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Walter Obermeier - Launching fintech products at high velocity by reducing complexity

23 minutes reading time

Walter Obermeier our growth guru is back with us at Unbounded Talks to share his knowledge on unlocking technology in the enterprise, speed and agility of banks, Cloud integration and how we can get financial services firms to perform better, grow faster, and move with agility and speed. 

Celebrating his new role as Chief Revenue Officer overseeing sales and marketing and playing a key role in future growth with FlowX.

He’s a firm believer that the most important thing to support your clients and customers is moving at their speed. Because customers need a decision today and you need to be fast and adaptive and help your customers achieve their goals. 

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Walter has so much to share about unlocking technology in the enterprise and how we can get financial services firms to perform better, grow faster, and move with agility and speed. So we've got a little surprise as well.

Get ready to dig in for the growth equation. Walter, welcome to the show. 

Hey Mike, thanks for the introduction and for having me on your show. Great to be here. I wish I were recording this with you in person. Walter, I would hand you a special trophy to be awarded the first return guest on unbounded Talks.

This is an extraordinary moment, but Walter, I think what is most important to share with everybody who is tuning into all our listeners is that you just weren't satisfied enough as a strategic advisor to FlowX. And let's say there is a new chapter arising for you, so tell us more. 

Yes. There's a new chapter because I have been working with Flowx.ai for the past 12 months as a strategic advisor. I could see how big the opportunities for FlowX are and how they can deliver huge benefits to their clients. And I would say I think I need to be part of this journey. So, I need to add some of my experience and learn from the others in FlowX.

To boost a bit into this AI-driven technology and make a difference in the world and banking. 

So this means that you are hanging up the Strategic advisor boots and putting on new World Cup soccer boots. So tell us a little about the role you will be doing at FlowX.

So I'm happy to confirm that I took on the role of Chief Revenue Officer overseeing sales and marketing in the future. And also reshaping our market approach because we have already seen a huge growth in the last months. And we will see huge growth and possibilities in the upcoming 3, 4, and 5 quarters. And I want to be one of the guys who will help to run this efficiently, efficiently, and effectively so that we can cover the world and the regions that I'm looking for within the next quarters, almost at full speed and with full action, is what we want to deliver.

It is a hell of a ride.  Let me say it this way. Sorry for this will be a hell of a ride in the next quarters and I like this. 

Those themes of being effective and efficient, and that certainly is the challenge that a lot of the clients of FlowX.ai faces.

The financial services industry is constantly in flux and change. I think what we see at the moment is this continuous change of customer expectations outside of banks, insurance companies, and fintechs, and also that complexity on the inside, the technology, the tech debt, and compliance.

There is so much. Hey, let's talk about managing risk as well. There's so much going on for your clients. And they also need to land that efficiency and that effectiveness, so there's no surprise that a big part of what you and I want to talk about today is how AI,  artificial intelligence might play a role in that.

What are you seeing now as fintechs banks, insurance companies, and that broader financial services industry? As they look at AI, where are the opportunities, Walter? What are the questions in the mind of the CTOs and the bank exec? 

That's a long list. In the banking environment, as you just said, there's a considerable expansion of the regulation piece in banking.

There's a profound change in customer expectations. And if you try to adapt to all this change. So you are almost in a hurry to do this 24/7 in your systems, in your IT systems, because of the change, because what you delivered in January might be again changed and unchanged in February and in March.

This means you, you're running like hell behind these regulations, and even you can't fix, you can't fix what the clients are expecting from you fast enough. So the big trouble is there's a solution for that where you clearly say just put something on Cloud and run it in the Cloud, and everything is scalable and very easy.

If you are in the banking industry, you have some legacy systems behind which you need to maintain and which you need to connect. And this is the challenge to connect the old world from a bank and the existing world from a bank with the new capabilities and the new AI capabilities you have 

The funny thing is that when you think about these factors driving banks to consider AI solutions, you've not only got compliance, particularly if you act across Europe and North America. So you have different governance, different legal and compliance standards.

