Drive Innovation in Digital Banking with Oracle Fusion Data Intelligence & AI

Immerse yourself in a delicious lunch, discover cutting-edge tech solutions, and engage in valuable networking opportunities with like-minded attendees in the Bank of the Future floor.

AI has the potential to redefine the Digital Banking space, discover how you can unleash the power of AI with Fusion Data Intelligence and accelerate this transformation. 


Transcription:

Tan Donu (00:11):

Good Afternoon everybody. I'm Tan Donu and I set some sales strategy for Oracle's financial service applications. This afternoon we're going to have Ben talk about how our data intelligence and data platform enables our customers to make smart business decision, and it's going to play up from a little bit from those that we're here this morning around how are we using the AI platform, right? Our tech Oracle's technology that we built from the ground up to enable this data analytics to help you make these intelligent decisions about your business in the future of your business. So with that, I'll turn it over to Ben. Thanks.

Benjamin Arnulf (00:55):

Thank you Tom. Hi everyone. So today we are going to look at drive innovation in digital banking with Oracle Fusion data intelligence and AI. So just the safe of Oracle to start, and then my name is Ben. I'm Senior Director of Product Strategy for Oracle Analytics. I'm going to speak a little bit about Oracle analytics, fusion data intelligence, machine learning, AI, our ecosystem and more. So first I wanted to show you what are our platform and application. So at the bottom you can see analytic platform. We have Oracle Analytic Cloud, it's our flagship platform. I will say most of Fortune 500 companies are using Oracle Analytic. We have also Oracle Analytics server, which is for the companies using their own server or their own data center, most likely, sometimes the banks, sometimes government. And then at the top we have Fusion data intelligence. This is for our customer that are already using Fusion, ERP, fusion, HCM, CX and SCM, and then NetSuite Analytics.

(02:14):

One of the big news it's today we just heard that we became a leader with Gartner. So we are leader beside Power BI and Tableau. So it has been a very good news because we were visionary in the past and now we are moving to the leader quadrant, but in the past we have been also leader with Forrester, leader with Nucleus research leader with IDC leader with vent research and leader with Bark. Bark it's more in Europe. So all this analyst film put Oracle Analytic as a leader in the industry. I'm going to move to the next slide to show you also what is Oracle Analytic because maybe some of you are not aware. So Oracle Analytic is not just a data visualization tool. We do augmented analytic data preparation, data flow. We do data modeling, data visualization, auto ml, AI, natural language generation, natural long edge processing. We do auto insight, one click to do forecast, one click to cluster, one click to outlier. And the beauty of the tool, it's that it's self patching, self upgrading, selfe securing. So you don't need to have an army of IT people to do that. We do that for you.

Tan Donu (03:39):

So this morning we had some questions about how do we trust your data? So we're giving you here a platform to make sure that you can trust your data that you're going to use in your AI models, right? Because the data secured within Oracle, right? We're preparing the data for use. So this is going to greatly assist all the folks that are looking to use large data models with AI.

Benjamin Arnulf (04:06):

Also, I speak to a lot of customer every day. So they are always asking me how do I go from reporting to self-service BI to augmented analytic, and ultimately to decision intelligence? How do I look at my dashboard and I take immediate decision? So I speak to probably 500 customers per year. You have to know that a lot of them are still stuck between reporting self-service bi, looking at all their dashboard with only private table. And when I ask them, what do you do with this dashboard? They tell me, I'm just looking at my data. But when I ask what type of decision you take based on that, they don't really know. So our goal at Oracle, it's really to help with augmented analytics and with decision intelligence. So we take your data, we analyze your data, we take for example one of your table and we build for you automatically 100 data visual utilization, so you don't have to do anything. We use also natural long generation to explain the data for you so you don't have to ask a business analyst to do it for you

Tan Donu (05:19):

In financial services in begging, this is so important, right? When you think at the speeds that you have to make decisions and you look at things in the past like Silicon Valley Bank, right? If they had something like this, they would've known immediately their balance sheet was upside down in no time and there would've been alerts going off across the bank. So the speed that this tool can help you make these predictive analytics is just super impressive.

