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I'm going to talk a little bit about the uh kind of the past present and the future of document Automation and then I've got some distinguished guests here from from our customers and our partners they're going to talk about their journey in Automation and how they've leveraged our platform to not only automate documents but automate end-to-end business processes so let's start at the beginning if you look at the history of intelligent document processing it really started in the scanning world you know I personally in 2005 was an I.T administrator for a mail room where we focus mostly on scanning paper and converting that paper into electronic files so that you could go find those in Enterprise content management system and then a big part of that project was zotal OCR right everyone's favorite word right templates and really that was all about you know just getting those keywords so you can go find those in that Enterprise content management system and then the kind of mid-2000s a little bit later in in the 2000s we started to see the emergence of what we consider today as intelligent document processing which really is the ability to extract information from documents that are semi-structured unstructured without templates right so this technology has been around for you know a fairly long time now and if you look at the different capabilities right a lot of buzzwords here a lot of terms and I kind of put them into two different categories the first is is rules based which are typical things like Zone OCR and instructions you know key value pair matching things like that and then you have a lot of AI right that we always talk about especially when it comes to documents so layout classification I mean I'm sorry machine learning computer vision natural language processing things like that and you'll see in the market today right there are tools that can address all these documents that you see correspondence you know emails any type of contract as well as fixed forms but one of the challenges that you'll see is a lot of tools today are kind of stuck in that paper world right if you think about it they all started as tools to help organizations convert paper into digital content and then over time they advance to add on more and more of these capabilities with zonal extraction then semi-structured extraction and then finally free form extraction but the applications themselves right architecturally are made to process information in large batches which is not a bad thing right if you've got a mail room you've got a shared service center you know these tools are really great but if you look at how most business operates today it's really about the transactions right I want to be able to process a document as soon as it comes in my organization whether it be an email and an attachment or you know a customer in my store and I need to capture some information from them so this batch Focus really doesn't fit that model right because you're either having to capture information up front in the as part of the business process and then send it off to another system for the actual workflow to occur or you captured at the end for archival purposes it typically is a very linear you know type of process and it's usually not very flexible right you can't make a lot of decisions about what to do with those documents it's really hey I've got this siled solution that has this linear workflow and I'm going to process and information through that workflow at the same time these Solutions being large Enterprise applications they're typically take a long time to configure right uh you know large-scale Enterprise IDP project will take three six months maybe even longer and a lot of that is due to just again how they're configured and how they're set up so when we look at this space in general and you guys have seen you know some of this in the Keynotes with document automation we believe the future is real-time document automation right so the ability to process these documents in real time as they come into your organization and to be able to do that that's really leveraging our entire platform right if you look at our automation success platform and the different capabilities in that architecture slide that we'll see here in a moment it really is a component right and the idea is that in this case document automation is built directly into the platform as a component of the platform as opposed to a separate solution so what that's going to allow you to do is basically ingest or inject document extraction directly into your business processes and that real-time document you know ingestion piece really is you know using RPA right to to pull that information in but there are some key capabilities I want to highlight here around document automation you know what I mentioned earlier with traditional Solutions oftentimes they are hard to configure what we want to bring forth with document automation is the ability to more quickly set up these Solutions so we've put a lot of focus in bringing pre-built capabilities to the table so you don't have to spend all that time setting it up from scratch and that starts with document specific parsers right so a parser essentially is a pre-built configuration to extract information from a specific document so we have introduced our own extraction engines a new extraction Engine with document automation that can extract information from invoices as well as purchase orders right out of the box right when those pre-configuration or pre-training required at the same time we want to bring forth industry specific you know machine learning models we have a partner here Infinity ml if you guys haven't had a chance to go talk to them go see what they're doing they're doing some really interesting things around medical documents Right medical documents are very complex you know they're usually very unstructured you know just all over the place and they've built some really complex machine learning models to be able to extract information from these metal document medical documents that you can consume directly inside of our platform and our