The interesting thing we've seen really change post covid is interest rates. And that plays such a big role in managing risks. So we've got real questions that are burning hot as the cost of money increases as we see that the financial viability of whom the banks lean toward comes under more scrutiny.

That has been a big surprise hasn't it, in the second half of 2022. The inflation factor has been another thing the financial industry has had to tackle. 

Yes And with your few words, our listeners can already understand how complex the banking world is.

Let me pick out only one or two of those things. So if you think about the regulation piece.  That's not only that you have to deliver all the reports to the authorities for the regulations. It's more about when you think about cost savings, if you do not deliver, how  much fine you have to pay.

How many fines do you have to pay if you deliver the wrong data? And if you have seen the reports about the numbers of fines, what the authorities are invoicing, we're talking about hundreds of millions of dollars globally. These fines, in the end, are killing the interest rate or what you have in the margin from the interest rates dramatically. 

Then one of the next points is when you think about fraud detection. You want to give money to other people. You want to give people  mortgages. Sure, you want to provide loans to make money, but what if you see numbers in that way? A bank needs to write off 200 million in mortgages because of not getting paid back.

This 200 million is a hundred per cent cost. Again, diluting your margin and others in the bank have to pay. It dilutes your margin, it also reduces your chance to be strong enough against your competitive competition. Against your competitor or even protecting the bank from losses.

And this is a huge challenge for everyone, only with these few things.

If you take into consideration non-financial risks. Technology risks in automation even than the continued regulation trouble. So that's a huge burden to the financial industry at the moment.

Yes. The cost of a mistake is high because if you're a bank, you get done on both sides. You lose margin and competitiveness, and attractiveness to your customers on one side, but you can also get dinged on the other side by regulators by compliance. So, the stakes are pretty high.

So this is what is driving banks and financial institutions to look at AI and what it can do. Maybe what we should do is look at the role that AI has played in the back office first, and then we'll do some of the front office customer experience pieces. One of the starting points is that you can use AI processes to know your customer, assess your customer, and detect unusual behavior on an account. You can do a whole bunch of things. Tell me, where do you see AI providing the most value? Is there like a? Is there a home run feature or function you see in ai, or is it more of a comprehensive pattern of efficiency that it can drive inside the bank?

There's one thing AI really can deliver much better than any time before, right? And it's all about data and analytics. If it's about data and analytics, it runs into predictive analytics. Experiencing and then finding patterns. For example, fraud for spending behavior and all those things.

And AI is that fast because I don't know how to say hundred x. 1000 x faster than people with manual processes as it was in the past.

So when it comes to  speed and high volume, AI is the right choice. The thing behind this, the AI needs to be very thoroughly set up. And it needs to be very thoroughly maintained, and you always have the newest solution in place, and you even control your AI solutions if they're doing right.  

Also, the second thing is so many new services are coming up that you don't have to reinvent the wheel all the time.

Even with AI technology or machine learning, you sometimes have reusable assets out there in the banking scenario, which you only might integrate into your process workflow. So you need more of the connectivity piece of your processes and your business processes in the bank to connect to these AI-driven solutions

And to have the onboarding piece, for example, with live video services on AI for face recognition, not from a picture, because this is no longer allowed. You need to have already moved. Video with people's faces that you really can detect. Is this the right person I'm talking to? Is this the passport he's showing me and moving back and forth?

So there are many things you need to maintain, but you always need to be up to date with the current technology, and that's a bit of an issue as well. Implementing AI in 2021 is a nice play, but you have to change it already in March 2022. Then within the new law from the EU regulations, you had to change it again in September.

So you only have three or four months to follow up with all the changes and necessary things using AI technology. So you touched upon something I think we've seen happen several times: organizations look at the benefits and prospects of ai. Still, they underestimate how important the planning and the setup of AI-driven processes is, how important the setup is.

Because if you don't set it up right, it. It's not going to serve the business. Correct. What's the point if one of our listeners is considering deploying a process and transforming it into an AI-driven process, and they're in those early stages? What's the one thing you think they could do well to avoid wishful thinking or catch down the road? What can they do to be better organized before they deploy their technology?