Benjamin Arnulf (05:46):

Some of our top global customer run on Oracle Analytics. So you have H-S-B-C-B-N-P, Paraba Vanguard with from Vanguard, just spoke for Oracle Analytic at the Gartner Data and Analytics Summit in Orlando, I think it was two months ago. Nationwide, American Express, Citadel, Emerson and so on. I'm not going to go through all of them, but as I told you, I'm speaking to each of them every day. So you can see serial from Delta Airline, we have people from ar, people from the Nazar, we have people from PayPal and so on and so on. Dropbox, MetLife, nationwide Insurance, USSA and so on. So every day I'm speaking with them to understand what they want from their data, what they want in term of feature around machine learning, drag and drop AI and more. They all ask something in common. It's to simplify analytics for them. So being able to do things by drag and drop, not having to call a data scientist, a business analyst to get the result, just being able to have their own tool and do it themself.

(07:02):

So our product strategy, it's really to simplify, to unify our ecosystem and to add some AI to simplify everything. The big difference with a tool like Tableau for example, or ThoughtSpot or over type of analytic platform is that we have an entire ecosystem working together. So we have Oracle database, we have Oracle Cloud, Oracle infrastructure running with Nvidia, we have Oracle AI services and so on. I'm going to show that right after. But you have to know that we have all our services in our cloud so we don't have to use different ones. So Oracle bring AI to the SaaS application, bring AI to the data, the infrastructure, and to the partners. We have also generative AI inside our Fusion ERP fusion, HCM, CX SCM, and we use generative AI for example, for management reporting, narrative, financial reporting, narrative journal entry, reconciliation notes, financial data explanation. We use also for HCM, for the job description for requisition with SCM for assisted ordering or with summarization. So we put that at the source application and automatically you can use it. So we do all the work for you at the application level.

(08:38):

In term of generative AI, you have to know that we have now RAG and we are going to launch the rag agent. It's going to be all through 2024. So it's part of our roadmap and you will see more and more coming like SQL agent better and more. I'm going to show you a demo. I know you always want to see quickly the platform. So really quick, I'm not going to do an entire demo of the platform, but just how we use generative AI and large long edge model inside Oracle Analytics. So I'm going to not speak for that, but you are going to see this is Oracle Analytic. When you open a workbook at the left, you have your data source. You could have like 10, 20, 50 data sources from Redshift, Amazon, Google. You could have SAP, anything you want or rest API data sources or Excel file. And then in the middle it's where you create your database utilization by op. But imagine you are a customer you don't necessarily want to start to create by yourself. You

Video Presentation 1 (09:51):

Can ask question is the ability to interact with the Oracle analytics assistant to explore my data and create content? My first question relates to my topic. However, my catalog has no data to address it. Oracle Analytics will choose a general model such as cohere or ChatGPT to answer the question while indicating that the answer came from a public model. My follow-up question is slightly more complex as it relates to the previous response combined with the curated data that I have here, the assistant will combine the two using our internal analytics AI model, optimize for data computation and quality. I can use quick modifiers to enhance my question and when I find something interesting, I can add the resulting insight onto my canvas using the assistant. I can create new calculations by describing what I need and I can use these calculations and follow up questions.

(10:43):

The key is that the assistant is not the experience. It is interlaced into my experience and I can use it for some tasks and still choose to do other tasks myself. For example, I can still manually create insights and use them in synergy with chat. Clicking on the chat icon on any visualization allows me to get more insights and modify it using chat. Once my content is ready, I can share it with others while they can consume it as a dashboard. I can also use tools like synthesia to create visual newscasts to tell my data story.