goal in in the roadmap of document automation is to continue to bring more of these innovative solutions to the table that you guys can leverage right whether it be simple documents that you can address like with our our engines like iqbot or the new parsers that we develop of course or you can bring your own solution right if you have a product that you like today and you're leveraging and it works really well let's talk about how we can integrate that into that platform and again you know maybe that product could be used for one use case and you have other Pro or engines that you can use for another use case and our goal here is to make this seamless to you right to be able to ingest these things and pick and choose which engine you want as part of your business process and then action that you know across those different systems of record right it's not a linear process anymore right you can make decisions based on this information that's coming in the document type where it needs to go maybe it doesn't need to be extracted right maybe we just want to do classification and splitting and then route those to people so they can work off of that document this is the the goal and strategy that we have around IDP in in the market um so there's a couple really important features of document automation that I wanted to highlight before we hand it over and the first is we call instant feature enablement right so document automation now is part of the control room it's just one of the menu items inside of the control room you click it you can create learning instances directly inside of there using the new engines you can connect to your iqbot learning instances that you've created or again you can leverage those third parties as well but again the importance is not on all the third parties that are there really it's about how quickly and easily you can set this up and then integrate it into your processes it includes um a pre-built processes pre-built validation interface things like that all built on top of re right leveraging that in our entire platform to allow you to quickly set these things up and get going very quickly and lastly the you know the UI you'll see with document automation uh one you know from an RPA developer standpoint you know being inside of the application really powerful really easy to use but from an end user standpoint right this is an important part because of course not all documents are going to go through automatically so we want to be able to allow the user to you know use their common interface which it which could be the re workbench right in the work queue and be able to process documents or be able to process you know other types of work so it's very familiar and very user friendly when those exceptions occur so again you know to highlight this is really about not just document automation itself but about leveraging that end-to-end platform and ingesting document extraction in real time right and it's part of your business processes at the same time allowing you to bring you know engines in that are going to support those different document types so that you can quickly set these things up and get going as fast as you can when you know in your automation Journey so with that we're going to have two speakers here guest speakers so we've got vivec from Mosaic is one of our partners in the loan store which is one of uh mosaic's customers they're going to talk about their automation Journey their history in the intelligent document processing space and how they've been able to leverage this platform approach to bring together capabilities to give them a very high level rate of automation so with that I'll pass it over to Vivek thanks Michael thank you everybody um I'm going to start off with a taking you back a little bit okay so a lot of you are much younger than I am um it was a brief brief background I've been in in and out of the mortgage industry for um since 2003 so about 19 years right I got into the mortgage industry in 2003 when we built our first one of the first mortgage vertical BPO companies including ID services and mortgages um and that was um I knew nothing about BPL I came from the I.T industry and the BPO industry is slightly different right um knowing nothing about the BPO industry I asked a lot of stupid questions in hindsight there's stupid questions right so one of the questions I asked the team was I walked into a meeting we were doing classification we had 40 people in India doing classification of mortgage documents right so you have a 300 page file you're separating out your W-2 your pay stubs Etc right so I walked in the meeting and these guys were the people that were orchestrating the process being offshored to to India and I asked the question hey what's what are the metrics for this process right and they said well we it's a 92 it's 92 SLA is what we're we're going with so in my naivety I asked why is it not 100 percent right so the answer was nobody really gave me a good answer at that time I still remember that but the answer is really because humans make mistakes right that's that's the answer right he would make mistakes and if you have a human doing this mundane task eight hours a day they're gonna make a lot more mistakes than normally right so AAU that's not what you and them meant to do these mundane you know rules-based tasks that could be automated and secondly Bots don't make mistakes the program to do what they do right so I like to say that our OCR capability now is at 100 as long as the OCR quality is good right it's only dependent on OCR quality right so that's a story I'd like to get into tell you to you know you've heard all the reasons why automation is good right but one of the reasons that it's other than you know doing replacing the Monday task is that the operational efficiencies that you get that are kind of lost in the shuffle sometimes because people just look at oh I'm replacing a human I'm using a bond what does it cost there's a lot of operational efficiencies that I can we can talk about in the mortgage space that are soft costs that are actually translated into real dollars at the end of the day right so um