The financial landscape is evolving rapidly. This is creating new opportunities for firms, but also new challenges. Technology and operating models need to evolve if Operations is to keep pace with the changing needs of the business.
This was the central theme of a recent fireside chat between James Maxfield, Chief Product Officer at Duco, and Bhaskar Raj, Vice President at DWS Asset Management. Raj, who leads reconciliation operations for APAC and EMEA, shared his insights on a multi-year journey of moving off legacy technology to embrace a culture of innovation and operational excellence.
“A key focus of my role is how to transform the day-to-day operations that we have,” Raj explained. “Talent is another key area. How do we empower people to be part of that innovation journey and achieve what we want to achieve for the organisation: adding value to our clients?”
The conversation serves as a blueprint for financial institutions looking to modernise their middle and back-office operations. DWS focussed on scalability, employee empowerment, and the removal of technical bottlenecks. By doing so, they have demonstrated how a shift in technology can lead to a fundamental transformation in mindset.
The challenge: Legacy technology left behind
For decades, many asset managers had to rely on reconciliation platforms that were designed for a different era of finance. As Raj noted, these systems served their purpose in the past, but the environment has changed.
“Our clients' needs changed, the Operations needs changed, and the regulatory landscape itself was becoming a challenge. We needed a platform which is agile and which is modern to address some of our fundamental challenges.”
Raj highlighted that legacy platforms often failed when confronted with modern data, especially as the needs around “core data issues” became more complicated. The legacy systems were too rigid in circumstances where Operations needed to build a customised rule or transform data.
Bridging this gap was often a manual task. It left the Operations team unable to proactively tackle issues and manage risk.
“If I'm spending my time doing manual and repetitive tasks, I will always be in a reactive approach,” Raj explained.
Change management bottlenecks agility
As with many organisations, the change management process at DWS involved going through the IT department. This way of working is designed to preserve control. But there’s another reason it exists: legacy systems are too technical for anyone but highly-trained developers to build or iterate processes.
Yet the IT team were fielding demands from across the organisation. Their development queue was long, and requests from Operations could be stuck in the pipeline for weeks or months.
“The challenge for Operations is that we have a number of things that we identified that we want to improve at the start of the year, but we're always in the queue,” Raj explained. “We have to give tons of justifications to make our case, but there are also other divisions who have needs to be met.”
“Our technology team are great partners, but they have their own set of challenges as well during the year.”
Even small changes had to go through this process. ‘Time to market’ for new reconciliations was therefore slow, meaning the Operations function lacked agility, despite the speed at which the business needs changed. As Raj recalled:
“It was very challenging to even introduce a new rule, to improve. So the journey was quite slow.”
The goal: Scaling capabilities without scaling costs
Automation is often touted as the solution to rising costs, but not all automation is created equal. Raj pointed out that "incremental improvements through automations" on legacy platforms aren’t scalable.
“If we had to stay on the legacy platforms and were not able to make changes, we would continue to increase cost. As the business grows, demand would increase within Operations, and that's not feasible at all.”
Scalability in a legacy world usually means headcount growth. This is because the shortcomings of the technology require significant manual effort to address. Operations teams play the role of ‘Human APIs’; pulling and keying in data, reconciling on spreadsheets, or managing shared inboxes.
So, even if a legacy system can scale in the face of growing volume, the number of errors it produces, and the manual tasks required to cover the edge use cases it can’t automate, scale too.
Raj had a clear vision for scalability at DWS:
"If in the next two years our business grows twice the size of what we are today, can we do the same operations with the same set of people that we have instead of adding more headcount and costs? We need to have better systems, better platforms and do more with the same headcount that we have.”
The migration: Embracing no-code and tackling "shadow IT"
The decision to migrate to Duco was driven by a need for agility and control. Moving to a modern, no-code, cloud-native platform empowered the Operations teams to build and iterate on processes quickly.
“Getting Duco fundamentally changed the way we work, because it gave us the control to manage the process and build new rules ourselves".
The move supercharged agility, replacing the often months-long IT development queue with much faster, Ops-driven processes.
“Key to the innovation journey is the speed to market,” Raj said. “In the legacy world, a journey of delivering efficiency is a whole year, and then you may not even make the levels [of efficiency] that we want to make.”
“[With Duco] the innovation journey was faster and we became more agile. There was a period where we were introducing new rules almost every month.”
The benefits of a cloud-native approach extend beyond just speed; it allows for a more integrated view of data. For DWS, this meant being able to address upstream data challenges directly within the platform. For example, the team were able to use the data prep module, rather than waiting for IT to build a pre-processor for complex SWIFT messages.
A surprising discovery during the migration was the sheer number of ‘shadow IT’ processes that existed outside of the core reconciliation platform, Raj said. The team had various processes running on Excel, often supported by complex macros.