Video Presentation 2 (11:16):

Welcome to your Oracle Analytics update As of May 23rd, 2023. Today we will examine climate change and the impact of flooding. Let's start by looking at countries with major investments in flood prevention. Among the four countries with the biggest flood prevention projects, the Netherlands has the biggest problem.

Benjamin Arnulf (11:38):

So we use generative AI, large language model, we use AI avatar. If you need to make the data speaking for you what you have to know in our roadmap, we are going to allow you to bring your own key. So if you are using for example, ChatGPT co or cloud or any other type of large long edge model, you will be able to bring your key and automatically use their specific large long edge model inside Oracle Analytic. I'm going to speak about our ecosystem. So again, our foundational infrastructure. At the bottom you can see that we are using Nvidia, we are using any type of infrastructure in our cloud. Then you have ML for data platform inside Oracle Cloud where you have Oracle database, vector search, autonomous database where you have now ai, which is inside the database, MySQL E wave, which is super fast.

(12:40):

We have data science, you have data labeling, data catalog, and more analytics services. It's where you have Oracle analytic or Fusion data intelligence. We have smart data preparation, we have data enrichment, explainable ai, auto Insight, auto insight. It's really an engine where you just drag and drop your Excel file, drag and drop your table and automatically Oracle is building 100 data visualization for you. And then you can tweak, you can say, Hey, look a little bit more at the mortgage level or look about my employees or my location, and then you fine tune how you want the engine to create data visualization for you. And it take usually eight to nine seconds to generate this 50 to 100 data visualization. So you don't have to spend time analyzing the data. Oracle do it for you. We have a gene AI assistant that I just demoed. And then at the top you have AI services, the new one or gene AI gene AI agent to automate your process. We have also digital assistant speech. We have language vision for object detection and document understanding. You can use all these AI services directly into your application at the top. So again, the power of Oracle is that we have an entire ecosystem in the cloud that you can use.

(14:11):

Also, how do you build modern data platform? So a lot of people ask us the same question, what are doing Vanguard? What is doing TD Bank? What are doing other than others? So here it's a summary of what all over are doing. You can see at the left they have their different application. At the top they have their ERP, they have their supply chain application, industry application banking, application, HCM and so on. They have their development application on the top right, they ingest all the data using Kafka, using Informatica, using OCI integration services. They load all this data into their data lake or data warehouse or they use, for example, our data catalog, data flow, big data services, and finally they plug their analytic platform or real time analytic platform with Oracle Cloud. And you are going to be a surprised because I put Power BI and Tableau.

(15:13):

Why? Because they are also leader with Gartner and every time I contact one of our top customer, they always use multiple type of analytic platform and it's okay, you are never going to see any of them using only one. If it's the case, they are in advance, but they always use Oracle Analytic with Power BI specifically, they use Oracle Analytic cloud for backend reporting back office. They use for Finance, HR, Supply Chain, Procurement and more. Every time it's about, I will say sales or pricing or something different, they will use Power BI or sometime Tableau. What we can see is that more and more are using the Microsoft Oracle type of platform where Tableau start to become a little bit expensive for some of them, not for the biggest customer, but some of them they cannot continue to explain how they spend a million dollar per year for Tableau while they could spend something like 100 K for Oracle A or Power bi.

(16:24):

So we see a trend at this level and then you have also your machine learning and vision, speech language on the side. So this is a typical modern data platform. What Oracle is doing, it's easy also, we try to consolidate the experience of all the users so they can connect, they can prepare, they can model the data automatically in Oracle Analytic. They can explore, share and consume. So again, they can do live connection to all data sources to Google, to Dropbox, to anything you need. They do query federation in memory acceleration, secure remote access, ml, AI platform. You can do data virtualization, semantic model data flow to transform your data and more and then explore your data on workbook, on dashboard, on mobile, on report and more. And finally share your data and consume your data into podcast through API through mobile and more. We have a very cool app where if you look at your data on our iPhone app for example, you can ask for a podcast of it. So imagine you are in your car, in the plane, you just press play and the car will speak for you and tell you exactly what's going on.