that's that's really the a little bit story about that so the way the reason I talk about BPO and um automation is because there's a lot of similarity being older right um a lot of similarity I see from those days to these days right so in the old in 2000 2003 a lot of folks were doing invoice processing right Payment Processing those are the first jobs that were offshored right the horizontal processes FNA HR guess what's happening right now in automation every every Booth out there has invoice processing example right during invoice processing you're doing HR processes because those are the low-hanging fruit those are easy to do those documents are easy to read the processes are relatively standard and relatively simple it makes sense to do right what we did in 2003 was we did we were a little bit ahead we did domain-centric offshoring right and we're doing the exact same thing right now with Mosaic by doing domain-centric automation so at mosaic we do only mortgage automation on top of the platforms that we've kind of described so it's really what we're talking about is getting ahead of the curve right and not being with the crowd in terms of doing the standard stuff you want to do and that's maybe a little bit of ahead of our time but our time will you know slowly come so we we're tackling a much harder problem why is it much harder um and automation anywhere knows this because I bang their doors all the time like you know we're kind of like well I don't know what because the customer is zero in the sense of like we're pushing the boundaries of the platform right um because we're trying to do something that's much harder I'm sure all of you know have seen mortgage documents they have check boxes they have radio buttons they have tables they have tables within tables right they're Dynamic tables you don't know if you're listing your assets I don't know how many assets you have right so the dynamic tables to read off right so there's W-2s there's bank statements you might bank with or someone else might be back with Wells Fargo they're all different so how do you extract data from such a complex set of documents right so it's a very complex problem um and I will show you an example of what we do to kind of mitigate the problem so I'm going to hand it over I mean this is a pretty standard slide you know this is kind of the manual processing repetitive tasks and you go what the demo that we're going to show you today is really about intelligent mortgage automation everything that Michael talked about we've built and deployed in the mortgage space right um and even in terms of using multiple vendors for IDP or data extraction in terms of using um having an actual process Automation and I'd like to talk a little bit about that before I hand it over to Jag when when we're talking about Automation in the mortgage space some of the automation that we've done in the mortgage space and Jag will highlight that as well there are 250 steps in the automation we're using apis RPA at the same time right when Python scripts at the same time you might be going to a website using python automation we might be using an Los using apis and RPA it's very complex along with the data extraction so when we're talking about automation we're really talking about process Automation and we don't process one document at a time that's the other thing a process involves multiple documents right so I'm going to take in 40 documents I'm going to extract three to 300 fields from those 40 documents and then I'm going to use those fields to do my validation and business process right so it's not about oh I'm going to take one invoice process it to this it's it's a and to orchestrate that process there are multiple Bots working together talking to each other right so it's a much more complex narrative in reality in the mortgage space and I'm sure in other spaces as well but it's a much more complex narrative and you'll see some of that in action uh in terms of the intelligent automation I'll hand it over to Jag who's our client he'll talk a little bit about the Lone Store and himself and I'll come back and talk show you the demo thanks be back all right so uh my name is Jack Chopra I'm the CEO of the Lone Store I have over 20 years of business process mortgage knowledge and in my background I went to a school up north called McGill in Montreal I did my engineering degree there and then I went to Arizona and did my MBA in finance and Mis so that's kind of a analytical background process stuff in the last you know 20 plus years I've seen lots of Technologies come and go um I would say that you know in in 2019 um one specific technology caught my eye and can you guys guess what that technology is automation yeah she gets a candy bar we got a chocolate bars um exactly right so what we did then was instead of trying to inject automation into a going concern into a company that's already there and it has people as Legacy and as processes and they're all jumbled together we just I love white boards see that whiteboard me me and that whiteboard or are friends we we built the company from from that point right from the Whiteboard we said how do we get the most cost effective efficient operation out there so the Lone Store is a wholesale mortgage lender okay so what that means is I don't take applications directly from borrowers bars give their application to a broker and the broker then has multiple options to who they want to sell the loan to and so loan stores be one of them so we're licensed in 26 States uh nationally we're still growing on that and to be operationally as sound and efficient automation was one key driver the second thing that I wanted the Lone Star to have was awesome customer service and usually that there's it's an oxymoron to have awesome customer service and be super efficient because you need the same people to do that work but with automation that's possible right you can actually be very cost effective through the meaningful Automation and and now I've empowered my people to basically you know help the broker or handle I just got another testimonial this morning on my phone that the Brokers raving about us it was the