Fifty Percent, Two Thousand, Twenty Five Percent discussed on AI in Business

AI in Business


To get started. This episode is sponsored by easy. Op if you're interested in reaching emerges on go to e. m. e. r. j. dot com slash a. d. one that's eighty like add and then the number one m. e. r. j. dot com slash eighty-one and learn more about our creative services. What it is we offer in terms of content and reach and also how brands work with emerged. They want to learn more about that process. Yemi rj dot com slash. Eight one without further ado. This is emanuel decio easy. Opt here on the business. Podcast so emmanuel. I know we're going to be focused on some unique use cases in the financial services face in terms of where a i is starting to find its fit and add value or to talk first about the business units that you tend to work most closely with which again are somewhat unique. We cover a lot of different areas of banking but you guys hang out around the risk and compliance world as low as the finance and controlling world. I imagined kovic is change a lot of things for these folks the banking ecosystem insurance ecosystem or undergoing a lot of change. What do you see as some of those big kind of structural shifts that are changing and imposing new demands on on those business leaders. Well thanks well. It's a it's a great question so we have been working at easy up with at twenty five now tijuana large fashion institutions both in in europe. And the us. It's true that these guys are always intrigued by You know i could help us on so you know. I've been doing this project. Are you know. A lot of them are in production and pretty happy. Now with could be done. you'll think did accelerate. I think these guys are under massive pressure. You know they have given you know. Unprecedented amount of loan to help the economy a dramatic way. I mean they have. They have to be super giant. You know the certa tastes pretty high so they clearly have a lot of customers asking me. Okay how do you know how i could help me. I've let my team. How can i do more with the team. Have and you know. Could we be way more. If he shouldn't have to jail did a prediction that twenty five percent. You know of any companies with adopts on form of language a in g union natural language generation by twenty twenty two. We plan to double our install base this year so we actually way way way bigger. Yeah two things. I think some of the benefit of these kinds of applications that we're going to get into use cases in a moment is that there are some sorts of ai. Applications that require. I think a lot more data infrastructure overhauling than some of the stuff where we can kind of take what exists so we can actually just make it more simple. It's it's a little bit. More of a a circus. Accessible application of ai i take the jackhammer to the data. Infra overhaul what we're doing and by the way there's a place for that i think banks are going to have to evolve in a bigger way than surface but some of the accessible stuff right away. I think really great opportunities for you. These increased demands. Is it just due to. How much has changed about what they're reporting on is due to how many loans they have now out in the world. How much risk they have to manage. What are the things that covance brought onto them. That's made them forced to be more agile. Course being forced to work digitally. I think is probably part of it or do you see those being forces pressure from while you know. These guys have pressure from Everywhere yeah poor. Poor regulation england that now got into customers. Yup and because some say you know you need to help us to really get more data much more. Precise is more timely. And so on the buses who wants as well. You know what he's going to have any surprise this month. There's going to be you know a big change in your lab thomas shoulders. Y'all got the complaints. You know the governments you know. Compliance is is super era is not going to be lighter in the coming you know in the company and the sometimes you know. These guys are talking about finance but even risk organization. You know they would love to become way more business organizations of course they can you know. Have the right data in your get things straight and i think they are very good at that but helped transform these huge that They have on hand how to use that to make a better business. How to debuts intial customers to actually drive their business more efficient way. This is super so lots of pressure from all directions. It sounds like a little bit. Glad i'm not in that business but obviously it's very important. Facet of the financial services world is make sure our reporting is working when we get the insights. We need to move on make smarter decisions so we can talk about some of those decisions. One category that. I know we wanted to dive into here. Was looking at risk reporting specifically around of credit risk tons to think about you know so many more loans out there in the world walk us through a little bit of kind of what the business workflow is in where is starting to find. Its fit into that particular workflow. Yeah that's To use case which is getting more and more popular so just before. I stopped what we do in a nutshell. We do transform based on algorithms And the i. We do transform data into narrative that anybody can understand the letter in this type of ad. Kimmy trying to transform that. I in so the credit crate-raised departments for retail culprits institutions. You know these are huge departments within the banks of course and the year every time you do what you have to grant a new loan and then afterwards every year have to reassess the risk based on the data fashion statements to the customer based on the cash flow based junior all type of financial information. They have to reassessment and so that they can. You know do some direct provision and so on. so where are we jump in. We say guys you know we can help you to actually do sixty to seventy percent of this reports medical. We will produce a draft for the enemies so that all the section which are data driven will be actually drafted by the machine and the ice can actually dialogue with the machine. Say okay guys. Thank you for these highlights and you know this paragraph now a little more detail so yeah got slider you know and these interface and against say okay. I so to the machine was good morning until i want less detail at the east. You know dialogue. Who is a machine and makes the report the way it wants. The report look like super efficient. You know have been deployed that three four banks. Now they are one of the banks you know. They told us well. We cut the amount of time to do this report by half so it's a fifty percent efficiency gain. Which is you know. Pretty nice super high volume you the typically you have got two thousand two thousand five thousand and that is involved you know and you have to do in corporate banking you can. Do you know small and bean sized business you can do. So it's you know super away again the volume of our super high so the arrow i on this type of solution. Are you know in millions of dollars a year. and so. I want to talk a little bit. We'll go a little bit more into the nitty gritty of the reporting in the use case itself. In just a second. But i want to kind of pull up to the business value side of things. Obviously you folks have experienced deploying these so i think there's lessons learned here you. You mentioned saving fifty percent on what it takes to do this report. I think maybe not everybody listening in will understand how much has to go into news reports together. Maybe if we could if you wouldn't mind painting a bit of a picture of i need a certain kind of report on my small business loans in the state of the risk profile of my small business loans.

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