Podcast: Automation and machine learning for banking excellence
A rigorous understanding of banking processes, innovation and technology give Ingo Zimny a cutting-edge in his role at DVB Bank
Photo by Max Langelott on Unsplash
From early on in life, Ingo Zimny says he wasn’t the best at any one thing in particular. Instead, it was Zimny’s knack for connecting processes and ways of working across subjects that led him to find career success in the banking sector through process excellence and automation.
Today, as vice president of IT at DVB Bank, Zimny works with a team to design solutions and the processes behind them. This high visibility over the whole banking process, he admits, probably sets his team apart from IT departments in other banks. “It’s about listening to others,” he says.
“We are seen as enablers to get things done more efficiently in the bank, whereas in other banks, the drivers are coming more from the business units.”
In this episode of the AI Network Podcast, Zimny explains how his team is leveraging automation and machine learning tools to meet their demands as they’ve got a fair amount of unstructured data. It’s a shift that he says is moving them closer and closer to artificial intelligence (AI).
“If you look into the different AI technologies, I’m curious about the extent to which, for example, speech to text could help us.”
Tune in as Zimny shares insights into his experience in automation and financial services, as well as how to determine the cost benefit of solutions based on the size and scale of clients.
Seth: This episode is supported by the AI IA Network. The AI and Intelligent Automation network is an online community focused on building the intelligent enterprise. Content covers a broad range of issues, including digital disruption and transformation, task and robotic process automation, augmented intelligence, machine learning, and cognitive computing. Our goal is to help businesses apply these technologies and build the intelligent enterprise of the future. Go to aiia.net to join.
This episode is also supported by RPA and AI week 2017. The world decision makers and doers and process excellence and shared services meet in London this November to collaborate on the direction of task automation and augmented intelligence, share best practice and discover strategies, tactics and initiatives, which industry leaders are already implementing for business success. 2017 is our second year of bringing this growing and exciting industry together. Go to rpaandaisummit.com for more.
Seth: Vice president and IT for DVB Bank Ingo Zimny joins us from the RPA BFSI Summit where he shares that providing solutions is not the only thing that his group does. They design those solutions and they design the processes behind those solutions.
Ingo and the team like to challenge the way things are done. They try to streamline processes to set the base. For more efficient throughout the bank generally. As he and his team add more services as they get deeper into the bank, they're finding that automation and machine learning are tools that meet their demands as they've got a fair amount of unstructured data. When source and cognitive solutions, Ingo's concern which he admittedly needs to validate is that the cost benefit of the solution in question is based on the scope and scale of the client in question.
Welcome to the AI and Intelligent Automation Network on B2BIQ. I'm your host Seth Adler. Download episodes on aiia.net or through our app on iTunes. Within the iTunes podcast app in Google Play or wherever you currently get your podcasts. Ingo Zimny.
Ingo: That's essentially a Norwegian name or it stems from a Norwegian name.
Seth: Interesting. All right. It stems from a Norwegian name. Is it usually longer?
Ingo: No. A bit ...
Seth: Okay. I feel like I've heard of Ingva. Maybe in classical music? No.
Ingo: Maybe. Also God of War.
Seth: Oh. There's also that one.
Ingo: Not the most lovable guy.
Seth: You seem much more lovable than that. I can say immediately.
So we were in the workshops yesterday together and we're here today at the RPA and AI BFSI event.
Seth: Right? For those who appreciate letters.
Ingo: And abbreviations.
Seth: Yeah. Now you come from a bank. And so everyone always assumes that it's a large institution.
Ingo: Which it isn't.
Ingo: If you would call an institution of 600 employees large then it's a large one but for a bank it's rather small institution.
Seth: And that's fine. But everybody says you're a bank, you've got all this money. No, no we have 600 people. How much money ... So you have to do things differently than what would be foisted upon you from others. You have to be nimble, so to speak. Is that fair?
Ingo: Yes. Essentially face the same challenges than every other bank with respect of regulations. But we are different in the sense that we are only doing B2B business. So that's kind of rare. And we only do that type of business which leads to a different needs within the bank regarding process automation or so forth.
Seth: Before we get process automation let's just talk about process excellence. I have in front of me, you're the vice president of IT. Everybody wants to be friends with the vice president of IT because you're the only guy that knows how things work. Is that fair?
Ingo: Not exactly. Because we have several vice presidents, even in IT.
Seth: Fair enough. But do you take my point of you literally being a linchpin of the business, yes?
Ingo: Yeah kind of. We are probably different than other IT departments in other banks.
Seth: How so?
