We recently attended PostTrade 360, where we hosted a panel discussion featuring insights from two of our customers – Michael Mortensen, Managing Director at Danske Bank and Neco Dusseldorp, Global Head of Fund & Admin at Bolder Group – and our CEO, Michiel Verhoeven, led and moderated Andy Grayland, Head of Solution Architecture at Xceptor.
The session, “Looking beyond operational efficiency: building the business case for automation and AI” explored how financial institutions are leveraging AI to unlock value, reduce risk, and scale operations. With over 150 attendees, and standing room only, we’ve captured the key takeaways from the session below.
Andy opened the discussion by asking the panellists to reflect on how they define value creation beyond operational efficiency. Both highlighted the importance of people, internally and externally.
Michael from Danske Bank explained that automation must begin with employee buy-in. “First thing is, it’s important that colleagues buy in to the journey of automation. We spend significant efforts and investments in people – including skills and training – before we start talking about trade performs in the lifecycle, because we need to make sure we have our people on board and it’s extremely important to train and make people comfortable,” said Michael, General Manager at Danske Bank.
Neco Dusseldorp at Bolder Group echoed this statement from an external standpoint, “For us, we’re a service provider, so we need to cater to the needs of our clients. They have more technology at their disposal, and we know what our clients want. Consistency is one of them, and AI helps with that. What our clients don’t like are surprises, and AI helps to minimise surprises, which in turn helps us to improve our client experience.”
A recurring theme was the challenge of moving from theoretical discussions about AI and automation to tangible implementation. Michiel noted that success depends on the clarity of outcomes:
“The real question is, how do you get the outcomes you have in mind? One of the things I enjoy about our relationship with Danske and Bolder is that we’re very clear about the desire to create visibility across the lifecycle of a trade, a product, or a client. It’s important to have that focus and not just be one-dimensional.”
Building on this, Michael gave a flavour of how Danske Bank approached automation in practice.
“Running a bank is focused on getting the right risk to reward, and we’ve now got a much better risk picture for the service. Before the use of Xceptor’s AI document reader in the tax service, we had people looking through double tax saving treaties, trying to find the right answer to a very complex product. Today, with the AI document reader, it’s a very speedy process – you configure and then you get the answer.”
Neco at Bolder Group emphasized the importance of aligning technology with people – both internally and externally – and the benefits the Bolder Group has seen.
“For us, at Bolder Group, it’s really important to stay abreast with our clients’ operations,” said Neco. “They have technology at their disposal, they use it to differentiate themselves amongst their competitors and to increase their efficiencies, to increase volumes, to differentiate their offering to investors, which makes it [automation] more complex than all technology could bear. So, we need systems and tools to help us deliver our services to our clients, and we also need our people to stay abreast with that and be in control of what the technology can do – that is what I think is really important for us now – to make sure that technology advancements don’t go faster than our workforce.”
Vendor selection emerged as a critical factor in successful automation, as the next each panellist explained how they chose the right partner.
Michael from Danske Bank explained that while products are important, the decision process often goes beyond product capabilities. “Products need to be market-leading if we want to work with a vendor. But being explicit as a vendor about what you cannot do is a rarity. If you don’t have a vendor in front of you who is clear about what they can and can’t do, is a problem moving forward. Those discussions at the beginning about whether there is or is not a fit are extremely important.” Michael continued, “It’s also important that we understand the practical vision of the vendor. We must have good dialogue with each other, and how we think you can develop your products, and that’s super important to us. Beyond that, we look at the culture of the firm and how it fits with Danske Bank. If we’re engaging with a vendor that doesn’t have a good cultural fit, it’s not going to work.”
Michiel echoed this theme of transparency, as he explained Xceptor’s view on choosing partners, “Everyone says they want automation, and if you want to win at a small company – like ours – you have to be very good at what you do," he explained. “If I want to convince clients to partner with us, it’s because of our domain expertise in capital markets and the specific areas you have products with. How you get there is a lot to do with an honest dialogue of what your product can and cannot do. That level of transparency in a partnership from a vendor and client is very important – you need to be very committed to what you say you’re good at, not saying we can do everything now."
With so many competing priorities in financial operations, Andy asked the panellists how they decide which projects to focus on and what drives that decision-making.
“Data quality is extremely important,” explained Michael from Danske Bank. “If the data quality is not good, our work with AI and GenAI will be tricky as you’re automating something you’ve not understood.”
He shared a proof of concept (POC) that Danske Bank is currently working on as an example: “We want to understand how our trade platform performs through the lifecycle. We have T+1 down the line, we have pressures to scale, so when someone executes a trade with us at night, we want to understand how it performs – how long does it take to tap it in, what systems does it hit on the way, where does it fall off, and how can we make that a better customer experience? We’re trying to take the basics – data quality and go from there.”
Neco from Bolder Group added that their prioritisation is similarly shaped by the industry: “We see a few industry trends. There’s regulation – some in more than others – we see monetisation of asset classes; there’s always new asset classes where fund managers wish to invest. Then there’s technology.”
Both panellists agreed that prioritisation isn’t just about operational efficiency—it’s about strategic alignment, data integrity, and client-centricity.
To wrap up the session, Andy asked the panellists what trends they foresee over the next two years and what recommendations they’d offer to businesses navigating this space.
Michael from Danske Bank was first to offer up his thoughts, explaining, “Invest in tooling and don’t be afraid. In Danske, we have invested heavily in tooling, GenAI, and AI from the outset. We are training people, but don’t be afraid because it’s quite exponential. The third would be to think about your customers very heavily, and as you do these things, you must have your strategy clearly aligned in front of you.”
Neco continued with his thoughts, “AI is a bit of a buzzword, but you need to have a plan. Just “AI, AI” is not going to hack it. Decent governance around it and focus on what it means for your clients and your people is important. Just implementing a tool for operational efficiency may not be very tangible because there’s always the aspect of culture within a company and your clients, and that’s also something to factor in to make sure it’s being utilised, and that’s what we think is very important. You can easily invest, but making those investments effective and successful is the key to success.”
Michiel closed with a broader reflection on the future within the industry, “We are a 20+ year old software company. Every software company is getting totally disrupted in how you build software. What are the core questions we’re solving for? Whose problem are we solving? And do we still do it the right way? From an innovation perspective, and asking ourselves really the core questions – what do we need to solve for, not just the incremental stuff.
He quoted Dan Reid, Xceptor CTO & Co-Founder, linking back to what other panellists had said, “The problem isn’t AI. The problem is your data reliability and the flow of data underneath it that you really need to address. So, whether it’s agentic AI or any other capability, you need to address the data flow; otherwise you’ll fail.”
With a final thought and recommendation, “Please have a business case that’s outcome-oriented, as it’s very, very important.”