 First of all, they should always check and understand what the interconnectivity to other important processes is. So if I turn on the left button, what happens on the right side of my business?

 

 

The second is that I need to have a solution where I can change or adapt functionality or systems within days or maybe even real-time so that at any time, if I see something new coming up, I should be able to react. The same day and deliver the same day, a new solution or a new outcome for that.

One of the things I want, one of the things I wanted to build upon there, Walter, just as you were talking, what comes to my mind is so many time on times on these projects, what I see, and I want to see I want to understand what you've experienced, is I see the inadequate mapping. Of the processor as it is today.

Let's say you want to transform your KYC; my experience has been that it is. Rarely do you find a team with a really good map of their current KYC processes. They might have it in certain teams. One team has one part, and another team has another part. But what I find interesting, a fundamental idea is showing me the detailed map of all of the controls, flows, logic, et cetera. Across fraud, customer experience, technology, the business rules. Is this something you've also found that having fully up-to-date integrated maps of your processes is such an important requirement If you want to transform it? 

Yes, absolutely. And this is, again, something that you can probably solve with AI.

So if you have many resources out there, and it's mostly unstructured data, what you're just talking of in different areas of the client base and their IT systems, you can use semantic search.

 So you can use semantic platforms to gather and combine all the data you have at least. A full hundred per cent view of the solutions and the processes of your banking solution. And then you can craft and create new processes, new business processes with integrated AI. Probably within a few days. So the faster you can build upon that one, that's the way forward.

We've got a bit of a snapshot of some of those features and processes that can be transformed by AI risk assessment, fraud detection, anti-money laundering, KYC. Now what you pointed out is that it's really, where it's at its best. AI can help you with data analytics and understanding.

Give us a sense of some of the insights a financial institution can glean from its business. For example, what have you seen as the real aha moments when you do it right with AI on these processes? What is the gold standard for understanding that you can get from that data and analytics?

It depends on where we look. So if we look more on the risk side, you get the right data to understand how much clients have to pay, for example, unsecured landing. That my risk is covered with a higher margin or a higher interest rate. So how can I use AI and technology to cover my risks from different angles?

In using AI to make these predictive analytics on spending behavior from my client. So where does he spend his money, and why does he again ask for unsecured land or a bit of crucial discussion here at least in Germany, using the social data you can find?

The official data is on Facebook to understand what your client is doing and what clients in the US are doing versus what clients in the Apex region are doing.

 And these analytics will help you to understand who will pay back your loans,  who will not pay back, right? The same as if you use AI to predict anything that might happen when you have big data, this will help again save costs. To be more competitive, right?

What I'm always trying to say. These solutions are overall in place, and you can always focus on a few things like, as I said, AI for spending behavior and maybe even on social media content to understand how I can reduce my rights offs. So always be clear that there are interlinkages to something else. So I have a small example. A life example,  from myself, I was in Tokyo in a hotel on a business trip, and I was on Tokyo time, and then I looked at my agenda, and where I needed to be in two days and I didn’t  have a hotel booked yet, so I went on booking.de on my German website and found a hotel which suits me, and I booked my hotel, and it was fine. Ten seconds later, I got a message. Your credit card is blocked because of fraud detection. 

Because they said, we think that your credit card details were stolen.

So perfect solution for fraud avoidance, right? That no one can take money from my credit card. They made this assumption because I spent money in Japan in a restaurant the day before. And suddenly, I booked a hotel via a German website in the US, and I said, this does not work. So that was unusual behavior and unusual spending.

The trouble was Mike, I only had my credit card with me and nothing else, but in the evening I wanted to go to dinner. And how do you pay for dinner if your credit card is blocked. I tried to reach someone from customer service to unblock my credit card, and then they told me very nicely that they would do everything I needed.

It just takes 24 hours to reopen the system. So there I was 24 hours without food. Oh my gosh. See how you frustrate customers and they say, I don't care about your fraud solution. At that moment when I can't get something to eat. And now, this is the effort and the work that needs to be put into these processes.