Ingo: Because we have a high visibility of processes in the bank. We know them quite well as an IT which is probably not always the case. Listening to others. And with that also knowing about technology we are seen as enablers to get things done more efficiently in the bank whereas obviously other banks, the drivers are coming more from the business units. But as having the technical skills, understanding how things work together. And knowing processes it puts in quite interesting situation to help the bank with services which we can provide.
Seth: And you are almost in essence doing two jobs at the same time. For a bigger bank who has the business side and the IT side, those two sides are in one cranium. Those are two sides of your own brain.
Ingo: Again different to other banks potentially. Providing solutions is not the only thing we do because we design them and we design the processes behind. If you look at present processes we are not taking them one by one to implement an IT solution for it.
We challenge the way things are done. We try to streamline processes, to set the base for more efficient work throughout the bank generally.
Seth: How long have you been in this role?
Ingo: Seven years.
Seth: How long have you been at the bank?
Ingo: Seven years.
Seth: Okay fair enough. As far as processes that you have designed along with those IT solutions, give us an idea so that we understand the scope of the work that you've been doing over the past few years.
Ingo: How much time do I have for that?
Seth: As long as, you tell me, I'll edit it down to whatever.
Ingo: Where did we start? Kind of greenfields, so if a front office of a bank was working very manual with very minimal system support, which was a good chance for us because we didn't have to break walls on that side at least. So we have built up a serum system which was essentially collecting the data which was not collected in a structured manner before. So what are the opportunities, what are the clients? What is the status of opportunities? How often did we fail, how many opportunities went well at the end? And supporting essentially the most crucial processes in that whole process chain. So that's where it started. So we had to build up the pipeline of the bank.
That's across divisions. Which are shipping offshore land and aviation in our case. Doing that one division after the other we always concentrated on streamlining the processes in that different division. Meaning we on boarded the first division and if we came along with the same process in the other division we challenged them quite a bit to ask why do you do it differently. To largely come around with processes which were streamlined across the division.
Which is essentially my eyes for basis for the very next step which had to follow and which we are presently probably in is to add more services on top of that data. Of that solution.
Seth: How so?
Ingo: Because we are getting more and more deeper in the bank. We are getting not away from the front office but we are also tackling middle office and in certain cases you could even think already about the back office processes.
Seth: The front office is becoming further back. Not that you're getting away from it, it's just continually getting closer to the back.
Ingo: Yeah the solution takes more processes into consideration, so if a front office remained as it is, it's the sales organization essentially. But we took care of processes which start in the front office and go deeper into the organization afterwards. So as I said we started with a serum system. Probably we should not call it an XRM system because I said we take care about processes which are far away from being customer relationship management and processes.
This is a very natural, if you follow that path very naturally it comes to a point that you think about automation again and potentially also about machine learning. Because there's a lot of information all the artifacts which we collect in those different processes which we automate it and support.
Which are unstructured. So that's where one aspect of AI comes into play.
Seth: Certainly. The CRM though implementation, the strategy execution then across different various departments which becomes then XRM, sounds like you're still working on it. How long have you been doing that for?
Ingo: That's hard to tell. Cause ...
Seth: When did it even begin? It's always been going type of thing.
Ingo: It started seven years ago.
Seth: Fair enough.
Ingo: Having the first division on the platform, we were ready for the next step for them but we had to onboard the others.
Seth: Indeed. So this is a great example of continuous improvement. We've just been doing the same thing over and over again, continually improving the processes that we do by understanding what you do, to ensure that what you do is actually optimized.
Ingo: Right. Doing that repetitively showed us that we largely have done it right at the surface stage. But it was not a very exciting phase to do the same things again and again essentially, it was more doing what you already did. But that phase is over now so all the divisions are on the system and that's the point and having set the basis, having very similar processes. That's the point where you can really move forward.
Seth: So when we talk about RPA or AI automation in general how different is this in your mind than what you've already done. And by that I mean how much is exactly the same?
Ingo: It's hard to tell. If you talk about RPA it's essentially one of the most populated reasons to do it is essentially to bridge the gap between systems and avoid double input of people because you have collected the data already a first time. As I said we started from a greenfield. We have largely taken care of that aspect of already. So if data is collected once we generate through the relevant systems as much as we can so far via APIs.
Bridging the technology gap which our big banks probably have, having mainframe technologies in place and other systems, and for all the different purposes different applications. That's not the bridge or the gap we have to bridge.
So that is why RPA we have to find another use case for RPA if we want to apply it. There's potential for that topic but I presently think it may need to be accompanied by some AI technology.
Seth: Something cognitive.
