Sales operations automation for financial services

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[Music] welcome everyone uh we're very excited to have you uh here today with harry myself for our first session of process automation live which is a format of an interview a conversation either with a partner or with a customer uh benitezoff to talk about you know process automation uh more specifically on one given vertical so on the first episode as of today we're going to talk about financial services and quickly to introduce myself so i'm michael duken i'm the sales director for beniosoft in north america and i also managed and very happy to manage our our partners as well including evoke technologies hi again harry um i would be very happy if you could introduce yourself to the audience yeah definitely michael first of all uh thanks for this opportunity michael you know for having me here and share my experience about bonita soft and the bulldozer soft solutions uh so myself hari allah um i know so i'm i'm associate director at evo technologies part of business process automation solutions division i've been working with the bonita soft since you know so 2013 we have implemented multiple solutions to our customers you know so today i'm happy to share you know so the solutions are use cases you know as part of this uh conversation sure great harry also can you quickly share your background you know of course you can talk about evoke and what does what value evoke brings to um projects you know with customers who want to start the digital process automation journey but you know very interested maybe you can share also your overall background um and you know your your skill set yeah so definitely i'm you know primarily a java architect uh you know i was a full stack developer working as java and angular frameworks delivering you know the application development as you know so java based web applications and mobile applications right and then we we you know so we came into a situation where along with application development we had to bring certain process automation tools to increase the operational excellence or to increase the productivity of our customers that's where you know i came across with bonita soft and other tools where we started leveraging them to implement automations in in you know from our eu technologies to our customers okay and how large is evokes team today within either the bpm practice or the business process management or you know with bonita right so primarily evoke is basically you know so is uh based out of hyderabad india we focus on delivering solutions that increases end user productivity enhances customer experience you know today's enterprise world these are the problems that customers are trying as part of their digital transformation journey or other initiatives these are the problems that they are focusing today right so as part of these initiatives you know so we have been using bonita soft definitely as a widely used tool as part of this process automation solutions at ewok and you know so we have about 35 plus professionals working in with different customers across you know manufacturing pharma and financial services to our customers and you know so many of them are certified by bonita soft uh you know so certified professionals from bonita soft uh so jumping into the industry uh harry you know you work with a few of our customers in financial services can you you know share a brief intro or you know use case or what were the initial pains or challenges that you know the customers and financial services that you work with in automation have to uh how to tackle right definitely michael so we have been in so we have implemented bonita digital platform to you know couple of customers uh one of them are into wealth management business based out of u.s they manage the funds from the large investment banks and fund portfolios into the trading systems i'll explain little bit you know about that use case and the second second customer where we have implemented is called crystal it's an indian in india company in snp global india division they provide ratings to you know so uh the the you know the sme businesses in india michael can you hear me yeah i can hear you okay so i lost even you know the webcam um so you know little bit deeply so let's focus first on you know the fund management business that we have dealt with you know so if the time permits i can also you know happy to share uh how we implemented process automation for this rating agency so to start with you know our customer basically you know so as i said they're into wealth management so they receive funds and fund portfolios from different sources you know these sources are basically external to the customer you know ecosystem basically they are from external system parties right um so so these data sources were usually unstructured because we did not have control over this data those data sources right so these these funds portfolios that comes as a daily feeds we have to onboard into you know our our customers trading systems but as part of this onboarding what we'll have to do is because you are dealing with financial data and fund data it is very important for you to set up this data right there is lot of master data associated with these funds right relationship managers restrictions a lot of you know the the fund types that you are dealing with based on funder type there are rules associated with it and as part of these you know the before pushing the data into these trading systems there are multiple teams will get involved to basically you know the process the data right the steps like there is a team who basically focuses on setting up the basic account data right that involves lot of master data and other associated data sets right close to 250 to 300 fields of data they will have to you know populate or you know the feed into this uh you know the uh as part of onboarding process and then finally push it into the trading systems and there is a team who actually deals with only you