Because you need to, in the end, serve yourself and your customers simultaneously. Because if it is only for your fraud detection, you might be the most robust fraud detection service provider bank in the market. But nobody wants to have their credit cards with them because they're always blocking them when you need them most.

But now you see what I want to achieve with the FlowX. Nobody can predict every situation upfront and code everything perfectly into AI, banking, or fraud systems. So at any time, such things might happen like what happened to me in Japan.

But what if you would have a platform or a technical solution where you say, oh, I can see case from Walter, that's not a good story, that he has to wait 24 hours. So I go into my system the day after I change the process for fraud detection and for unblocking the credit card with 24 hours back to 10 minutes.

And at that moment, when we have identified Walter as the right guy and the credit card, things are all okay. So 10 minutes later, the card is unblocked. What if you have a technical solution to do this in real-time and not ask for a change request, and then three months later, this bug has been fixed?

So what if you can do bug fixes in real-time in the running systems within a few minutes? 

Yes, because what happens is, people who are leading financial institutions, banks, insurance companies, I think they're, they find themselves held hostage to the backlog, don't they? The tech debt;  we'd love to do that, but there's a massive backlog of fixes. So what you're proposing is pretty radical because of what it affords. Banks, the opportunity to do with processes that become AI-driven, that use platforms like FlowX.ai is that they can fine-tune in real-time. They don't have to wait for the dev team to get through the backlog of all the previous months or quarters of bugs and fixes. 

It puts the tools in the hands of people in real-time so you can continue to fine-tune them. And is that the mindset you think of banking in the future? Is that it's this continuous product development continuous.

Enhancement of technology, continuous development. It's no longer writing the requirements, and six months later, something pops out on the other end. It's almost a new paradigm. 

Yes, absolutely. And not only continuous adaptation, but also fast time to market, right? If something new is coming up, we have a new product or a new product set that we would like to sell, and it's absolutely for today because it's short for Christmas, and we have the best idea ever on how to sell fx, for example.

If you would like to do that and would like to approach your customer, you should do that the next day and be able to sell or deliver the contract the next day. Guess now, if you go to your IT account department, say, can you please give me a landing page and can you give me the business processes behind selling the product sets and IT department says, with much backlog. Yes, I can deliver for Christmas 25. So 2025, right? Not 2022.

So not only adapt fast but also create fast but still how they have the connectivity to the underlying systems that you don't have to reiterate and re code the wheel from the beginning.
So, you will have a few things flexible in the Cloud, a few things on stable ground in your on-prem solutions. And the journey will start to move more and more into the Cloud, and the journey will start to move more and more into separate microservices. Not relying on a big monolith system that are not good for maintenance and change.

So let me ensure that I have decoded all those thoughts from you, Walter. So to summarize it as that we are now moving into this continuous way of working, this continuous development, continuous product development built on top of the data and analytics we're getting out of driving our processes with AI and platforms like Flow X. This is how we meet the fast-changing expectations of customers and the fast-changing world of technology and compliance.

This is the frame that you are proposing. 

Exactly right. Good summary. 

So that's huge. It's very exciting because it feels like there's a lot of liberation and freedom here. After all, I think we've worked with many folks at banks held hostage a little bit.

They're shackled. By all that tech debt and that huge infrastructure, they're just keeping going. And I think they would all yearn for that idea of that continuous real-time development. So it's super exciting. So when people want to go on that journey, what advice do you give them? If there are listeners right now, we want them to take technologies like AI and FlowX and put them into their stack.

Is there a book to read? Is there someone on Twitter to follow? Where do we find more? The conversation about this idea of continuous development and continuous innovation. Do you have any sources, recommendations, or wisdom for this idea of doing business continuously?

I can give you a bit of my experience, maybe of my history. So when I grew into a business, I had an excellent coach who always told me, Walter, always remember everything that you do, the key principles. So keep it simple but smart.