Ingo: Because as I said we also work with a lot of unstructured data. That's where it could potentially grab information out of a text and no one has to manually input it anymore. Not even a first time. And that's the points where my present thing is heading to.
Seth: Now what are they and by that I mean the solution providers telling you about how cheap it is?
Ingo: So I didn't ask directly yet.
Seth: Weighting in right? Dipping the toe in the water.
Ingo: So we heard a lot about real business cases and I believe what I've heard my concern presently is and I still have to validate if I'm right or wrong is the business case comes with very lightly with size of company. If you have a company where you repeat tasks a million times in a year and you take away 30, 40% of effort because you had the first shot of RPA, that's quite a number which you reduced if you go to a B2B bank with 600 employees, the initial invest probably pays back much later.
Ingo: That's the calculation which we potentially have to do.
Seth: And it certainly wouldn't be as obvious even when it's later to someone like your CFO who will say, that's it?
Ingo: It's not like you do it under the hood and after three weeks you say, "By the way our business case is there."
Seth: It's solved.
Ingo: You have to probably keep it under the hood for a longer while.
Seth: Indeed. Which is why you've got to jump to the front end yet again and do so in a cognitive way. It sounds like customer facing must be the way that you first go with this.
Ingo: Yeah right. That's another thought. If you look into the different AI technologies, what I'm curious about is to what extent speech to text can help us. Having the scenario our relationship manager is visiting our work client, jumps into the taxi afterwards to get quickly to the airport, the results of that meeting are completely fresh in his mind and presently he has to either type it into his mobile or wait until he's back or in a silent place afterwards again.
What hinders or should hinder him to talk the core report to his mobile phone, having a voice to text possibility link that texts to the client and with that you have prepared your core report already to the extent of 80%.
Seth: Done. Time saved. What's that?
Ingo: Ideally that would be the case.
Seth: Yeah. Issue gone. Sales person happy if it's possible. Right?
Ingo: And you can guess how happy they are about core reports.
Seth: Yeah exactly. This is a wonderful solution. Now have you spoken to anyone in that role at your organization about that type of thing? What if we could do X?
Ingo: I did.
Seth: Yeah, what was feedback from the frontlines?
Ingo: They would be quite interested. It's always the balance of generating the appetite and the capability to deliver. We know that this is coming. I personally don't know yet how mature it is right now. Besides that we have to consider some compliance aspects. Having a speech to text solution which is cloud based, faces at least we face at least some issues with that as a bank because if that translated text is stored somewhere in the cloud completely uncontrolled and from bank's perspective this may be an issue.
Seth: For us, for regulators, for anybody in between.
Seth: Right. All right so how do we have you as the VP of IT in front office and credit services for the past seven years, where were you before this?
Ingo: I was an Oracle administrator.
Seth: I see.
Ingo: Trying to optimize essentially operations on Oracle Administration.
Seth: As an employee of Oracle.
Ingo: No. EDS at that time which have vanished from the market.
Seth: Yes they were here once very loudly. And now I'm where, I don't know.
Ingo: They creeped into HP.
Seth: They creeped into HP that's a good way to say it. It's true. So did Compaq for that matter.
So you were doing that and then there was that change. Let's go all the way back. You're from Germany, where in Germany?
Ingo: Presently living near Frankfurt. Before that even more landscape. Close to a village which is called … which may be known in the US as one of the biggest army bases.
Ingo: That's close to it.
Seth: Got it. I have only been to Berlin so far.
Ingo: Which is a nice city.
Seth: And of course Dusseldorf on a connection. So I need to do more in Germany. What was it like growing up in Germany? It sounds like in smaller town life.
Ingo: Yeah it was. Good. So not really enough anything bad on it. The worst thing I can tell about is that my favorite sport would have been basketball and the nearest team was too far away to really go into practice there so that's why I ended up in football.
Seth: I see - as a participant you're saying?
Ingo: Yes right.
Seth: Did you have talent?
Ingo: Had some shots on myself.
Seth: So did you play at university?
Ingo: No. It's very different here. Sports don't play a real big role on university in Germany.
Seth: Did you play semi professionally in any way?
Ingo: Not even that. Not basketball.
Seth: But football?
Ingo: Football I played but it was really on the lower levels.
Seth: I see. Would you have been towards the front of the pitch or towards the back of the pitch? Defense, striker? What?
Ingo: Exactly in between, so connecting both, like now.
Seth: We learned it back on the pitch, now we know.
Ingo: The pattern of my life.
Seth: Fantastic. This is one where I just smacked you in the arm because what an epiphany. Did you ever get to the basketball court though?
Ingo: Yes. I made it once to an NBA game even. It was Nets versus Atlanta.