first loan they did with us and they loved it you know why because my people have enough time to talk them through it and they're the bot the bot is clicking the buttons the bot's doing all the menial tedious work right so that's that's that's what we're trying to do so we we try to win with Superior customer service and keeping operational costs as low as possible a couple things I want to point out 10 business processes and Counting that doesn't sound like a lot you guys saw the Keynotes these guys are doing thousands but these processes are very long hard difficult processes these are bots in a meeting and they're all working together right you've got the RPA bot you got the API bot and then they're they're exchanging information one another they're they I'm in a system where multiple users can't work on the same loan at the same time so one has to come out oh one okay this loan is locked it's it's a very complex problem like vivec mentioned it's you know over 200 steps just to do one thing on the fulfillment life cycle which is you know loan setup underwriting closing post-closing and then servicing the five different bu's that happen to be in most mortgage Banks right um there if I take a servicing if I let those you know end-to-end closing and funding of the loan there's only about 30 art processes depending on how you slice it everybody has different the only three so they've done quite a bit in terms of automation right and they've gotten pretty far so far yeah and of course there's a lot more to do but I wanted to give you a sense for what 10 processes means for a mortgage bank right it's about one third of their Autumn end-to-end process right so to talk about those 10 processes you can see the benefits here the productivity uh the straight through 80 percent cost savings all that this number actually to me is most meaningful and it doesn't sound like a big number 25 compared to the other numbers there but that 25 compression in the lone life cycle means big money for us because in in um when you when you lend money we have Warehouse banks that we have to pay back and the faster we can turn our loan around a couple of things happen we get a better price from the secondary Market the loan's not sitting on the warehouse line where we're paying interest the uh the actual the borrower experience is much better because now the borrower doesn't have to you know they're not sitting on the sidelines like wondering where's my loan and what you know do I need to get out so our capture what you call our pull through rate is much higher the faster we go right but we don't want to sacrifice obviously quality so that's again why automation is a fantastic tool for that so um I think that's that's one of the softer metrics I was kind of talking about right other than Bots just being cheaper than having human workers is that reducing their you know time to close alone has real dollar benefits Downstream for them right um and you know we don't usually use that in our Roi calculations but for for us we can um definitely use those yeah exactly um so if you think about the mortgage process a lot of the front end we've automated um a lot of the back end we've automated because those are more simple right and now I'm working towards the middle right so getting into the the more nuanced stuff and you know Mosaic uh you know built an incredible tool that we're going to show you guys um and it basically is like a it's a it's a foundational tool so you can apply it at different points in the mortgage process and basically it gets rid of a lot of the stare and compare stuff so you don't have people doing it you have the bot staring and comparing and then the Bots highlight the discrepancies so now the people just work on the discrepancies so we're going to show that as well so you know I just I'm very proud of what we've done at The Loan Store and um you know it's kind of what mihir said in the the keynote uh you know think automation first that's how we built this company so very very cool stuff so I think it goes next to the Bring It On Together you want to take that yeah sure go ahead um I like to be on that side you got it that's a good side guys my neck doesn't bend that way very well um so um we basically said the context you see the evolution in the in the market we've discussed mosaic's Journey on my journey because I started both companies and we've seen you know the IDP tools moved from screen scraping or you know to to this you've heard a real customer story in terms of the benefits they've gotten if they used the automation first Mantra so to speak right to do things so I think in terms of I think the the um the real um devil is always in the details right so I want to I want I'm excited to show you the demo but um in terms of just Mosaic this is what we do right um we we do our own process orchestration because it's very specific to the mortgage industry we've integrated into the system of record right and we've obviously used automation anywhere to do the RPA as well as the intelligent IDP stuff and then we all you can't do anything without having metrics reporting Etc on it and it's also very specific to the to the mortgage vertical so we build that the one thing I did not discuss is why did we pick the mortgage vertical to work on right does anybody know anybody have any insight into mortgage vertical why is Mori the question is why is the mortgage vertical ideal for automation if you can take this what I'm going to say you can take it and apply to other Industries right one reason is very simple reason about 70 of the Fulfillment life cycle is rules-based right so it's not decision based the underwriting is obviously decision based but seventy percent of these processes are stare and compare rules-based processes at the end of the day right so that's when the processes are like likely to you know very and it's very paper intensive that's the second reason the third reason I think is probably the most important reason is that if I ask Jag today right Jag what is your volume going to be three months down the road he will not have a good answer for me so it's kind of like saying how much are you