Banking
Digital transformation, transform the data, and the rest will follow
Published by Gbaf News
Posted on August 10, 2018
13 min readLast updated: January 21, 2026
Global Banking and Finance Review
Company
Published by Gbaf News
Posted on August 10, 2018
13 min readLast updated: January 21, 2026
By Andrew Kouloumbrides, CEO at Xceptor
Evolve or face extinction, that’s the biggest challenge facing banks today.
We are at a fork in the road. But what’s the aim here? To kick the can a bit further down it, or invest in a digital transformation programme that will provide the solid foundations necessary to thrive and survive for the long term?
It is imperative to change the status quo of how banks have operated for decades, if they do not there is no way they can meet the very real but conflicting demands of banking today -to do much more with much less and yet most banks do not have the resources to carry on running their bank while transforming it at the same time.
To survive banks now must meet the ever more onerous regulatory demands and obligations; increase operational efficiency across the entire enterprise; and meet the rising expectations of clients who have embraced digital in every other element of their lives. They must also adapt to compete with the continually evolving challenges and disruption posed by the presumptuous new kids on the block, the agile fintechs which unencumbered by legacy technology and attitudes can laser target niche markets.
Limp wristed efforts that focus on cost reduction by say offshoring or chucking bots at inefficient processes will not get you there and ultimately waste more time and more money.
It’s not like chickens and eggs
From what we have seen, firms often focuson their desired end result, but with digital transformation projects, it’s deciding how and where to start that can often determines project success.
The experience of many suggests that beginning by primarily focussing on either processesor technology may not be the best route to achieving the intended digital transformation objectives.It goes without saying that learning from others’ mistakes can minimise the risk of repeating a costly failure already made elsewhere.
The problem with process
The overwhelming trend in banking revolves around reducing costs and increasing productivity and this is often process driven. But processes have tended to result from a fusing of existing legacy technologies, or quick fixes or often just because ‘it’s always been done that way’ rather than being created as best practice. If a digital transformation concentrates on process, then there’s a real danger that it will replicate imperfect existing processes and lock in more problems. Processes need to be overhauled and optimised, but there remains a need to ensure that the current processes are well-documented and understood by the transformation team.
Looking at processes through a data-first lens enables firms to re-imagine the processes.
Don’t tape it up with technology
Too many have started by focusing on technology. It’s true that picking the technology may be a route to quicker implementation but whatever is chosen will have strengths and weaknesses, and this would suggest that an amalgam of automation technologies would likely produce a better result. Virginie O’Shea, research director at Aite Group believes that best practice in data management and strategies for digital transformation involve establishing foundational data standards and taxonomies that are consistent across the business, and that “next generation technologies are only usefully implemented when the data you feed into them is actually fit for purpose – technology is no ‘fix all’ for a firm’s broken processes.”
Data first, second, third…
Data should be the initial focus of the transformation it holds the key to realising the key analytical insights into the firm’s business and its clients – to ensure that firms can derive the best value from it.Quite apart from streamlining work processes, increasing efficiency and saving time and cost, used properly it enables clients’ transactional behaviour to be constantly monitored resulting in quicker and more personalised services and advice. It can also strengthen risk management, enhance compliance reporting, and increase security by detecting and preventing fraud. Data needs to be at the heart of the transformation, so that the right data can be intelligently connected in the right format at the right time.
Here’s some real world examples of successful data-centric digital transformations.
Bots need data
A global investment bank identified 6,000 non-strategic back-office processes that it considered suitable for robotic process automation (RPA) to enable significant labour-intensive cost savings.But its bots could only access the data in about 1,000 of the processes so success was limited.
But if you can capture any type of data in any format, and we can, then all the data in the 6,000 processes became accessible to produce real-time consolidated reports, exception work queues and dashboards, and these are automatically distributed to users. This data transformation enabled the capture of internal and external data, including from the robots, and some of the 6,000 processes no longer needed to be processed by bots but could be handled directly by Xceptor technology.
Due diligence needs data
Another firm had multiple systems and repetitive manual processes, when connecting the right fee data to the right services at the right time, to manage its 400-page invoices. There were far too many processes and the fee data couldn’t be interrogated or validated making due diligence nigh impossible. The firm wanted to eliminate the risk of paying wrong amounts and to have controls in place to pinpoint any irregularities from month-to-month.
With a data first approach we could capture invoice data across all formats and channels and enable all the fee structures to be interrogated. Automated processes enabled line-by-line reconciliations and intelligent insights allowed the firm to identify high cost agents, high exposure to certain markets or agents, and any high cost trading activity and so align its procurement strategy accordingly.
Lessons learned
We’ve worked on more than 75 implementations in 20 countries for 45 clients and there are many- lessons learnt from our experience and one is that it is important to start with the priority projects and then to gradually broaden out to building longer-term capabilities. Another is that RPAs are best for dealing with simple tasks with structured data rather than complex end-to-end processes. Given that processes are typically made up of multiple tasks, RPAs are likely to be applicable to less than 30% of a firm’s portfolio of tasks – for example the KYC process may entail hundreds of tasks, so it’s important to use RPAs for the simpler constituent tasks rather than for the entire end-to-end process.
We have found that there are three key strands to a successful digital transformation project:
Business transformation powered by digital engineering
While digital transformation can speed up the development of new products and services and improve management decisions, it can also disrupt traditional business models, so it is imperative to regard it not just as digital transformation but as a business transformation.Follow the golden planning and decision-making rules to ensure that the digital transformation provides the solutions and versatility required, and it can genuinely transform an organisation. Labour and cost saving efficiencies, increased productivity and vastly enhanced automated analytical insights are just some of the prizes it will bring.