(17:57):

Fusion data intelligence, we have a majority of customer that tell us we don't want to spend time on maintenance. We don't want to spend time with our IT team looking at the data, looking at the governance, looking at managing the dashboard and everything. We want Oracle to do that for us. So it's what we did. If you are a customer with Oracle Fusion, Oracle NetSuite, Oracle Health, Oracle Industries or some third party data, Oracle will manage the data pipeline for you. So you don't have to use your ETL like Informatica or anything. Oracle will manage all the load of your data. Oracle will load this data into a data lake or an autonomous database for you. We will manage the database and the lake for you. We are building the data model for you. We are pre-building all the KPI for you, so you don't have anything to do.

(19:01):

And finally, we also build the dashboard for you and we run all of that for you with Oracle Analytic and we plug AI and ML on top of it. So basically we manage the entire stack from your data to loading the data, modeling your data and bringing the analytic for you so you don't have to call your IT all the time, your business analyst, your data scientist and so on. Fusion data intelligence is going very fast. Since we released that, it was two years maybe ago or three years ago, we have now 1000 customer and some of the biggest customer in the industry. We manage half a million of tables. We have 4,000 prebuilt metric and 250 prebuilt subject area. A subject area could be accounting, generally procurement, talent analytics. It could be purchase order, it could be anything, account analysis and more what we offer to you.

(20:06):

It's also prebuilt dimension, prebuilt fact, prebuilt hierarchies. So you don't have to refine that. And of course we provide all the KPI for you like general ledger or revenue, K-P-I-E-B-D-A, AR D-S-O-D-P-O and more. So we do already the definition for you of all these KPI and you are going to use the same one as HSBC, the same one as any other companies. Using that, you can tweak the definition, but if you decide to use the same as all the other industry, all the other customers, you don't have to think about anything else. And then in the future we are going to allow you to benchmark anonymously using ai. We will say, okay, what's your cost of your FTE for, I don't know, for your payroll? And we will say you are 20% up compared to the same industry and same size of customer that are 10 billion revenue per year.

(21:10):

So that it's really the power of fusion data intelligence. Also, we are building intelligent application on top of that. So we bring your data, we do the data model, we do analytic, but now we are going to do ML on top of it, UI and workflow. You will have for example, dynamic sales forecasting where we will do the scenario modeling and adjustment for you. We are going to build some AI application on top of that for you. Some of the thing we are already releasing, collection risk prediction on time payment risk prediction. We are working on spend classification expense, anomaly detection. We are working on diversity analysis, sales forecasting, pricing optimization. So every quarter you will see some new ML AI application built for you and you will be able to use them to see anomaly detection, to see unfair skills and more. We speak to customer every day and every day they ask us for more of this AI ML application so they don't have to build them inside their company. So we have customer advisory board where we review that with them and we continue to put into our queue of development new model. So you are going to see all of that coming. It's best in class in the industry and you are not alone to build that. Everybody's going to use the same like Vanguard and others.

Tan Donu (22:45):

And these are small models built within our applications that are using your data to learn, right? So we're not going externally to use some large model that might bring back some of these bad results. You hear about it's learning off of your data itself,

Benjamin Arnulf (23:01):

Correct? We offer also prebuilt financial analytic data visualization and dashboard. So to analyze your working capital, we use prebuilt KPI to do that, to analyze your profitability and cost, your operational efficiency and more. We do the same for procurement analytic to analyze the spend to enhance your source, to pay efficiency, minimize supplier risk. And again, you have all the set of KPI that you can use for that. And again, it's totally prebuilt so you don't have to do anything. You have also project analytics. You can see your portfolio health monitor variances integrate with HR and supply chain. And we have a lot of question usually from customer asking, is it just for record or can I bring data from Salesforce data from third party? And is yes, you can bring data from third party, mix that with your own data model and automatically use the same prebuilt KPI. The beauty of a tool again is that you don't need an army of IT people. We do that for you. You have zero downtime, so it's a very, very big thing to refresh your data upgrade if you have some upgrade of application. We have also nightly refresh. Some of customer that are smaller than others, sometime they ask for multiple refresh per day or by morning or more