going to sell three months from down the road well if you don't know you can't staff do that to that request so look at this example if I'm doing a thousand loans a month right three hundred thousand dollars per loan that you're doing about 300 million in originations a month right that translates to about 3.6 billion a year right that's that would be a small to mid-sized Mortgage Bank right um so if if you have a thousand loans a month maybe you have 150 people in 100 people in operations processing those loans if you can't if if in three months your volume drops to instead of thousand loans a month it drops to 700 loans a month you have 30 of your Workforce doing nothing if you fire them and then three months later interest rates drop at you and your volume goes back up then you have to rehire them right so that's a problem in the mortgage industry where you do not know how to right size your Ops Team for the volume you're going to get because nobody knows what the interest rates are going to be and what the volume is going to be you can take a guess but you don't know but if I have Bots doing the process you know the answer right I can turn off about if volume goes down I can add another bot if volume goes up right so that's the reason it's ideal for the mortgage industry if you couple what I just said with the margins in the mortgage industry the margin in the mortgage industry or Mortgage Bank are 50 to 150 basis points right great Market it might be two 200 to 300 basis points but typical Market it's between 50 to 150 basis points that's a small margin if you have if you are a large bank and you have thrown 30 40 people just sitting around doing nothing that eats it to your margin when your margin well you need to increase your you know you're not going to be the most competitive person in the market and a mortgage at the end of the day is a commodity right you don't care which bank is giving you the mortgage as long as you get the best rate right so there's there are many reasons we got into the mortgage industry and then from an automation anywhere or just a general point of view each mortgage is you know 300 to 500 pages you're going to process billions of pages so there's lots of money to be made right in terms of processing mortgages as well okay so we're going to start this demo and if you'll help me pause it when I need to I'll just say pause right okay so if you can kick it off before uh sorry before you kick it off hold on one second this is a process called post close audit there are about eight processes in the mortgage life cycle that are all audit processes um like Jack mentioned we built a technology we call it checkpoint and we deploy it for different audit processes the difference between the different audit processes it could be pre-fund audit post close audit post fund audit loan onboarding pre-underwriting audit you know all these audit processes in the mortgage space right um all we change is the documents that go in right the data that's extracted and the business rules the underlying technology of checkpoint is the same right so with that can we kick it off please so what you're going to see is the bot logging in and it's going to pick there's a pipeline of loans right and then you're gonna it's gonna go into after that that was it's going to class so in for this particular process there are 40 documents if you can pause right here please there are 40 documents here that we're going to classify first of all in this process right and this is what I mean by a process all this happens in an integrated fashion like Michael talked about right everything is happening in in in as part of one whole automation process right the classification of 40 different documents from mortgage file you were going to extract 265 fields for this specific process from those 40 documents right and then we're going to the audit is going to do multiple things it's not about just data Integrity right it's not just about validating hey is my loan origination system has the same number for loan for loan amount as my my document it's not just not about checking data you might be the business rules might be we're checking missing documents are they there right did they really submit a W-2 do I have the bank statement the latest bank statements you have the latest W-2 mismatch DNA documents that's the thing but there might be other business rules like calculate calculation based business rules as well so the audit process checks all of those things right and then it will it will first of all the next Slide the next thing you're going to see is it's going to show you a list of loans that have gone through the audit process so now in Ops person um let me step back a little bit this process in the BPO world or in from a human perspective it takes about an hour to do right typically um because you're checking all these documents and doing all these business rules um if you when you use mosaics checkpoint it's a fight depending on the number of audit rules it passes or Not by passes it's a now a five to ten minute process so what the the Ops person who used to spend an hour doing this now interacts with mosaics checkpoint Pros product right which which we'll show in a second so we can start it again please play so you're going to see um we're going to move to the next step this so you see the list of loans and you'll see a list of the audit status could you pause it please so it went it went by pretty quickly but you saw a list of loans and then you you saw the they picked one loan and you're looking at the documents for that particular loan what's missing like the 1008 is unavailable and you're seeing the actual document with the fields extracted next to it right and they may if they're discrepancies they would be highlighted could we start it again please so that's the document review it's part of the audit right the audit is the tab on the on the top right so you can go through this correct things send it back to the system or record or not right um and um it can be modified if you were not able to even extract the data so it shows you exactly what's happening with the docs and then I want to go back to