And keeping something simple means - don't invest in huge monolith systems and huge IT systems. If you can, put it piece by piece in the Cloud as a service. And then, you can adapt, change and restructure, and re-cluster the services into a functional business application. But you don't need to reinvent the wheel. You use them again. And have reusable assets that are not always duplicated. Data and pro-business processes. So that's  a huge thing to keep in mind; keep it simple and smart.

So when I recommend something to read, to open up your mind. I've been running for a few years trying to understand cybernetics management. And if you think about cybernetics, it looks more like you control your environment. The machines or, in analogy, living organisms. You only need a few patterns and sometimes only a few points to measure to run a very complex system like a living organism.

And I'm not talking now from mankind. If you only take mushrooms, something like that. But then you will see that they run complex structures with only a few inputs. And they can adapt and change pretty fast, too. 

So cybernetics and management and the art of transformation. Sounds like we've got a reason to have another podcast, Walter. 

Then if we did that, we would need to have a podcast for the next three or four hours, I think. 

To remind all of our listeners that Unbounded Talks is brought to you by FlowX.ai. So how can we deal with that insistent never-ending change that we see from tech, from compliance, from the expectations of customers. And one of the things that have come up so far in the show world, too, is we've touched upon the role of the underlying platform. Technology components are going to play here.

We've mentioned monoliths. We've mentioned the idea of biting off small bite-size pieces. Don't make it too complex and too big, which I think was excellent advice from you. But I want to talk about it now. The job to be done. What do we need to do when thinking about underlying inherent legacy platforms and technology, particularly when we want to deploy AI-driven processes and transform the back and front office?

But we have to refactor and modernize how where we start on this journey, and let's get inside this because I feel that we're obligated to our listeners if we're going to talk a lot about the potential of AI-driven processes and everyone's on board and saying, yes, makes great sense.

Let's do it. When we look at financial institutions, particularly banks, the whole thing here is the gotcha. Oh, the legacy system, the tech debt. So where do we start when we want to improve, refactor and modernize that infrastructure, that backbone? Walter shines a light on it. 

So my strong advice is don't start again with a big bang. So, if we have a monolith system that is pretty old and does not deliver the services and processes we need, start by taking out the first business processes and putting them into Cloud. Like I'm running a new landing page for unsecured landing or a mortgage.

And I will add to this business process some components that I have that are easier, faster and more secure and take the customer data and the deep tech out from the monolith systems. So connect them. New business process in Cloud , including AI functionality with the underlying system to have a fast solution.

The next phase is you take the next business process out and maybe in a timeframe of only a few weeks. You take out 60, 70% of the business processes from the legacy systems, from the monolith systems and put them as services into the Cloud; then you start to run and add that to the solution.

You start to run the old system, the legacy system, and the new processes in parallel. Until you can confirm consistency between data in the old system and data in the new systems in Cloud, confirmed consistency could be that you then say I only transferred 60% into the modern world in flux? But the other 40% in these legacy systems I don't need anymore.

That is his historical data. It's old stuff which no one else needs anymore. So I might use only the data or the database to store it historically. Or if I need this missing 40%, I might go there and say, okay, I will refactor. So my old system, my legacy systems, but I will only refactor 40% because the other 60% is already in the Cloud.

So suddenly, the workload for refactoring the old monolith system has shrunk from hundred per cent to 40%. 

 

 

This is huge, Walter, because what you are talking about is a paradigm of when you transform or refactor, don't start with the assumption that you need to take everything from the old and just put it into the new.

What you are highlighting for us is that there's going to be much overhead in old monolith systems that don't need to be ported either to the Cloud or to AI. So it's just inefficient overhead that can be made fully redundant. 

Exactly. And if you think about the data you want to use in the future, I'm saying run that in parallel. If you start the business process on the flux platform, then the modern cloud-native process takes data from the monolith system. Or you create data like a new customer. You read data from the customer from the monolith systems and update or even delete all on the monolith systems, but in parallel, in another new database.

