems We can't integrate systems completely front to back end to end the reason is Each system will have different software different product. Okay different external vendors like Some people use this accounting software, custodian services, banking systems. So these kinds of fragmentation makes it difficult to, get them into sync. Which leads to most of the problems next delayed information. So most of the legacy systems reconciliation systems Typically rely on batch updates. So which means they don't process the data on real time So they process the data on batches. They are they upload the data. So which means If user wanted to perform the reconciliation, it will not be real time most of the times. So we can't perform the decision making on the fly due to this outdated and incomplete information. And, the other point is difficulty in audits. So with all these problems, and then, we don't have a proper end to end integrated systems, and there are many manual and, it's. So we can't audit each and every step due to many manual interventions, human errors, and then disjointed systems. So auditing the reconciliation process becomes so cumbersome, which it didn't increase the time and cost to complete the audit. These are the few challenges with traditional reconciliation systems. Now let's go into the features of cloud based reconciliation system. So first one is automated data matching. So when we say automated data matching, so we can design the cloud based platforms to automate each and every process of matching the transactions from Multiple sources like sources can be banks, counter parties, custodians and trading platforms. The system compares the internal records with external records. So pre cancellation always performs between two systems and, it automatically flags if there are any discrepancies for the user to review. once this is automated, the data matching, so most of the problem will be solved. the second point is real time data synchronization. With our new cloud evolving technology, the data to be synced and updated in real time. So this means that as and when the transaction occurs, as and when user posts something, there is, we can do the reconciliation immediately. And, it can even speed up the reconciliation process completely as we don't have to wait for anything. As the system is system and data is synchronized all the time. And the third point is integration of multiple systems. So this is the key feature where these platforms can seamlessly integrate with the various internal and external systems. Any source system, accounting system, custodian system. So if it is in cloud, if you configure properly, so the things will be as quick as possible and which will help us break down the data silos and provide a unified view of financial transactions. and final thing is like reporting once we perform the reconciliation, obviously, we have to create the reports. the cloud based systems typically have powerful reporting and analytic capabilities. these tools allow firms to generate, The comprehensive reports on the reconciliation process and highlight the issues in real time are very quickly. Reports can be customized as user require, needs and they can be exported to other systems shared with stakeholders and shared to different, shared in multiple formats. Everything can be done in a single click. So once the report is unleashed, and then the next thing is audit trials and compliances. So the most difficult part, is audit trials and compliance. So that too, for the financial institution, maintaining accurate records for regulatory reporting is very crucial. So this cloud system maintains the detailed audit trails of all reconciliation activities like Who made the changes? When it was done? How it was done? If something is broken, how is it broken? All this will be properly audited in the cloud based systems. This ensures complete transparency and makes the process of auditing. More straightforward. and machine learning and a integration, which is a key concept in any of the cloud stuff. So some of the advanced cloud based reconstruction tools in cloud incorporate machine learning and a. These technologies can predict and automatically resolve the discrepancies based on historical patterns, reducing human interventions, and speeding up the process further because it takes care of everything. Those are the key features. Let's come to the benefits of cloud based reconciliation with the features which we have. First, increased efficiency. So automating this. Manual tasks like ingestion, data matching, exception handling, generating the reports and audit trials, all this will be very quick. Now, this leads to a quicker close cycles and more timely decision making. and reduce risk of errors. So this old system, configure the system properly, you develop something, we produce it, this cloud platform automate much of the reconciliation process and reduce the manual entry. The chances of human errors and data mistakes are no more available except for the coding, of course, which means our manual errors are minimized more efficiently. And now, enhanced collaboration. Cloud platforms are accessible from anywhere within Internet connection, facilitating collaboration across multiple teams or even multiple regions and locations. This is especially useful for investment banks and financial firms with global operations across teams working remotely. Next, cost optimization. The time savings from cloud based reconciliation can translate into cost reductions, as expected. Organizations can report around 60 percent faster monthly end closures. So these month end reports, month end closures are very crucial for any financial form. And they even realize approximately 50 percent in the manual introversion reduce and the ability to reallocate 40 percent of their savings in resource allocations to improve the products even better. So now, next point is better complaints and transparency. This cloud based reconciliation systems are frequently updated to meet changing regulatory requirements. The built in audit trial features. For this cloud provides clear visibility into the reconstruction process making it easier to comply with all regulatory standards like GDPR and so on. And major, very great benefit is faster decision making. With faster reconstruction cycles and real time data updates, decision making is, decision making. Is very quick and this can rely on more accurate and up to date financial data. To inform business strategies now, let's think about the architecture of this reconciliation. So If you if we just think any of the reconciliation systems So data in this we need to perform the load loading of the data and then we have to build some reconciliation system and then we have to perform the Some tool to validate and then we have to see some reporting methodology It's like quite common, but when it comes to cloud based thing, the data engine, the system employs advanced APIs, excuse me, and connectors to ingest the data from multiple sources. That can include trade confirmations, settlement transactions. And, real time market fits. this features robust error handling and data buffering capabilities. which ensures during peak hours, we can queue the data than, breaking the system and go