(24:39):

With fusion analytic, you have full security. And I will not lie, it's why most of customers are using Oracle. It's because they know in term of security for financial, for HCM supply chain, it's very, very strong. We are automating all our cloud, all our security. So you have limited interaction of IT people and basically automatically we are fixing all the patch, doing all the security work for you. We have single sign-on integrated with your data and integrated with your application. You have also data security synchronization between application.

(25:23):

Okay, some of the capabilities. So you can see a little bit about the platform. Again, you can connect to all your Oracle sas. You have direct connectivity to Oracle database. You have direct connected to different data store OCI data store. You can also connect to SQL server from Microsoft and more you can connect with JDBC driver, so you can connect to your on-prem database to your legacy system. You have also direct connectivity to Salesforce, rest API, an example of rest API. It's what you see on the right side. I created for example, a workbook which is going to retrieve information from Bloomberg on the S&P 500 and showing in real time what is the daily change for the S&P 500 stock. You are going also to have the ability to connect to Dropbox, Google on-prem database. And finally you have remote sources, remote gateway, so you can create your own tunnel to query your data sources. So again, we work with everything, Amazon Doo, MongoDB, all the different data sources

(26:43):

You have self-service analytic and statistics. What we like is that we have more than 50 data visualization types. So if you look at Oracle Analytic five years ago we were really at the same level as Tableau in terms of data visualization type. As of today, June, we are at more than 60 now. Data visualization type from Santi clustering, you have tree map, you have maps, you have anything you need. So we continue to add more and more on our roadmap customer ask us to bring the Gant chart, gauge chart, they ask us to bring the org chart. So every quarter you are going to see more and more data visualization types that you can use and we are one of the best in the industry. You have custom calculation, KPI card, what if scenario, which is really cool. One click to do prediction forecast, cluster outlier trend.

(27:48):

We use seasonal ARIMA for forecasting. ETS, you don't have to do anything. You just take your data, you right click, you say forecast for me and it'll use this type of algorithm for you. We also have a way to explain your data. You can right click on attrition cells, any type of data and Oracle will explain for you what are the key driver, the segmentation and more. For example, for the segmentation of data, it's real time. We recruited a lot of different data scientists to create this model. We put it inside the Oracle and in one click you can say, okay, for this 1 billion lines or on this table, tell me the segmentation and it'll tell you 5% of the data show you customer from this company or another one automated inside that it's probably the preferred feature of all our customer. You drag and drop a table, you drag and drop an Excel file.

(28:54):

You don't have time to look at it or analyze. And at the right Oracle is going to look at all the different data visualization possible for you. Chart 80 20 analysis, indexing analysis. Not only we create the data visualization but also the calculation for you and some very interesting calculation or we forecast the data for you. I think next quarter we are going to release contextual insight where you will see for example, that one of your branch at the bank is not having a lot of asset under management or not having a lot of loan for a specific month. You will be able to right click and say, explain me why it's happening and it'll do all this data visualization for you, but in context of your data. So it's something that has been requested by ton of customer. We do data preparation. Again, we don't want your users to go to Excel and I will paraphrase Marriott, Marriott International, they told me we want to kill Excel at Marriott, we don't want people to do anything in Excel.

