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the panel discussion on the evolution of voice assistance in the banking and financial industry banking and finance has been on a roll the last couple of months here in india and in fact all over the world so we're going to find out how the banking and financial institutes can explore speech technology for conversational interfaces like chat bots and we're also going to see how increased customer expectations is pushing the industry to expand to bring their services on par i'd like to first introduce our final members starting with rami al-kharmi who is the digital cto of the apex group then we have mr damodaran rahman the chief technology and innovation officer of bayern payments limited we also have rana gujaral who is the ceo of behavioral signals who was with us last time as well for the voice tech summit india and we have mustafa seif who is a software team lead and vice president of efg hermes welcome gentlemen and this discussion is going to be moderated by carla vervee marin who is the founder and managing partner of smart voices smart voices of course is our partner for this initiative call of the stage is yours please take it away okay thank you very much uh welcome to everybody today we'll be discussing voice assistance in the banking and in the financial industry my name is carla i'm a founder of smart voices which is a dutch marketing voice agency and before i started this company two years ago i've been working at financial industry for about i think 20 years and i believe that conversational ai is going to have a huge impact on the yeah on this industry because the way we connect with customers and with employees it will change the next next years for me it's very special to introduce my four panelists for today and i think it's best if they introduce them themselves can i ask you to take the floor and i'm sorry okay sorry uh well uh thanks carla and it's a pleasure to be here uh i am the ceo of uh behavioral signals uh behavioral signals uh were were looking to unravel insights from the tone of voice so a variety of signals emotion signals like anger happen and sadness behavioral signals such as engagement empathy politeness and also intense signals and that's our core technology what we've done with that is we've built a very intelligent matching engine and the way it works is it analyzes recent interactions uh between agents and clients and creates very accurate behavioral profiles of those participants and then uses that information and knowledge to find just the right person to speak to the particular client and we've applied that solution towards collections conversations in the banking and the second tier debt market and uh that's a core focus area a pleasure to be here thank you so much uh that's very interesting uh down perhaps you could introduce yourself that's me demoed around so the viewers and the panelists thank you karla for this opportunity so my name is damodaran rahman short name is damon or basically my career is a you know rocket scientist worked 14 years in the indian space research organization working in the design programming control system what not and then my second stint i moved to ibm and i walked across the geographies name it north america south america europe middle east and last take you know a challenging role in the growing fintech so currently i'm working as a chief technology and payments limited at saudi arabia we are the one of the uh three fintechs in this region we started our journey we had graduated from sandbox to psp [Music] okay i think this connection is a little bit off but um thank you so much uh we'll move on to mostafa what's that please yours yes hi hi let's gentlemen uh hi carlos thank you uh it's my pleasure uh to be uh with you today on this summit my name is mustafa from egypt i work as a software team did at efdmas i'm responsible maybe for authentic projects and development of fantech projects and data science projects inside our company i have ten years of experience in software development especially the financial industry also efg hms is working on many financial services like investment banking stock market consumer financing management and any financial service it's the leading of uh financial committee it's my pleasure to uh with you today and about our discussion about conversation ai how to use it on a financial industry thanks it's great having you here and we have another fintech man awards neil thank you carla um and good day to everybody on the call my name is neil crutierfoy i've spent about 20 years in banking across investment banking asset management corporate retail last five to ten years really moved into a lot of regulatory work reg tech fintech um and i'm currently chief technology officer for a uh a new business which is due to launch in january um where we'll be offering a full digital banking service to corporates and institutional investors hopefully uh breaking the mold of what that means to the business in that space and look forward to talking with you all today great thank you listen of course now i'm very curious about what you're building but today we're going to talk about uh about conversational ai in the financial industry um neil perhaps i could give you the word how do you think conversational ai will affect the financial industry in the next coming years uh thank you for that so i mean obviously with the rapid move toward digital banking over the last five years both some challenges and incumbents the goals always needed to be without becoming more customer-centric um as all digital transformation aware um you know the evolution the story of banking services one that's come really from storm in the