the audit part because this is all verifying data there's a discrepancy here we'll talk about that a little bit so these were the closing docs and you can see that can you could you pause it for a sec here when yeah so these business rules have passed and that business rule has not passed for collateral and then we're going to go back to the closing docks because the docs are also divided into different categories right income docs closing docs we're going to go back to the closing docs and look at one of the things that did not pass please start it again foreign so the Ops person has the ability to go in there and look at this and say oh the DU says attached the loss says detached so we're going to have to probably run desktop underwriting again right so if they run it again and they'll run the audit process again it should fix that problem and over here the loan amount is different so they can fix that as well right so that's basically so your job it used to be an hour worth of work in terms of running this post close audit process now it's just you all you have to do is work with the exceptions for the audit process Jack anything to add sorry I just went through it no that was perfect because you knew where to pause it and stuff um you know it basically is it helps right it helps tremendously because it takes uh the heavy lifting gives it to a bot and then the human is actually using more decision making and higher higher Roi right it's stuff and they actually they love it like they love using these kinds of tools they love using the thoughts they actually feel like they're they're like many managers right and they're they're sending Bots commands and they're making and the bot's going to do the work while they do something else maybe they get on the phone they talk to a broker and they they show them how our our platform works or our technology or they answer questions they train them so that they become much more useful right they're not just pointing and clicking buttons the bot's doing that and in this in this case checkpoint can be applied at multiple places right post close is an important one we don't want to give away money that's wrong so this is when we want to make sure that we got right the data is right we have a similar one at checkpoint we call pre-underwriting so what that means is before the underwriters which are the most expensive resource in a mortgage bank before they start looking at it well we have other people looking at stuff and sort of prepping the file so the underwriter isn't having to do some of the more administrative clerical work so checkpoint is a very useful tool over there as well then you can get into the QC side after a loan funds just to make sure things line up typically I like to do it before we fund a loan I don't like using stuff after the fact but you got to do that actually you got to do that for the Auditors you got to show that you're sampling it you know 10 QC size to to your to your loans so that's it this is um you know we oftentimes we get asked when we're working with a new client on how we View processes being lined up from an automation roadmap right and for each one of these wave one wave two wave three this is the way we view um the if you're going to get into start on your RPA Journey do the classification in RPA low hanging fruit first then you start doing the data extraction kind of word and there's a very specific to the mortgage industry and people different people do different things but because the documents in the mortgage industry are hard to extract from we usually try to do the low hanging fruit with our clients first give them some success and then move on to the uh you know uh you know more difficult processes I think what we've done is some of these products that we have and you can go check it out on our website these are pre-built products in the mortgage space that we sell on a per file basis like eight dollars a file ten dollars a file checkpoint is a little more expensive but um you know we sell the we can deploy these in four weeks because they're already pre-built right so that's the idea is you know you want to get your Roi as soon as possible right so building these little products or little little little uh little processes that are already automate automated helps our clients move very quickly obviously Jags and The Loan Store are thankfully a guinea pig for building there are partners for building a lot of this stuff so they get a lot of stuff free right but he gets my 20 plus years of process knowledge for you too but yeah it's a good partnership they're they're uh there are in many ways our development partner as well just so you guys know um that's all I had Michael do you have anything yeah thanks for back and and thanks Jag as well appreciate you guys telling your story I think it's pretty exciting right we talked about how you can use a platform right to really bring different Technologies together and you know one of the things that Vic talked about was you know using our RPA components our document automation components he's also actually bringing other engines and engines in as well so with that I want to open it up for questions so is this a vertical solution expert s is this a vertical solution that you're selling from many mortgage companies or is there some competitive advantage that your customers get from no if we selected many mortgage companies it is a vertical solution so our approach to automation is is has been to build a vertical solution in the mortgage space so we sell it to we'll sell it to any Mortgage Bank you that you recommend or anybody anybody anymore good luck I got a bit of a head start yeah so for each one of those things I just showed you we have product specs and you know we'll show you what exactly is configurable what's not and then the way we go to market just so you know is we charge about five to ten thousand dollars for configuration and then after that is just outcome based everything's right on the cloud it's five dollars alone file ten dollars a loan depending on what process it is so there's very little you know our clients don't have to deploy anything other than the