(30:08):

So they use that to just go drag and drop, filter the data, aggregate, join the data, clean the data and so on. And when you have PWC or ENY coming to do an audit, you just show that and you see this is how we transform the data. So they don't have to say, Hey, look at our 100 data sheet or Excel file that Terry used like two months ago and where is Terry? Oh, she left the company and I know that PWCA few years ago did a huge audit and they saw that bottom line, 80% of Excel file have some issues in the cell in the calculation. So we don't want that anymore, but still good luck. We have also anomaly detection. We do intelligent recommendation. So if you drag and drop a table or an Excel file and we recognize customer social security number or credit card number, automatically at the right you will have an algorithm telling you click to mask the social security number, click to mask the first, I don't know, 10 digit of a credit card number and in one click you do it and it'll do the modification and hide that for you.

(31:26):

We have also a drag and drop way to do security in Oracle. You could go to this data set and say, I just want the VP of Florida to be able to see the salary of Florida branches or I just want this or that. So data level security by drag and drop, very easy to do. We have one of the best in class data modelization tool inside Oracle Analytic. You can do star schema. It's using GitHub, so you could have multiple developer doing that. They can see also the data source, what type of transformation you did and what is your presentation layer so they can see the data lineage of everything you have been doing here. It's using SMML, which is semantic model market blockage, and again, it's the best in class in the industry. Okay, machine.

Tan Donu (32:26):

So imagine when you order a walked in and said, well, how did you arrive at that number? And you can show them that drill back, right? That's just amazing.

Benjamin Arnulf (32:34):

Correct? We have a lot of different ML and AI capabilities inside Oracle Analytic. I'm not going to go through all of them, but you have ai, augmented experience at the top. It's really for your users, for your consumers. They go into the dashboard, they go into a workbook automatically, they have targeted segmentation, one click in context, ml and so on. Then you have ML user friendly where they can do drag and drop auto ml, drag and drop machine learning. You don't have to be like fur use in Python or art to do that. You can do that by drag and drop model quality, explainability and more. And then for data scientists or people that know how to use our Python or the cloud services, you can do document key value extraction. You can do special and network graph, sentiment analysis, classification, PII, object detection, face recognition and more.

(33:40):

One of the best use case that we know is that one, you can go select a machine learning model and say, I want to forecast attrition, I want to forecast the cells. You just tell our machine learning prebuilt model what you want to do. You can tweak few parameter of the model and Oracle Analytic is going to build the machine learning model for you. Indeed, really one hour you know how to do that and you can start to use that to forecast, do linear aggression neural network, CRT and more. To give you an example, Andre at HSBC in uk, he created a machine learning model to forecast the duplicate invoices because HSBC saw that every month they were paying, they were doing duplicate payment for duplicate invoices and they wanted to stop that. So they use this type of machine learning model by drag and drop every month to understand what are the duplicate invoice keys, forecast that and not pay them duplicate every time.

(34:49):

We have also over customer using this drag and drop model to forecast attrition and other things. We have over type of AI vision, AI object detection, image classification, long age AI document AI. So you can do everything by drag and drop. An example here it takes classification with ai, you can definitely use your table, your data detect automatically what is personal identification data and ask Oracle AI to mask it for you. So you don't have to do that. You can analyze with ai, the customer feedback. You can do also all type of analysis using text classification, sentiment analysis, name entity recognition.

(35:42):

We are doing also AI vision and image classification. I know for the bank it's a little bit less useful, but here it's an example of what I built using 3000 brain MRI. So I use this type of picture to basically label them and tell if it's a men angio tumor, pary tumor and more, then we load 300 different over MRI and automatically it's going to recognize with our model what type of tumor it is. But you could use that for anything you want. You can recognize any type of picture, any type of document. We have also AI document understanding. Some of the bank are using that. Some of customers start to use it at the government level. At the defense level, I created fake passport to test that of my team. I put their passport. It's recognizing automatically that it's a passport, extracting the data from the passport and then put that into a dataset. You can use this dataset with your database to understand what are the passport that are expired or fake passport or people that are banned from your branch or from your bank automatically. You can use also to recognize invoices received driver license on the go. So you can literally just do a picture and automatically use that to recognize in once second what you want. So you have a lot of different use cases.