technology regulatory change customer mindset and sort of scalable cost effective services the consumer at large is significantly more savvier than they were 10 years ago and has a head of expectation service provision and what good looks like conversational ai is you know it's a critical part of this evolution and whilst technology is still it's in today there's no doubt and the importance is part of the banks over and you know that's going to escalate whether it's 24 7 support medium accessibility cost efficiency scalability or improved engagement you must look at its current capabilities as just one aspect of its potential and where it will fit customer journey experience and how it contributes to wider fintech ecosystem um i mean for example at one of my previous clients i was writing digital bank evolution he launched the ability for the customers for biometric identification as well as obviously part of a conversational process um and that's just an extension of how you perceive ai and conversational voice tech to be you know simply much more than a sort of a smart driven responder or chatbot the ability to interact with the customer to help streamline customer queries and provide services as an obvious part of the conversation it's services where the value adds start to develop goes for a computer and provider that we really want to get into so increase security is absolutely one of those as i'm sure rana will attest you know being able to interact with voice voice recognition pain and tone and emotion the customer is voice expressed or making a large bank transfer feeding this into backing and analyzing the patterns of behavior versus transaction types of significant protection to all parties and i firmly believe that privacy concerns will be far outweighed by the protection this kind of facility as part of a customer's experience and they must always be cognizant of their expectation and hiring clients who still want to speak even and service charges will reflect that so i think you always need to look at it at the moment a hybrid approach but you know it'll always be this option even in that case where paul recorded today continues to feed this into wider analytics to actually develop and evolve the processes and as the responses come from a trained customer representative that will also feed into how we develop these conditions i think the scenario is currently programmed will be an evolving storyline and yes today there will still be a need for human involvement to some extent especially when addressing customer complaints and bespoke queries but there's no doubt that the speed of which you know the evolution through ml and nlp is going to be faster than most people expect and as most people have been caught by surprise a lot of incumbents in the industry today have really been caught on the back foot by how quickly the technology has developed as i say through this perfect storm really started off in 2008 i suppose along with the support of all the technology to build up on top of that so whether you know interfacing through iot devices or online phone line customer support the data that can be drawn from these channels be far greater than traditional channels and will contribute to much better understanding so it's all part of a bank's digital offering i think that's a great understanding and i believe that rana is going to tell us more about the uh thing later on with mustafa you uh can you tell us what you think operational ai channels again which scandals are there and which one do you believe to be the biggest challenge yes uh according to our industry uh i think uh bailey the financial market me today that all clients need to make their transaction within seconds and no time consuming during customer service and all banks need to introduce their products in just the time format and speed up their services to accept more and more clients and expand the client base uh so the many challenges in in in conversation how applied conversation ai is through shadows but there are many pictures from chatbots especially in financial industry uh let's take an example from boats they usually is installed in financial institutions to film policies problems like frequently asked questions that in the sample code the main role for is to handle all frequently asked questions asked by customers and no need to make a repeatable response from customer service or centers to save time and save effort for for other complex issues another type of puts execution put the main role for this is to avoid waiting to hold for an agent to be available for supportive center operations quite automatically it transmitting them to support who can take a message customers to manage the details of their accounts and meet account their related quests in a single frictionless conversation support mainly work as retrieved customers customer information such as account balance payment due dates the most recent transactions and other related details to be ready for past responses also one of the more important uh the chatbot right composition financial industry is an on-boarding port on boarding what is a approach that can handle the importing process for clients that need to make new bank card alone as it can be simpler and faster and more confident using this type of chatbot this is a shortcut journey for example promoting a customer could be proof documents and information for capturing digital signature this this facilitates a proven process but also reduce the pitch in gathering and the transferring document um this is mainly the channel or conversation ai channels that can be used inside the financial industry yeah i think what you're saying also is that it's the repetitive questions