Where you run the same thing. Now what you did in one system you do in parallel in two systems. That's just technology. That's just it. They can do this by huge numbers, but the thing is, after a phase, you can decide on your own, like after three months, after six months, or even after two years, you have a kind of smooth migration.

Without any big bang, you compare. Is there consistency by a hundred per cent or by 99.9%? And then you can say, okay, I can shut down the old monolith systems because everything is in the new infrastructure and new system in the Cloud. 

Okay. So we've made things less complex because we've reduced all of that overhead.

We've de-risked this a little because when we've thought about modernizing the stack and refactoring it, we've run them in parallel. We've seen any of the edge cases we've ironed out. Okay, done. Let's talk a little bit about how we can make this. Underlying obligation to the technology, more sustainable and easier to maintain.

How when we go cloud-native when we deploy a dr. AI-driven processes, how can we reduce what is common in banks? I understand, Walter, that they deploy a huge amount of funds. So keeping the lights on and maintaining the existing tech, how do we make it a bit more sustainable and maintainable? 

First, you need to cut the old systems into pieces, as I just said, because the biggest trouble is that they have all their processes, or old ones, coded in one system. I'm so sorry for this comparison now, but it's like Microsoft Office. So if I look into Microsoft Office, Me as Walter? I can probably use Excel, Word, and PowerPoint.

I use 5% of the functionality, and the rest is not necessary for me, which is a 95% additional burden because I don't know what to do with that. I would love to have such an office solution with 5% of the processes I need. So I would love a tailored solution and not pay for the other 95% because I don't need that.

The same is with banks. You have a vast IT system where you'd use maybe 5% for landing processes, another 6% for other things, but you don't need the hundred per cent of this system, but you still pay the maintenance. You still pay the infrastructure cost. Pay probably the license cost.
So you have a huge lump sum of costs, which you cannot allocate to the different offerings, what you do at the different departments because it's too big, to adjust and allocate to the departments.

It looks like you sometimes have a truck with which you can load 10 tons of data and processes, but you only need 500 kilograms. So why run a truck if you deliver 500 kilograms per day?

It's such a good analogy because to build on that, you pay for a license for all of these functionalities within Microsoft Office, but you use so few of them and what you are saying is literally, The financial services industry is often put in that same situation by its vendors, where it's like you have to take so much function and feature that doesn't directly contribute to the bottom line. Still, you are buying it, licensing it, and maintaining it.

So I think your invitation is to break it into pieces. Use, pay for, maintain, and sustain only the pieces you need for your business. And that's the key to being much more sustainable, making it easier to maintain. Because if you have less in the stack, then it becomes easier to focus and manage.

And I would imagine, Walter, there are fewer interoperability and co-dependencies if you can strip it back even just 10 or 15. 

Yes absolutely. And you get much speed in launching everything. So let us be with this analogy with the truck. If you have a tent on the truck and want to add AI or other functionalities to this big truck, you have to wait until the truck is everywhere, right?

And in all departments, if you have small cars or delivery cars, each can deliver 500 kilos instead of the truck. But. Four or five of them. The one is going to the landing area. The next one is going to have X. Then the third one is going to mortgage. And then you can add the right pieces for them, what they need and not for the big ones, right?

So you can run more tailored solutions with fewer investments and tailor them better and directly to the point. And adapt fast on that point then as well.

It's funny when you're talking, launching at speed; it almost brings me back to what you said before. So when we think about AI-driven processes, it does enable us to work in a more real-time continuous manner.

And that is exactly what you are talking about when you say launching at speed, working at speed, not only to be going from your sandbox to live but from. Version one to version 1.1 and one point two, and three and four, and so on. It's where you see that intersection between deploying the right technology to enable your business to move faster and to be continuous.

I guess my thing is what are the opportunities that happen, perhaps more from a business and entrepreneurial perspective, for a bank when they have this tool set, when they have the AI-driven processes, when they have refactored their legacy systems when they're ready to meet the obligations of customers and compliance, what do you see as the new business opportunity?