know setting up the paperwork for this account the fund that they are dealing with for that particular account a lot of paperwork is involved there is you know the third team who actually focuses on validating the data and you know so and then basically quality control of this data that is flowing into the before trading it you know before putting them into the trading systems right so these are multi-stage data teams analyst teams who gets involved before this data being processed into the trading system right so so you know when this problem was you know so they were dealing with before bonita platform was implemented they were dealing with basically you know so they have different systems you know a lot of them are a lot of manual steps they used to follow some of the spreadsheets and email communications used to happen between these two but also they also have certain systems where they feed the data but they were disconnected there was no visibility around this process they were having lot of you know inefficiency bottlenecks you know in having these operations you know run this you know the onboarding process that's the challenge that they were facing no sure um so you sure you know the challenges so typically when does evoke arrive in such projects do you arrive at the beginning of the automation journey do you arrive after you know your customers or our customers already start doing it themselves and then they're kind of stuck what do you think is what was your role at the pivotal moment as you know such project all right it depends on case to case michael so there are situations to customers so you know some of our customers we were involved right from the grounding of the solution right right from understanding the requirements that is usually we call it as process discovery phase we go hand in hand right you know but in this case a special case where we were talking about this fund management company right so bonita was already involved you know the bonita team the professional services team they were involved with this customer in building a prototype so we were not part of evaluation of you know so choosing this bonita platform there could be multiple reasons you know at that time you know how exactly the bonita bonita will fit into their solution you know so we were not part of evaluation phase but there was a prototype you know prototype built by bonita professional services team which was nicely laid out you know the business really understood the value of bonita tool in terms of you know bringing this you know the process visibility that they are dealing with today so so that's where you know so being a premier partner you know for us evoke technologies were involved in converting these uh you know prototype solution into your production grade solutions that's where you know so you will evoke got onboarded into this project and you know so we we had to deal with lot of other challenges you know to convert this prototype into a production grade system sure sure and um what type of of expertise or what type of value do you bring to your customers is it just focusing on speeding up their developments uh bringing them maybe expertise where they don't have it in-house what is you know the the range and the broad of assistance and and guidance that you can bring in in such projects of animation definitely michael so so let me explain this also as i said there were few challenges right so if you when you are converting a prototype into a production grid system the important aspect that you need to look at is you need to think beyond the process right so when while you are building your process automation what we look at is what were the steps involved what are the forms that you know the uh the the manual interactions were happening we basically simplify the problem and do you know the business case right but when when you talk about production grade system typically you need to think beyond the process that brings a lot of other ecosystem into your solution right for example in this case i can talk about three challenges that they were facing how you could bring a value while providing the solution right the challenge one as i was saying the funds that they receive on daily basis those were daily feeds thousands of data sets that they received the accounts information that too into different channels right they have email channels some customers some investment banks they send through emails some customers they send it send them through spreadsheets and there were customers who have their web portals right so we had to go to their web portals scrape the data and you know feed those data into our trading systems right so if you consider this problem there are variety of data sources and the data is unstructured because the data is coming from external parties right so so in this case so if you understand right so so this is a problem to deal with the data processing and data you know dealing with unstructured data not with process orchestration so this is where you can bring value so we have distinctive competencies we focus on end-to-end solutions right so as part of our you know the intel due diligence we understood that this problem has to be solved by rpa framework right so we have introduced rpa basically the rpa basically you know the bots that we have deployed they die they day-to-day you know on the scheduled basis they they they you know that they connect to these data sources these boards and process these data we have also added certain cognitive capability because you need to deal with unstructured data and then this data will be fed into the process engine now the process engine starts with the orchestration of the process right yeah this is how we solve this problem the challenge too in this problem was the user interfaces were really complex right so because we were dealing with 300 to 350 fields and each field has certain rules associated with it when you change a field there are certain rules you need we need to bring from other systems because these are financial