Such macros are fragile, opaque, and difficult to audit. DWS was able to automate these manual processes with Duco, because the platform is flexible enough to adapt to changes and complexities in the data. This consolidation allowed the team to "shift our focus to risk management" rather than just managing the tools.
Managing the transition
Transformation is never without its challenges. Raj acknowledged that the project faced complexity, technical hurdles, and a "status quo mentality" along the way. It’s not surprising that there was resistance to change - it’s a natural human behaviour, especially given that Operations is “in the business of trust”.
Overcoming this resistance required a cultural shift and a "step-by-step journey".
One key strategy was starting with a complex but high-impact use case: cash reconciliation. Successfully automating a difficult process provided the proof of concept needed to win over stakeholders.
Managing the regional differences in risk appetite was also crucial. For example, in APAC there is "zero tolerance for risk," Raj explained. But the team used Duco’s customisation capabilities to set stricter tolerances and workflows than might be used in other regions.
Addressing these specific regional needs enabled DWS to build consensus. It also proved that Duco was able to enforce a greater level of operational control than legacy governance processes.
Empowering the workforce
One of the most profound impacts of the transformation was on the employees themselves.
"Apart from creating value, making our operations efficient, for me, it was about how it helped empower the people within the team."
The team at DWS was eager to embrace the change, as it gave them the opportunity to learn something new, beyond the confines of their day-to-day roles. The no-code nature of the platform meant that "there was no IT knowledge required," allowing operational experts to develop their own workflows.
This shift has long-term career benefits. It gives employees a more holistic understanding of the business, as they have to know the process from end-to-end.
“This journey opened up a lot of opportunities. We were able to understand the processes and functions end-to-end; how the upstream systems work and how it impacts what we do, and then after, how the downstream processes work, and how it gets changed. That understanding improved because we started looking at things holistically.”
This broader organisational understanding will pay dividends as the industry moves toward an agentic future powered by AI. These upskilled individuals are perfectly positioned to manage the AI agents that will further automate the mundane aspects of the job.
“I think the skill sets that we created in the team - where they not only understand the function, they understand the platform, they know how the rules, and how the platform works - when we move into the agentic world, they would be able to transition into playing the role of oversight on the agentic processes.”
Measuring ROI beyond simple cost savings
The complexity of a financial institution’s tech stack can make return on investment (ROI) a difficult thing to measure. Legacy systems have a lot of hidden and indirect costs that stretch far beyond the licence fees.
But DWS is able to measure the impact of their data automation journey in several ways. First is the cost-income ratio, which is a very important metric given developments in the industry. “The margins are shrinking,” Raj said. “The cost-income ratio becomes a key driver for our success. If we have to do that, we need to be able to have better systems, better platforms, to do more with the same headcount that we have.”
"If we had not made that journey [to Duco] then we would really struggle to meet the targets that we get in terms of the cost-income ratios".
Scalability is another key metric: the business can now scale without the increased demand automatically translating to additional headcount in Operations. “If the volumes continue to increase because of growing business or market volatility, am I able to operate optimally?”
Risk reduction also shows the impact of data automation, with the Ops team moving from a "reactive" to a "proactive" approach to risk management by eliminating repetitive manual tasks.
This can be clearly measured in the number of spreadsheets or other end-user computing (EUC) solutions replaced with automated controls on the Duco platform.
As mentioned above, the total cost of ownership (TCO) for legacy software can be tricky to work out. One aspect that is easy to measure is the amount of IT resources or additional vendor support that is no longer required.
A clear and easily trackable metric that proves the impact of migrating from legacy systems to Duco’s data automation platform is match rates. Before the move, the team were achieving match rates of 60-65% with their legacy platform. Since moving to Duco that has risen to 80%, with the team now targeting an 85% match rate.
The path forward
The journey at DWS is a testament to the power of challenging the status quo. They have moved away from legacy technology and embraced a modern, cloud-native approach.
Data automation has raised their match rates, reduced manual tasks, unlocked true scalability, improved the employee experience - and more. Operations are more efficient, more resilient, and future-proof.
What advice would Raj give to others considering whether to replace their legacy system with a data automation solution? He summarised the points he had made earlier into three main areas of focus.
The first was scalability: “Is the legacy platform efficient enough to scale with the growing business?”
The next was around addressing some key challenges of dealing with data. “Data is core to everything that we do in Operations. Can [your existing system] address the challenges that come with data in terms of transformation and quality overall?”
And then there was the cost element. Does the cost of maintaining legacy systems “really help the cause to deliver value to the business and the end client?”
If the answer to these questions is ‘no’, then perhaps it’s time to start your own data automation journey.