there that people are asking which are easily or easily it's uh it's actually quite a job to fix that but exactly very good for conversational ai yes thank you thank you which brings me to the question because most of uh you told us it's also about scalability and about costs in the cost center reducing costs that brings me to the question can a conversational ai replace co-workers in an organization and actually do we want this to be that to happen perhaps this is a good question for you yeah i mean i think that's uh that's a complicated question i think uh you know if you kind of look at sort of the general spectrum of ai and that of course includes conversational ai for the most part most of the applications are in the realm of augmenting and helping the humans do what they currently do today but just do it better and so for the most part you know the aspects of ai are being implemented in automating mundane things and minimizing errors and minimizing mistakes but also sort of uh you know helping helping bring an additional level of capability or skills to the equation right so like for example in terms of sort of uh what we do like what what sort of where we're different from say the rest of the conversational ai spectrum um if you kind of see out there right there's a variety of different solutions in the market but for the most part if you really look under the hood what you see is uh intelligent semantic trees that are first taking the audio converting that into text and they're parsing the text for meaning and while that was really cutting edge 10 to 15 years ago you know it's really not necessarily uh the revolutionary technology that we're looking to do today and there's a lot more uh that you can sort of implement in the conversational ai space which is you know rather than focusing on what is being said you know focus on how something is being said and extract signals from that um now you know for example let's take an implementation right so you have an agent who is speaking with a client and uh if the if the agent's speaking with a client generally the agent's focused on the client that's what they're trained to do they're focused on how the client's doing how the client's feeling so the agent doesn't necessarily need a lot of help uh to sort of uh you know have somebody or or a software remind the agent in terms of hey the the client's feeling angry the agent knows clients feeling angry you can hear it you can sense it and you can also sense the tone of voice you know but but what the agent's not doing is focusing on himself or herself um and so they're not necessarily aware that they sound angry or they're not necessarily aware that uh they're speaking too fast or they're speaking too slow or they're cutting the client off because they're focused on the client and so now if you have a capability that sort of is guiding the agent in terms of how they're doing it becomes uh it becomes a compelling tool for an agent which is oh you know um maybe i should course correct uh or maybe i set something and if there's a system that's sort of monitoring the general engagement in you know and sort of sort of tracking a change of tone from negativity to positivity or positivity to negativity and something sad was said that that resulted in that that change of engagement uh that is really helpful right now what we've also done is uh we've sort of taken that core signs of emotion and behavioral recognition pushed it a little further right so if you sort of process those basic signals and then you apply to a specific context you could actually predict intent and although that sounds like magic i mean it's really you know traditional behavioral sciences that that has been studied by a scientist and doctors for decades and so for example um you could very much predict the intent of the person you have on the phone so like for example if there's a client that's looking to buy or not buy you could predict if the person is going to do that or not um or if you're looking to collect debt you can predict if the the collect that you know the debt holder will pay or not pay so our engines typically can make a prediction within the first 20 seconds of the call and that prediction is a binary prediction yes we'll pay or not pay or buy or not buy and the prediction is about 85 accurate so it is really really powerful right i mean and it's really sort of like you know if you sort of uh um you know sort of hone in into uh the cognitive state of mind of the participants and then apply it to a specific context uh there's a variety of uh information and insights that come in and so i think those are the things that apply so it's less about replacing a human because the humans need it right as neil said right i mean the quest for digitization is real banks want to digitize banks want to minimize cost but fo the most part the high value conversations and the more complex conversations like let's talk about the collections industry right it's a very uh unique interaction between each client every person's situation is different every person's debt is different uh the solution is going to be very different so you can't digitize a collections conversation which is probably one of the most complex conversations out there uh by creating a self-service portal and you need to talk to a human understand that humans dilemma come up with the solution agree upon a middle ground and then make it work the question is how can ai help with that i can can you can you add an element of empathy in there can you match make and you can you bring the right people together so that you can have better conversations and i think it's all around sort of augmenting those interactions it's very little