data fundament fund related data right so the user interfaces were complex thanks to bonita digital platform lot of process platforms typically you are limited to build your user interfaces because they focus on orchestration user interface capabilities are very limited because they come up with their own you know the proprietary frameworks bonito soft uses a widely you know well-known platform called angularjs so in this case we were not limited you know we were able to use the angular community bonita widgets we were able to provide this complex ui which is a multi-tab we were different grids inline edit grids wherever is needed for our analyst right it made it so yet we had to build intuitive interface for our customer right does that mean over here does that mean in this specific project when it comes to the front end of the ui you have used the angular technology provided by the bonita platform or the you had to integrate with their existing uh you know portals so we have used uh angular framework provided by bonita platform yeah okay right the third challenge that we were doing facing in this solution was you know so because we had because we had to think beyond the process so when we explored this when when we talked when we were you know so exploring while we are converting into production grade system what we found was there are multiple downstream systems which were you know listening to this process at different stages of event right different stages of the process events and there are upstream systems which we have to push the data like master data and other you know financial related data into this process so we needed to have a you know the very robust integration framework again thanks to bonita digital platform so bonita has a robust api framework where you can build your own rest apis it also comes up with lot of rest api framework out of the box and also it provides you a connector framework through which you can you know it made our integration challenge was easy for us right we were able to build resilient integrations where if there are any failures we can recover from those failures re-drive fault tolerant and you know all these scalable aspects we've been able to build with this bonita integration framework so these so this is how you can bring value think beyond the process bring the right platforms and tools to build your ecosystem you know that's how your solution can scale and adapt to the agility that you know on how which comes you know which are unknown you know problems that you foresee after your solution go live and and in terms of results or delivery um how does an organization measure the success of you know such an implementation or how were you how was it perceived what value and benefits have they seen on top of course of having you know an automated platform of how how strategic and how beneficial you what you thought you think it was for them to measure to say you know we went through that route and we have you know delivered what we expected and we have improved you know for instance customer experience uh time to execute tasks i don't know how how they were or how you were able to help them measure that right yeah so typically you know so so what happens is when it comes to roi definitely being a partner you know so we will not have enough data to calculate roi but you know so we can directly correlate the way they are doing today how the process being handled and you know so after we implement this process automation solution you know how the productivity looks like so we can do a direct correlation you know so so in this case especially what happened was before this process automation was done their themes the collaboration was you know not managed well right so you know the the out of these three teams who were collaboratively working in this onboarding process they have as i said there were you know the few systems where they log in you know so these systems were disconnected right they upload the data and they do certain steps there and they come out right if i want to look at where is my process my onboarding of certain account i did not have a data because it is not centralized this is being distributed into you know few systems right so in terms of product the visibility is one aspect where we were able to bring all these systems you know connected well into an orchestration layer by using bonita digital platform the second aspect is the challenge that they were facing they were they had if they want to do onboard one account they'll have to deal with multiple you know interfaces you know so first thing they deal with the different spreadsheets the manage enter second status and they send it to other team they feed the data into an interface right there were multiple interfaces that they were dealing the productivity was you know so they could not scale the accounts onboarding that they were receiving right there was a lot of tampd time delay okay the productivity is the either direct calculations that we were able to do you know so so so they were able to improve the operational efficiency by you know today they were able to onboard these customer of fund accounts you know five times faster than before you know implementing this you know automation platform yeah now i think these are good examples what we see not only uh you know in financial services industry but overall and and you're right to point out the kpis and lri is not something easy to monitor but usually the the great triggers or kpis is the time to build maintain and evolve the platform uh because like having an agile stack of integrated systems with an automated platform is going to help you make your changes on the fly and how easy it is to maintain which you have you know developers leaving in around the company and second it's time to execute task and then overall efficiency right what we could all you know call and to end visibility as well it's uh it's definitely something yeah and so to conclude on on this conversation before we jump into uh any questions from the audience