Seth: When was this?
Ingo: About a year ago.
Seth: So recently.
Seth: So it wouldn't have been when Dominique Wilkins was on the Hawks. Do you remember Dominique Wilkins?
Ingo: Yeah. The human highlight film?
Seth: The human highlight film. What I say Dominique Wilkins if you don't know who he is, he was exactly like Michael Jordan without all the winning.
Ingo: But the flying.
Seth: Bu the flying certainly, without question. All right when did you realize what you were good at, certainly fine we'll play some basketball, we'll play some football, but when did you realize what you were good at in your mind?
Ingo: It took awhile. The tragic about me is I was never best in anything and that's why probably I started connecting things which I understand quite well but where I'm not the best in any of the domains. That's where I'm quite good at.
Seth: So simply because you can't do anything extremely well you're very good at connecting the dots for everyone.
Ingo: That's what I try.
Seth: I can do a little bit of this, here's what you need to hear, here's what you need to know.
Seth: That's fair.
Ingo: That's it. Yeah.
Seth: How did you apply that at school? I would imagine science, math, where was it that came alive?
Ingo: Essentially I was a bit better at science stuff and mathematics. Just a bit less in language and the other stuff. But it wasn't really bad anyways, anywhere. That continued essentially during the studies where things which where I was not really good, and other areas where I was a bit better, nothing where I was really bad.
Seth: What I've learned, Ingo, in life is as long as you're not really bad at the thing that you're doing.
Ingo: Being above average is already a good thing.
Seth: Exactly, just be slightly above average and you'll be okay. At least for the time being because we are talking about automation aren't we?
When did you make your way into an actual IT department and how?
Ingo: It essentially started quite funny. So my father was coming back from work and he said there's an opportunity to study and you get money at the same time. So there's a different kind of concept regarding university in Germany which is you practice in a company and they pay you overtime and you then go to university and you're still paid by them. That type of study essentially brought some money in while you are studying.
And he said there's two possibilities, you can do engineering or essentially information science. You have to fill it out today because tomorrow you have to apply. So I had no idea what I was applying for, I was not too much interested in engineering so I put the cross in the other box. And then started to find out for what I was applying and it went down the route to be taken to go to that university, do my stuff and get me where I am.
Seth: So your father would have been basically in his forties at that time, right?
Seth: Yeah. So when he was telling you to do this I'm sure you were like, ugh, as I would've been.
Ingo: No he didn't tell us to do it. He just said that's an opportunity in the company where he worked with.
Seth: Oh it wasn't pre scripted, he wasn't saying ...
Seth: I took that the wrong way.
Ingo: No he just said that's an opportunity if you want grab it, if you don't want, leave it. As I didn't have any better idea at that stage I just filled out that formula which was not that big of a thought.
Seth: What did he do for a living?
Ingo: He was working in the company for oil bearings, so SKF is the name.
He was getting the machines into the right shape so that they can do the next production line. Jumping between machines and ...
Seth: Connecting the dots like his son.
Ingo: Kind of again.
Seth: I know it's a reach. What about your mother?
Ingo: She, what's the English word?
Seth: A saint. That's what I would call my mother.
Ingo: That's right.
Seth: Of course.
Ingo: So that's taken. The basis of my emotional skills.
Seth: Sure. The EQ. Right? The emotional quotient. You understand how to be a human being around other human beings cause of her.
Ingo: Yeah. At least I think so.
Seth: Exactly. You're doing the best you can. Likewise. Okay so I've got three final questions I'll tell you what they are, I'll ask them in order. What's most surprised you at work? I'd love an early on, in addition to what's most surprised you at work, I'd love an early on anecdote of someone coming to you in the IT department with just a ridiculous request, but we'll get to that. What has most surprised you in life is the second question? And on the soundtrack of your life, one track, one song that's gotta be on there. That's the third question.
So the first question is, what's most surprised you at work? But on our way into that can you give us an early anecdote of someone that works at the company coming in to the IT department and just asking for something that was just silly?
Ingo: I wouldn't call it silly because everybody has its background.
Seth: Fair enough. Everybody's coming from some place.
Ingo: I already give an excuse if that one isn't ...
Seth: Of course.
Ingo: No what was very surprising to me, we had a workshop about smart data. We talked through the topic a bit. Then I explained and I already felt dumb explaining it with the data warehouse capability we are able to draw the data of the past. Which I thought is very obvious to everybody and that was essentially not the case for anybody who was involved in that room. So that was kind of surprise ...