about replacing and personally i think for the most part i've come across very little very few use cases where ai has actually replaced a human you know for the most part it's completely the opposite at this point and i think that's what it needs to be at this point because yeah i've i've worked with several companies and also the the issue of natural language understanding often is a big issue because sarcasm for example is something that's difficult for bots to understand and to interpret uh for yeah to understand that uh how this works and to give the right intent yeah on that point i mean i think that's an interesting point that you bring up i mean and the language itself right uh so we speak differently all of us because we're from different parts of the world but we think pretty similarly and we reflect emotions in a very similar way right so like for example when we're looking at the tone of voice and extracting signals from that you're now building a solution that's truly culturally and language agnostic and uh because you're not focused on the language at all and you know we're not interested in what you're saying or how you know we're just interested in how you're saying it and for that matter we're not even you know paying attention to what you're saying or the words you're choosing to speak or the language that you're speaking in and because you know while we speak in different tones different pitch tones we all reflect emotions very similarly and that's very very powerful great thanks interesting stuff most of our perhaps i can go to you what do you believe are the main challenges for the financial industry to focus on for the next few years yes the main challenges for conversation ai apply it on the financial industry i think the first challenge would be the language uh the different languages especially on the on the multinational companies that have a variant cultures clients the language will be the main challenge of this area and you have to develop a port for every for every language to study and to learn the quotes about the signals for each each language and the body of each language i think this will be the main challenge another challenge is the consumer expectations when it comes to money related matters consumers are highly sensitive and expect knowledge consistent and customized customer service the bank have to be extra vigilant meeting those expectations also avoid any disciplines also regulations regulations consider as one of the most important uh challenges in applying uh chatbots and comprehension ai and financial industry that we see that many banks spend a half month money on developing systems and processes and two compliance also one of the most important challenges how to surprise and add authenticate as users are going to use conversation ai and chatbots also also this is this is a main challenge especially on security teams on on national industry but there are many methods to avoid this challenge like digital signature and like biometric as fingerprint facial or voice of nations just all methods that can be used to thrive and authenticate the users well so it takes the courage and persistence also to face all those issues and all those challenges yes yes it's something recognizable in my experience uh working with different companies it's not something else that let's start a conversational ai today and in a few weeks we have this thing live and then we're going to do something else it's it's a philosophy it's a way of working and changing your organization [Music] i think that's an important thing to keep in mind when you're working with the conversational ai yes this was the questions for damodaran but i think he's uh he has some technical issues but perhaps neil you could also answer this question uh what are the latest developments on payments using conversational interfaces is that something you are i've looked at in part um i'd say he'd probably be better better at answering this one at the moment but you know absolutely i mean this is one of the things we're making transactions i would say the largest part is going to be around security and authentication uh is going to be a large part of it yeah but i'll uh let you jump into that now we were talking about uh payments in the conversational ai yeah yes yes basically okay great see when we talk about the banking and financial sector right so all the advancements which is happening the changes are happening very rapidly and your core banking and the infrastructure and the you know your application has to be named and you know agile and and secure very very importantly because we are talking about the money right and the fintech startups are the basically it's giving the solutions to the you know uh the banking experience of going to the branch standing across and all those things and we are seeing the evolution of you know digital uh transformation in the financial industry and pretty much i think few years back i think we visit bank nowadays i never visited bank for last couple of years right so everything has been done there and having said that i think now we talk about the digital banking today you see there are a lot of conversational uh you know aids which is helping uh to have the basic queries in terms of customer what they want to know about their stuff for example you know amazon google and facebook basically they have their own you know voice assistance which can be integrated with the banking and things like that but uh in this particular area now i am in your fintech basically we have a digital wallets and then payment gateway and if you really see basically the very i think it's a technical issue can you hear me now yes we'll give it one more time can you