what would you advise an audience uh on how to get started on on process automation journey in general if you have maybe tips and do's or don'ts uh to share around that definitely michael yeah i would be happy to you know share that you know it's an interesting question yeah so there i mean to it based on my experience because i have been with dealing with cross automation solutions more than you know close to 2013 so we have started and you know so so to to you know so basically two points that i can bring on to the table you know so hopefully that will help one right so when you are talking about when you are when you are starting thinking about a process automation solution so think beyond the process as i said right so what were the systems involved so process anyway we deal with right because any process automation solution deals with your human orchestration the rule engines the transition bpm annotations these are all well taken care there is there is nothing to worry about that any platform will provide this but what we need to understand is being a solution provider we need to think beyond the process what are the upstream systems that are involved from which data is flowing in what are the downstream systems that are involved after this process is being done where the data can add value to those downstream systems sometimes the stakeholders may not be able to give you these because they are outside of the process they focus only on the process right so when you when you can bring these aspects your solution can change right so that's where you can bring right platforms right tools to solve these peripheral problems around this process and that way your solution can be you know a complete solution right you can bring an end-to-end solution for your customer right the second point you know the the second point from my experience is never try to solve all the problems with one platform right so let's say in in our case there was unstructured data that we are dealing with we could have implemented a process where we load the data you know you process the data add certain rules around the data and then start with process orchestration but that is not the core competency of the process automation platform that's the responsibility of your you know the rpa tools other data integration tools right so don't bring those don't spill those responsibilities into process engine the core competency understand the core competency of the platform and deal with those core competency problems around that and take complement platforms like rpa and integration integration tools to build you know so to solve those data problems right these are the two things you know so which you know which i learned in my experience which really you know fit well and you know helped our customers to scale their solutions sure sure sure um and so from your standpoint also when it comes to sponsorship or who has to be involved in in project is it more led by i.t is it more led by business what do you think should be the right split or responsibility in having both you know business analyst or or i.t development team is being involved in automation right yeah definitely because especially when we are doing a business process transformation business and i t collaboration is very vital you know they play vital role right in our case we recommend so you know definitely the business team will involve in the initial process discovery phase we we run different workshop understand the business problems talk with different stakeholders but we also recommend to get involved this one of the business stakeholder as part of your development life cycle it could be sdlc or waterfall or you know agent whatever you follow have this business stakeholder part of your implementation journey you know keep you know reviewing whatever the process that you are developing you know keep reviewing with their with the stakeholder on sprint basis right in our case we used to have we recommended to have the business stakeholder part of our implementation journey that really you know helped us eliminating lot of gaps you know while the implementation before release itself yeah sure um so moving into a few questions that we we've received that we we can you know address today the first one is you know you talk with one of our your customers uh that you have to integrate with rpa you know and we hear a lot about bpm rpa from your standpoint and i'll be happy to address as well from maybe a vendor perspective but maybe you as a consultant what difference do you see between bpm and rpa and how they complement or how do they compete in certain cases all right yeah yeah definitely there is a little bit confusion about bpm and rpa are they replaceable no can i use rpa where bpm is used so it's not so basically from our experience so so how it works is so when you when you have a when you have information that has to flow from you know so between different people or you you wanted to connect different systems basically this is usually called as an orchestration whenever you wanted to do an orchestration of the data orchestration of the teams and the people right so bpm fits well right the streamlining of the process streamlining of the information between the people bringing the visibility because because you are collaborating with different teams it is difficult to you know bring the visibility that's where your cross automation solutions will help whereas rpi deals with repetitive tasks right you have a rep you have a task where you know a human is doing repeatedly you know daily they come in log into the system download the data write some data you know extract some data put it into some system right these kind of repetitive tasks it cannot do orchestration or it is not recommended to orchestration though you can achieve in different means as i said never try to solve the problems which are not its core competency right so in our case so uh we were dealing with this unstructured data in our use case rpa has a cognitive capabilities which comes out of