By Andrew Kouloumbrides, CEO at Xceptor
Evolve or face extinction, that’s the biggest challenge facing banks today.
We are at a fork in the road. But what’s the aim here? To kick the can a bit further down it, or invest in a digital transformation programme that will provide the solid foundations necessary to thrive and survive for the long term?
It is imperative to change the status quo of how banks have operated for decades, if they do not there is no way they can meet the very real but conflicting demands of banking today -to do much more with much less and yet most banks do not have the resources to carry on running their bank while transforming it at the same time.
To survive banks now must meet the ever more onerous regulatory demands and obligations; increase operational efficiency across the entire enterprise; and meet the rising expectations of clients who have embraced digital in every other element of their lives. They must also adapt to compete with the continually evolving challenges and disruption posed by the presumptuous new kids on the block, the agile fintechs which unencumbered by legacy technology and attitudes can laser target niche markets.
Limp wristed efforts that focus on cost reduction by say offshoring or chucking bots at inefficient processes will not get you there and ultimately waste more time and more money.
It’s not like chickens and eggs
From what we have seen, firms often focuson their desired end result, but with digital transformation projects, it’s deciding how and where to start that can often determines project success.
The experience of many suggests that beginning by primarily focussing on either processesor technology may not be the best route to achieving the intended digital transformation objectives.It goes without saying that learning from others’ mistakes can minimise the risk of repeating a costly failure already made elsewhere.
The problem with process
The overwhelming trend in banking revolves around reducing costs and increasing productivity and this is often process driven. But processes have tended to result from a fusing of existing legacy technologies, or quick fixes or often just because ‘it’s always been done that way’ rather than being created as best practice. If a digital transformation concentrates on process, then there’s a real danger that it will replicate imperfect existing processes and lock in more problems. Processes need to be overhauled and optimised, but there remains a need to ensure that the current processes are well-documented and understood by the transformation team.
Looking at processes through a data-first lens enables firms to re-imagine the processes.
Don’t tape it up with technology
Too many have started by focusing on technology. It’s true that picking the technology may be a route to quicker implementation but whatever is chosen will have strengths and weaknesses, and this would suggest that an amalgam of automation technologies would likely produce a better result. Virginie O’Shea, research director at Aite Group believes that best practice in data management and strategies for digital transformation involve establishing foundational data standards and taxonomies that are consistent across the business, and that “next generation technologies are only usefully implemented when the data you feed into them is actually fit for purpose – technology is no ‘fix all’ for a firm’s broken processes.”
Data first, second, third…
Data should be the initial focus of the transformation it holds the key to realising the key analytical insights into the firm’s business and its clients – to ensure that firms can derive the best value from it.Quite apart from streamlining work processes, increasing efficiency and saving time and cost, used properly it enables clients’ transactional behaviour to be constantly monitored resulting in quicker and more personalised services and advice. It can also strengthen risk management, enhance compliance reporting, and increase security by detecting and preventing fraud. Data needs to be at the heart of the transformation, so that the right data can be intelligently connected in the right format at the right time.
Here’s some real world examples of successful data-centric digital transformations.
Bots need data
A global investment bank identified 6,000 non-strategic back-office processes that it considered suitable for robotic process automation (RPA) to enable significant labour-intensive cost savings.But its bots could only access the data in about 1,000 of the processes so success was limited.
But if you can capture any type of data in any format, and we can, then all the data in the 6,000 processes became accessible to produce real-time consolidated reports, exception work queues and dashboards, and these are automatically distributed to users. This data transformation enabled the capture of internal and external data, including from the robots, and some of the 6,000 processes no longer needed to be processed by bots but could be handled directly by Xceptor technology.
Due diligence needs data
Another firm had multiple systems and repetitive manual processes, when connecting the right fee data to the right services at the right time, to manage its 400-page invoices. There were far too many processes and the fee data couldn’t be interrogated or validated making due diligence nigh impossible. The firm wanted to eliminate the risk of paying wrong amounts and to have controls in place to pinpoint any irregularities from month-to-month.
With a data first approach we could capture invoice data across all formats and channels and enable all the fee structures to be interrogated. Automated processes enabled line-by-line reconciliations and intelligent insights allowed the firm to identify high cost agents, high exposure to certain markets or agents, and any high cost trading activity and so align its procurement strategy accordingly.
Lessons learned
We’ve worked on more than 75 implementations in 20 countries for 45 clients and there are many- lessons learnt from our experience and one is that it is important to start with the priority projects and then to gradually broaden out to building longer-term capabilities. Another is that RPAs are best for dealing with simple tasks with structured data rather than complex end-to-end processes. Given that processes are typically made up of multiple tasks, RPAs are likely to be applicable to less than 30% of a firm’s portfolio of tasks – for example the KYC process may entail hundreds of tasks, so it’s important to use RPAs for the simpler constituent tasks rather than for the entire end-to-end process.
We have found that there are three key strands to a successful digital transformation project:
Business transformation powered by digital engineering
While digital transformation can speed up the development of new products and services and improve management decisions, it can also disrupt traditional business models, so it is imperative to regard it not just as digital transformation but as a business transformation.Follow the golden planning and decision-making rules to ensure that the digital transformation provides the solutions and versatility required, and it can genuinely transform an organisation. Labour and cost saving efficiencies, increased productivity and vastly enhanced automated analytical insights are just some of the prizes it will bring.
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