hear me now yes we can hear you now we'll give it one more try the floor is yours yeah okay quickly i'll just get into yeah no i'm sorry this is fine no no the sound isn't it's not so the chatbots are the you know basically that's nothing uh i'm sorry it's about the customer expectations um most of our perhaps this is a good question for you do you think a conversational ai will increase customer expectations in the next years yes i think it will be increased customer expectations because it solves the most problems that related to customers and banks from customer point of view the main issue summarized in long time waiting in queues to make transactions through banks and also atms and the wrong steps taken in using internet banking and mobile banking and from banks and financial institution point of view as a heavy workloads every day that bank publishing new uh new product and the ability to stand from many this consumed time and can be used to handle many other complex cases that need human interaction so uh i think that conversation ei can uh uh make uh uh transformations on financial industry uh in the next uh in the next years and and that requires immediately without any movement from him to the bank and waiting for the fuel so i think conversation ai will be a distribution on the next days okay it's quite some interesting uh thing and do you believe that if companies do not [Music] use conversational ai in future they will be in business in a few years or will be out of yes i think my company uh put a plan put a good plan for use for use conversational ai on the next month and put a budget for this uh to handle such these projects okay thanks thanks a lot we're going to try again a demo for you uh i have the question consumer adoption is an important barrier to cross in the netherlands i know and that uh talking to a voice assistant or you're using a chatbot it's um i think something that people have to get used to uh what do you think about customer adoption is how are we going yeah can you hear me now hope uh internet supports me i'm working from office anyway right so customer adoption is the key basically i think when the digital transformation is going particularly in the payments so you may be seeing the history right so the digital wallets have come in and then perhaps there are multiple wallets and then the customer association and the retaining of them is very very crucial and it's my experience also from last two years i think uh we did the customer acquisition and then if your competitor comes in with a better uh you know user experience and uh you know the the things like backs and loyalty program and all those things i think your customer segmentation will move there so when the technology is going forward and it is much more important to retain your customers within yourselves right so that's that's becoming a very big challenge um and most of the digital wallet perspective which you want to talk about it's a cash burning uh exercise right you don't really make money rather you need to do the acquisition through giving their cash back and things like that so that's when this year what we did in buy and be perspective so payment is our core and with that what we can do so always i believe in two things one is an innovation and second is the disruption so what we are trying to do is we so we developed three platforms in terms of you know the transportation the mobile e-commerce and the chat okay it's it's a so-called amazons and you know e-commerce platforms and things like that so basically our use case is all about keeping the customers uh very happy in terms of the value added system which we are giving across the uh your payment arena and also keep their experience so initially we started with you know call centers which are manually intervention and you know in digital wallets if some of the intricate questions in terms of some of the frauds and things like that people are not able to give the right things then people they are not happy right so we are just moving towards initially we are in the very nascent stage of adopting and and port which is called arab part and our goal is to really look into the behavioral aspect as rana was talking about so we are we would like to capture the behavioral pattern it varies from the culture and the place and things like that when we have the sufficient data we will curate our machine and machine will learn and then we want to have the a based uh stuff so today basically i think uh the chatbots are uh well enough enabled with the ai power and we need to have a sufficient data to make it work for us so customer adoption and retain is big challenge and these uh technologies will disrupt unless otherwise you give them a great experience you will they will shift their base absolutely okay thank you we've had questions from the audience i think uh rana this one for you to um to answer how do you take into account the various cultural deviations and contexts okay yeah that's a good question so um look when i was talking about this earlier right so when you're looking at uh you know measuring signals uh emotions and behavioral signals from the tone of voice uh what you're really doing is uh you're sort of uh looking at the tonal variance you're looking at balance and porosity tonality and um you know the the key there is that although different cultures speak uh in different tones um sometimes there are you know their culture some cultures speak in higher picture tones and there's some who speak in softer undertones but the variants from the bass lines are almost identical and so when you're working on a brand new language data set so let's say you're working on a data set that you've never worked before