Now more than ever, businesses are investing in digital transformation, but many don’t focus attention on transforming data processes as part of this. But data plays an integral role in every aspect of the financial services industry; whether it’s in reporting to meet regulations, analyzing the risk or predicting long-term business goals.
So, if data informs every aspect of the financial services industry, why are so many firms still struggling to manage data effectively and, more importantly, why aren’t they investing in measures and tools to facilitate change?
The Problem With Manual Data Reconciliation and Legacy Systems
Manual processes bring the element of human error to data reconciliation. Repetitive manual tasks can become tedious for humans, which can impact concentration levels and threaten the consistency required for good data management. In making errors that require fixing, employees are also increasing the time spent on each task, on top of the time they are spending manually reconciling the data in the first place.
Businesses still using manual processes also plan their workforce’s size based on the expected amount of data they need to reconcile. This becomes an issue when external events result in data spikes. The team size cannot be instantly increased to handle the spike.
As well as taking additional time, manual processes can also cost financial services organizations a fortune in regulatory fines as a result of inaccurately reported data.
By failing to comply – or prove compliance – with data regulations, financial services organizations may miss out on external investments and funding due to seeming incompetent or high risk.
Increasing digitalization –especially in response to the pandemic– has only served to accelerate the problems with manual processes because organizations are creating more data than ever before. This acceleration has also unearthed issues for firms who continue to rely on legacy systems, as these are often unable to handle large influxes of more complex data as quickly as Cloud-based systems can.
The inefficiencies created by these legacy systems and manual processes add up to a whopping amount. Our recent “State of Reconciliation” report –which surveyed 300 heads of global reconciliation utilities, COOs, heads of financial control, and heads of finance transformation working in large financial services organizations across the UK – revealed that on average, poor data reconciliation is costing USD 142,790 per financial service organization, as a result of wasted resourcing and other inefficiencies. But despite this, a huge proportion of organizations –nearly one in five (17%)– rely wholly on manual data reconciliation.
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Why Are Organizations Still Reliant on Manual Processes and Legacy Systems?
Many financial services are struggling to move away from restrictive legacy systems because of resistance to change from the organizational culture.
Replacing systems and processes that employees have been working with for years can be tricky, even if businesses can see that these processes and systems are inefficient or prone to error. Often employees have a resistance to change and are used to or comfortable with these older processes, so are happy to continue with them, despite apparent flaws and delays.
For others, it’s simply that the legacy systems and manual processes are so deeply integrated into their organization and have been over many years. There is a perception that ripping out these legacy systems is a daunting task, costing a large amount of money and involving a process that takes place over years. Many don’t realize that continuing with these inefficient systems will cost them more in the long run.
However, more and more businesses are now beginning to recognize the importance of investing in transforming their data management processes and are looking to prioritize this in their digital transformation efforts moving forward.
Our research found that almost half of businesses (46%) say data reconciliations are more important to their business in 2021 compared to previous years, and a further 45% say they are actively investing in ways to improve data reconciliation.
Intelligent Data Automation (IDA) platforms help financial services organizations to achieve their goals in improving data management processes.
Automation reduces the level of human intervention required in data management. This not only increases organizational speed and agility but also frees up an employee’s time to focus on less menial tasks allowing them to add more value to the business. And with clearer reporting and insights thanks to automation, the data businesses produce can be used more effectively to foster innovation.
IDA enables businesses to control all financial, operational, and commercial data across the organization in a holistic way. And as IDA platforms can be customized to sit alongside legacy systems, it is ideal for financial service organizations who are not keen on making the big decision to rip out legacy systems, whilst also gaining the data benefits of doing so.
Our data reconciliation research shows that already, two-thirds (66%) of financial service organizations expect solutions that automate manual processes to be one of their top investment focuses over the next three years, whilst 68% plan to have fully automated their reconciliation within the next five years.
This increased focus on moving away from manual processes and legacy software is a huge positive for the financial services industry, one that will save them from the potentially costly ramifications of incorrect data, especially as data regulations continue to tighten.