Oh, there's a huge data. Oh, I can't handle the data. Let's break it. let's ask users to push only little more data on a batch of dates. So we don't have to do all of this. So the cloud based systems can easily scale up and scale down if you architect it properly. That's the power of cloud based. And then once data is ingested, we have to build a reconciliation engine. So what does this do? That system can be a high performance matching engine. So where we can configure the rules and machine learning algorithms to perform multivariate reconciliation across So any kind of data sources. Advanced pattern recognition identifies complex expenses, while the intelligent AI handles routine matches, escalating only the exceptions that require human interventions. And user can comment, annotate however they want, they can make the changes, they can push the changes back to the system. So we can develop reconciliation in such a way that it's more powerful for Front and back validations So it's nothing but data processing and validation this sophisticated etl extract transform language So this is a normal etl system, but when it comes to cloud it is so powerful by using automated workflows, machine learning algorithms, which can detect any anomalies, built in validation rules, to ensure the data quality and completeness. and then issue resolution and reporting. An integrated workflow management system streamlines exception handling through automated routing and collaborative resolution tools. The reporting layer leverages Business intelligence capabilities to generate real time dashboards regulated reports and Predictive analytics that drives operational improvement. So which means there is a issue We can flag the issue and then send the issue to corresponding user on an email on Any kind of cloud based platform where we can quickly check and then perform the resolution accordingly. We can send the reports in cloud as much faster as we need. So that's the architecture now When we do the when we do some kind of case studies in the real world So so there are some invest bank Is investment banks. So when they use the cloud-based platform, for their reconciliation, they within six months, they achieved 60. 60, not 60. It's 70% reduction in manual processing errors, cutting reconciliation time from 44 hours to less than 45 minutes, and their accuracy rates sold to 99%. While reconciliation related operation cost decreased by 40%. So, more less operational cost, less manual effort, more speedy approach. So one of the company have evolved with that. So next, when it comes to hedge funds, so a 10 billion hedge fund revolutionized their portfolio reconciliation through cloud technology. The new system automatically resolves 92 percent of their position risk expenses. within minutes compared to hours when they do it perfectly or days if there are any mistakes. Real time monitoring now flags 90 percent of potential issues before they impact trading decisions. This dramatically strengthening their risk management framework. And, it is asset management company, which is like 50 billion asset manager. They streamlined the regulatory reporting through this cloud technology reconciliation, daily reporting cycle shortened from six hours to 90 minutes, while accuracy improved from 96 to 99. 8%. The company now handles three times the transaction volume. more than what they used to handle earlier with legacy applications. this is the scalability and it can go even 10 percent as 10 times as well. So this is the cloud based and then what is the future we can even think of using an artificial intelligence, what it will do. So next generation AI transforms the reconciliation through intelligent pattern because Transcribed Recognization and machine learning advanced algorithms automate the complex matching while real time anomaly detection prevents before they impact the operations. This reduces the manual intervention by up to 80%. Yes. When AI comes, any similar activities can be detected automatically and based on the historical data, it does, the pattern matching and it speeds up the process. And we can use blockchain technology. This distributed ledger technology, The reconciliation by creating a single source of truth, smart contracts, automated verification, while immutable audit trials, enhanced transparency and compliance. Virtually eliminating the data discrepancies between the parties. The third point is data analytics and visualization. Now, everything will be dashboards, reports, hit a single click of button. They can just move from one reconciliation to another reconciliation. The interactive visualization that highlights the trends and problems. And it can even show us the predictive models, forecast, potential issues, which can be used for proactive optimization of reconciliation workflows. So what are our key takeaways and our next steps? So I believe we need to implement the cloud based reconciliation solution to reduce all this manual efforts and, minimize the operation risk and reallocate the valuable resources to. Strategic initiatives than using spreadsheets comparing taking more time and second point is strengthen the risk management established. Robust data governance frameworks and automated validation process to ensure 99 percent of accuracy. This meets the regulatory requirements and builds stakeholder stress. Yes, as and when everything is automated and validated. The chances of risk will be quite less. And next drive innovation leadership. Deliveries AI powered analytical and blockchain technology to transform the reconciliation from back office function into a strategic advantage, delivering the real time insights and predictive capabilities. Yeah, it transforms everything. this is some, estimated changes of the cloud based reconciliation in investment banking operation. So it, as we talked, it reduces around 75 percent of manual effort and improved accuracy in their systems. And it lowered the cost, operating costs also. So it's all savings. And, more efficient, more savings, and, more scalable. And the conclusion, cloud based reconciliation applications have revolutionized investment banking operations, delivering up to 80 percent reduction in processing time, while ensuring unprecedented accuracy in financial data management. by leveraging intelligent automation and real time analytics, companies are not only streamlining their operation, but also uncovering valuable insights that drive the strategic decision making as the financial landscape continues to evolve. Organizations that go with these transformative solutions will be in a better position to scale efficiently by maintaining the regulatory compliance and, capture new opportunities. Very quickly in this competitive world, which will make their company growth go more success and scalable very quick as cloud based reconciliation systems can be scalable as easy as possible, as quick as possible. And thank you. First of all, I would like to thank you for giving me these opportunities. Thank you so much Con 42 for giving me this opportunity and thank you for listening to this great initiative. And I hope this gives you some kind of more insight on reconciliation processes by using cloud based systems. Thank you all. Have a wonderful day.