Seth: Why do you think? So in other words as you explain it, it makes perfect sense to me, I have the, I am blessed with the fact that I didn't have to do anything, but when I'm listening to you, why do you think they couldn't see what you were talking about?
Ingo: I probably they thought it's that amount of data can't be that this is in one box. I don't know.
Seth: Literally couldn't conceive of what ...
Ingo: They can't really oversee, and that's very normal the data which is there at present, and telling them that we can go back 10 years in time and tell you everyday how the data was looking like, that was a bit of a surprise to them.
Seth: Yeah. And also nice. Right?
Seth: Even though it was frustrating for you it was wonderful for them.
Ingo: It opened some gates in the discussions.
Seth: There we go. So understanding that anecdote what has most surprised you at work along the way?
Ingo: Most surprised then?
Hard to tell. Is it a surprise? It's essentially nice to see that if you come up with an idea that people are very open to it if you place it the right way, you can call it a surprise because you often hear that people are very defensive on change. But I think it's surprising how easy it is if you get the right point about what you want to tell them, then it gets easy.
Seth: If you find the way in. If you find the connection point. Connecting the dots, then all of a sudden you've got them. This is, the biggest detractors become the biggest promoters. This is along the same thinking.
Ingo: It is. It's essentially you have broken some walls on that journey. In recent years. And it became easy, before we had to really polish the knobs off the door. And now we are not closing it but we are running through our door in the meanwhile to get support so that's a nice change.
Seth: I have to remember we had to polish the knobs off the door. I have to remember that. That's good, that's the first time I've heard that.
Ingo: It's a Germany saying so it's not from myself.
Seth: Still I love it, it's fantastic. What's most surprised you in life?
Ingo: Surprised ...
Probably myself. What is most important for me in life is to understand that people are different. And that you kind of have to learn that there are people you won't change ever. People where it's worth it. Even if it is not worth it it's just their way of life. As long as we don't harm anybody just let them be. Why would I call it a surprise? I think there was a time in life I thought I could change everything. And that thought is vanished.
Seth: Yeah. I'm with you 100% on this. I think first, first, and I wonder if it's true of you. I thought everyone was like me. That was first. The first though. Then the second thought was, I'll be able to change folks. I'll be able to change everybody, anybody. Both of those things, 100% wrong.
Ingo: Right. A small difference for me as I have a twin brother, I didn't think that everybody else is the same because I have seen with my twin brother that there's a huge difference between him and everybody else.
Seth: And you for that matter.
Ingo: Yeah right. I reflected it to me.
Seth: Is it fraternal or identical?
Seth: So this is an identical twin and you have a different outlook. Because I know two identical twins, meaning two sets of identical twins. And I also know a triplet. The triplets, they're all different so forget about them.
But the two identical twins, they're similar, each of them. Each set are similar at the way that they go. And close knit. So it's interesting to hear that there's a difference in the identical twins.
Ingo: There's not much difference.
Seth: In the approach.
Ingo: If I've seen how he is and how the others are, and I knew that he's very very similar to me, I knew that the others must be different to me.
Seth: I gotcha. I understand completely. Now I get it, I misunderstood you. What you're saying is you used him as the control, as opposed to you being the control.
Seth: Yes. And then, oh, they're not the same so I guess I'm not ... that's interesting. So you had a jump start on me.
Ingo: On that topic, yes.
Seth: But just understanding that this whole universe is a wacky place and we're all different. We can evolve and adjust but we're all gonna be the same people that we are essentially.
Ingo: Yeah. Right.
Seth: Yeah. It is what it is, what are you gonna do. On that soundtrack of your life, Ingo, one track, one song that's gotta be on there.
Ingo: That's a hard one. Probably The Answer. By Bad Religion, don't you know if you know that one.
Seth: Oh sure of course I do. I'm old enough to know Bad Religion.
Ingo: At this stage I started listening that type of music, my English wasn't good enough but what I always got from it is don't believe if anybody tells you that yes, the answer to everything. That influenced me. So I'm very critical on things which I got told until I've checked my boxes to validate if it's true. And that's kind of one of the songs which had impact.
Seth: It's a perfect ... That's a great choice I think. Essentially that song taught you how to be an analytical person in some ways. Now when you said The Answer I thought you were going to be talking about Allen Iverson knowing that you have an NBA tendencies.
Ingo: Right? So I know his name too.
Seth: That'll be the next conversation another time. Ingo I very much appreciate the time.
And there you have Ingo Zimny. Clearly in a space, in a place where he can if he can find it, infuse cognitive solutions into his admittedly small to midsize business process optimization. So we'll check back in with him, thanks to him for his time, thanks to you for yours. Stay tuned.