VM and sometimes we'll deploy it for them right so it's very non-intrusive to their I.T environment or we just need to get a yes we rarely talk to it folks it folks kind of vet us and say okay yeah you can use this we usually sell to the CEO or the CFO of the company so so you know much funding you need now to start your business I mean the reason I'm excited about this really if you guys are in different verticals I think the team to stop talking about invoice processing and automation guys okay just stop you build vertical Solutions in automation I think you can do it we've done it and it is possible to do it there are tools available to do it so I mean that's that's where the real value is right in terms of the real vertical processes that you can do not to say there's no value in FNA and HR but you know I think that's that's been all minimal value it's been all the play that's all any other questions do you have people who are verifying that or do you trust no no no in the mortgage world we don't trust the bot at all right because if you make a mistake it's going to cost him a lot of money right so we don't trust about it all so that's what the checkpoint is checkpoint we are talking about one specific business rule which is data of Integrity right so it will so that's part of what the Ops person will look at in terms of what what document wasn't extracted at all nothing happened there's a missing document it'll look at you saw the highlight of the difference between the loan amount right with the confidence levels you know which which Fields they need to look at right and they're very even if without confidence levels the process would be and is that you do look at a loan amount in every document because it's an important field right so you do they do that in the checkpoint application itself so that those checks are done in the checkpoint application it's one of our employees using checkpoint the bot runs then and it highlights the discrepancies and the deploy takes action on those discrepancies right and the action might be fixing it the action might be even leaving it alone uh action might be like in this case running the desktop underwrite it again because it said the task versus attached they saw that discrepancy so it might be many different things it might be one of the trade rules which Jack can talk about I don't even know what they are but you know there might be some other business rules that are mortgage related embedded in the audit process itself yeah I think the key there about Christ is the business rules right it's about building business rules into the process so that we not only extract the information but we validate you know it's valid because you know the information on the document may not always be correct right and so that's an important piece when you when you look at extraction engines right so what else can you do around it and the business rules are the magic right that's what the people are thinking when they look at it so can we literally take their thoughts and make a business rule out of it so coming back to the trade example you can't consummate a loan uh prior to you know seven days uh from when you took the the application so you know if that date was somehow earlier then we know hey wait a minute we need to wait another day right we can't send that CD out that fast that testimonial I got I was telling you about got a two hours before we got on here the the broker was who's he was over the moon because we we took and funded in 10 days and he's like dude I'm gonna send you our loans because you guys did a great job but we have to have safeties in place right there's a lot of stuff that happened in the mortgage industry as you probably are aware of um and so there's now lots of guard rails and we make sure those business rules handle those guard rails so they've got time for one more question two more so uh thank you Vivek Jag this is a great presentation I guess my question is more for automation anywhere which is I feel like a lot of what we've seen is very much intelligent document processing and I've to understand the difference between what what the title of the of the presentation was IDP is dead document Automation and something or other and is the idea of document automation essentially re where you know it's the I guess I'm struggling to understand yeah I can see how the title is a little confusing I didn't understand that so really it's about you know talking about automation being this integration platform right and allowing you to pick different engines right it could be our cubot engines it could be some of the new engines that we brought forth in automation 360. as well as like you know these guys built a classification engine that they use in the mortgage space as well but if you look at traditional IDP it's really about you know siled solutions that are there to process maybe it's a specific document type like an invoice or more generic platform but that platform itself is very very silo so we're saying about document automation you know it's a it's a verb but it's also a product name right and the product itself we're trying to move towards that more real time right to be able to take information as it comes in it's like for example these guys you know as these loan packets come in to be able to process those immediately and distribute that as part of a larger business process and not say okay I've got to capture the loan and then I've got to pass that over to some other system that's going to do all this other work we're talking about right in all these businesses a lot of times Brokers will submit stuff piecemail right so we don't get it all at once it's so it's not a batch process that's what I think of when I hear that so like you know it's not like we we got everything in the mail room and now we're processing it it comes in live so as that comes in we know about it the bot works it uh human cleans it up and then it keeps going back right sorry guys we ran out of time well we can take your question off the side but I really appreciate you guys coming and if you have any questions please come find us let us know thank you guys thank you