the box where you can read the read the data from images extract the data or you know build certain cognitive capabilities convert the data that you are read with a little bit human intelligence into the data that your processor engine understands right so that's where the rpa was complimentary for us to build these solutions that we have done okay yeah i agree from our perspective the way we see rpa versus bpm is rpa is greater you know automated like you say you know repetitive tasks a bpm has more the end-to-end visibility and it can also manage exceptions okay so but what i mean exceptions is we have a human behind the screen and the decision cannot be mimicked or guessed automatically by automated task or system you need to have human intelligence behind that so of course we talk about automation rpa but the role that human is still key today and this is how with you know bonita or bpm in general collaboration on top of automated tasks and system is key as well um another question so um maybe you could share your experience in helping customers deploying their first application or what how usually how long does it take to build a first application or to build several applications once the first one is implemented of course it's a very wide question because it really depends on the complexity of the process most systems involved but from your experience what have you seen and maybe be able to guide and give some timeline to the audience around that definitely yeah so so definitely as you said it you know it depends on the it varies from case to case but from our experience the way we implement is we wanted to buy the you know the buy the idea quickly right so we wanted to take the idea that that you know how the bonita digital platform can bring the value to the business very quickly so what we recommend is initially we build a poc or a prototype to test the water what is the problem and we simplify the case and we implement basically we do not take beyond four weeks when we are doing any prototype with that you will be able to understand what are your pain points how this platform can solve your problems and what kind of roi you know so you can basically with gut feeling you can guess right so once you know we recommend to have this poc or prototype within four weeks once that is done that's where we build basically we take it to the next level so usually in our experience it takes minimum 12 weeks to build a production grade version of any any medium to you know complex process you know i know so into the production you know into the which can make the you know live business right so then you know that's where on this foundation we start building roll out this platform to multiple business divisions because you will have similar problems that need to be addressed within the enterprise so then the once the foundation is done usually it takes six to eight weeks to deliver to roll out same solution because you can reuse lot of code what you have built in this three months time frame okay i uh we i think we have time for one more question um so one question and i'll be able to uh address this one so sorry if i missed it but the solution was the solution built deployed on on-premise or on a cloud no and was the solution built on locally on-premise so maybe harry you can share from your two customers that you can work on financial services just to talk about hosting with it on-premise versus cloud and then i'll be able to address and say you know what what is also common and and what we see today with overall with the customers ideas of right definitely so in our case to these two financial customers you know definitely in financial domain data privacy is very important there are a lot of gdpr components and all those in this case we have implemented you know so we have implemented on there within data centers right we did not have cloud so because of the data privacy so we implement the you know the bonita solution on local and then deploy to their data centers right so we did not use the cloud okay yeah so uh and then to address what we see with our customers today uh i see three types of deployments okay the traditional one of course is the on-premise where we used to have a more boring customer base where you know it was deployed managed directly by customers in their environments the second is public or a private cloud of of your choice or you know our customers decide to deploy on aws on microsoft azure so there's no limitation and we don't impose to say if you want to host it in the cloud it has to be on this one uh and the third is our fairly recent but we've been doing that for a couple years now it's our bonita cloud offering which is a platform as a service a pass offering where we host manage scale and monitor directly the application for a customer in our cloud environment which is an aws environment okay so it's not a sas model p as you use it's really you delegate the infrastructure cost the maintenance the scalability directly to bonita salt but we can imagine other scenarios where you know other system indicators even such as evoke would also you know be able to guide and help as well in either choosing the right cloud environment or supporting your teams in maintaining also the the infrastructure needed for the automation platform okay harry so um i think we have reached our 30 minutes for today's chats uh it was really really nice talking to you i really want to thank you again for sharing you know your experience on working with a couple of customers in financial services so thank you very much um as a reminder this session was recorded so we will send you this video and i apologize once again uh for not know being able to show my face on the webcam and i don't know what happened it seems to be frozen right now so as usual when we practice it works but on the demo phase it seems not to be working so i apologize once again but harry thank you and i really look forward to talking to you soon thank you michael thanks thanks everyone thanks for joining thank you harry bye you