you need a small amount of audio sample that that is required to recalibrate that baseline once you calibrated that baseline which can be done fairly quickly with a small amount of data set the variance from that baseline is very very similar across different cultures across different uh you know [Music] different languages and so that's what you've seen and so that actually truly makes this uh you know capability of sort of understanding the state of mind from the tone of voice language and cultural agnostic okay i hope the question is answered thank you very much hannah sure next question i think neil this one is for you do we want conversational assistance to be more human although you risk ending up in the uncanny valley yeah because people they can uh doubt if am i talking to a real person or am i talking to a voice agent no it's very it's a really it's a very good question and i think you know especially when it comes to financial services and money trust is a key thing right i mean that that's ultimately why you go to a bank because you trust and believe in their security and their services so people won't want to feel conned into talking to a robot if they do that i think that trust will be lost to some extent or they will feel uh like you know can i rely on these people because they're they're they're not being truthful with who i'm talking to so it must be addressed up front um and i think certainly right now we're not there yet as everyone knows this is this is the start of this journey um but it will you know we need to feed this kind of context into the initial journey options of how people interface with these systems and i think the ability to migrate customer expectations at a comfortable rate can't be overlooked um in the same way that we sort of vary charges between paper and electronic statements so the same approach will have to shift early adopters into the new technology um you know in the medium to long term consumers unlikely to go back once they actually sort of realize the benefits that are occurring and the hyper personalization that can come from this and the fact that you know we already mentioned people talk to siri and alexa devices shows that the consumer's open to dialogue with voice day and can differentiate between human and computer but i do still think that distinction is important um and we need always you know to help people know who they are talking to i think if you got it too perfect i think you know people might lose some trust there yeah yeah the other way around also i remember i googled saying and that was something that people didn't uh appreciate very much because it was too human-like yeah thank you very much um mustafa uh you've been working on some cases in the of the last few months perhaps you can tell us what your most inspiring case for this audience audiences yes let's share with you some some cases from my company that i devised as a case in two parts stock market stock market market board and consumer financing port let's start with the stock market we know that a stock market station have a limited time and the call center resource is limited so so we have many online platforms and many clients need to contact call center directly for frequently asked questions like what is the stock trend today and the account opening process news for a specific stock and what is the next coming uh ipo all these questions take long time from call center and the consumer effort that can be used to work with with another client on complex uh and how to manage this to order what's the best price uh for uh uh to place the disorder on stock and other frequently asked questions but it can be used to respond all frequently asking questions and reduce the workload from a call center another another uh live case from uh from uh stock market um in stock market we have uh r d department that spent long time uh technical analysis and funda ental analysis to prepare a good recommendation for the client uh but all this analysis is done before the stock market session uh but uh what about uh during the stock market session what about the analysis during the stock market there are teams staying long time in front of news channels and the published videos uh threads and news and make analysis for it so uh it will be a worse if we have an ai solutions that convert this all these speeches and translate it to texas to make sentimental analysis uh and give recommendations for the uh traders uh what is the facebook and the what is it this is about stock market station in in consumer financing we have a product value value is a product that used to make installments for the clients using a credit limit we grant it to them we're on the end of our time okay okay okay i see something looking at me very strictly now yeah okay well i think i have to finish this uh this conversation it was really fun and uh interesting talking to all of you thanks a lot for the audience for joining us and uh of you feel free to uh connect with us uh besides this session thanks a lot thank you guys thank you thanks everybody thank you okay of course all of our speakers are available backstage and in the vip section so if any of our viewers like to interact with any of our speakers all of them are available backstage but until then thank you very much to all of our panelists thank you everyone you're welcome all right ladies and gentlemen we are going to slip into a short networking break for about five or ten minutes and when we come back from the break we're going to uh we're going to learn how to use voice technology to identify what is it that customers really want from a brand perspective all of this and much more on the other side of this very short break you