Tan Donu (37:19):

Think how beneficial this would be with know your customer, right? We all have faced with the AI ML, and this is a great example of how we can identify who the customer actually is.

Benjamin Arnulf (37:32):

It's recognizing re resume and a different type of document and we are going to add more and more recognition. You can create your custom document classification. So you could say every month my statement is looking like that. At the top I have this, I have this or check from my bank is looking like that and automatically you use it. Gen AI, I show you a demo, we are doubling on it. We are going to add more and more feature on that. So it's really going fast. You will see a lot of improvement. We have an entire team dedicated to that and it's going really fast. Also, what you have to know is that every two months I will say we are updating our design. So the Oracle Redwood design got a lot of different award and every other month we are adding different element in this design. So you are going to see the interface of Oracle Analytic, I will say being enhanced every other move our mobile app. You don't have to rebuild your dashboard to use the app. When you create a dashboard, automatically the dashboard is converted to an app format and you can scroll like this or remove the visualization. You don't want to see. You can also open any dashboard in the correct format from your app and say, show me how I see it on my screen, or show me just an app card type like that.

(39:06):

Finally, to finish, I'm going to show you the art of possible what you can do with Oracle Analytics. So this is the type of data visualization you can do. I think that I created it one year ago. The stock was at one 15. Now we are a little bit more at one 50 or one 40, but this is the type of data visualization you can create with logo picture. And this is a real time API doing the trend. This is S&P 500 daily change where you can see how any stock is moving during the day, every second, every mid second. It could be coming from your data or anything else. If you want to do more infographic vc. For example, the United Nation World Food Program where we look at the increase in term of price for the rice, the sugar, the wheat. You can see at the bottom right, we use the one click forecast to forecast the price of a different commodities that it's just what we created few months ago with, for example, the passport of Alex. You can see that the passport expires status pass that it's a calculation that I created manually by Dragon Drop. But you can link that directly to your dataset, to your knowledge database and do anything you want with one picture of any document using AI.

(40:37):

Our partnership with Red Bull. So again, when we have a simulator, we are using also an Oracle analytic dashboard to analyze all the data from the simulator. You might have seen Max Vertap using the simulator. And also you need to know that Oracle cloud is used by Red Bull to run like million of simulation every second. So every second max VER in Formula one is doing something. We calculate a million of different simulation and forecast on how it's going to finish the raise

(41:16):

That it's one of the most recent dashboard that we use. We use some data from finance data from HCM hr. We look for example at a leader of approval score. We look at three different direct report from this leader, what are their base pay salary since 2020? And then you have some AI recommendation telling you what's the skills based on the skills and the base pay, what we should do, and then it's detecting that you have some payroll costs with some open requisition and telling you that it might have an opportunity to move some requisition from California to Texas to reduce the cost and more. So if you want more information, I'm here to speak or you can go on YouTube. We have different blog. We have a community website, an ID lab. If you have some feature request, you can scan the QR code or we can take maybe some question. If you have any question,

Tan Donu (42:21):

Any questions, don't be shy. We'll be out on the floor too. So both the technology team talking about the AI capabilities of the platform, Eric and Megan and myself will be out on the floor that you can talk to us about the Oracle analytics, but love to hear more from you.

Audience Member 1 (42:44):

So this strikes me that the ETL products are going to go out of business. Is that the future?

Tan Donu (42:50):

We hope so.

Benjamin Arnulf (42:52):

Yeah, we hope. But it's the trend that we see with all our customers. They don't want to manage their ETL and they don't want every time you upgrade an application, your ERP or your HCM to have to redo all the ETL mapping and everything. So I'm not sure it's going to go out of business, but at least they ask Oracle. Oracle to manage it. They don't want to have to deal with it anymore. But good question. Yeah, very good question. Perfect. Thank you.

Tan Donu (43:26):

Thank you. Enjoy the rest of the conference.

(43:28):

Thank you.