The thing is probably in banking, the business opportunity, if you're that fast in launching services, if you're that fast in delivering AI-driven services in banking, you might even sell or co-sell it to your competition. So if you have a perfect solution for unsecured landing, and you have the perfect AI KYC solutions behind that, why not take this IP and this asset you have and offer it to the market?

That creates new opportunities and markets that perhaps don't exist for you now because you don't have the capability, is that what you're saying? 

That's what I'm saying. Yeah. Or even take things like big bank banks, like Bank of America or German Deutsche Deutsche Bundes bank or government Bank.

Might deliver some solutions on AI-driven how-to for anti-money laundering and say, you know what? I'm asking all the banks to report money laundering. Here's an app for that, and it's proven technology, and we have invested in that. So you don't have to pay the total investment costs so you can reuse our solution.

That's quite a twist. It makes retailers and transforms them into wholesalers. Doesn't it? 

Exactly, but it's also government authorities asking for reports and you only need to adapt this IT solution, AI solution, to your banking systems and connect it with your systems, and you can be sure that you deliver a hundred percent correct reports for what they are asked to do from a legal perspective.

And Walter; that sounds like the essence of efficiency, effectiveness. So that you talked about at the beginning of the show, didn't you?

Exactly. And if you can run this on different microservices, for example, for anti-money laundering, you might understand there are many more things that we can share. 

For example in the supply chain, in banking. When you think about all the requirements that authorities have for banking and how banking tries to support and drive this regulation and deliver the reports for these regulations, you have 20, 30, or 50 different results coming back to the authorities for AML.

Why? Instead of delivering the solution for the reports, add and connect them and get a hundred percent reports back, which are all equal and compliant. Can you imagine how much money you can save? 

Particularly at the scale that financial services firms work at. Towards customers in the front office and the back office towards compliance. Third parties know your customer, open banking. It sounds like there's a world of opportunity if you have the right mindset and are willing to meet the needs of customers and the business if you're willing to deploy.

Technologies like AI to transform your processes, get the data and the analytics, be continuous in how you build, strip back, refactor and modernize the backend, break it into small pieces and to have that continuous mindset, you'll have a much more sustainable, maintainable way of working in your bank or your insurance company. Still, you'll be able to launch at speed and creates new opportunities and markets.

That doesn't even appear on your horizon today. 

Yes. And then having a platform like FlowX will support you in your journey, right? Who will give you a chance to connect all the underlying systems, no matter if you connect your underlying system to your bank? Or you might even need to connect with the authorities and their systems to align the data and align on deliverables or on data analytics that don't only analyze your data and the bank, but you can also analyze big data that you would get from the authorities or the government? 

So you see, there are many things that you can do if you use a platform like FlowX to connect the different dots in a process in the Cloud and then even have the chance to retire the underlying systems and move to the new.

Walter, I think we've brought this full story circle. Very exciting. I guess my question is, now that we have brought a world of opportunity to our listeners to rethink technology, business and financial services if they want to find out more about you, can they find Walter Obemeier on LinkedIn?

Walter, this was fun. I am so glad we got a chance to announce your new role and get into the vision and how we can transform financial services together. I hope you enjoyed chatting about it, and I do feel a great deal of excitement.

When we see this kind of vision deployed into banks, you and I have seen so many times the struggle that executives in banks and insurance companies face, don't they? 

They do, and they need help. And this is why we are here.

We're trying; we are here to help and support. And this is why I'm very thankful that I had a chance to work on the vision for the upcoming years, because there is much more to come. Much more to come. We have a little AI technology in the back that we're working on, and hopefully, we can deliver next year.

That is exciting. Walter Obermeier, CRO FlowX.ai. 

Thank you so much for sharing your thoughts, ideas, and vision with me and our listeners today. So thank you to you as well. Our listeners, this was Unbounded Talks, powered by FlowX.ai. If you want to know more about the show, you want to get the show notes, the transcripts, and all the goodies.

Head over to unbounded.flowx.ai

All right, that's a wrap. 

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FLOWX.AI is part of IBM Cloud for Financial Services. See listing and more details here.

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