By Chris Peacock, Head of Marketing.
When we first started developing the Reconciliation Maturity Model at the start of this year, we envisaged (and had seen) a fairly slow progression through the stages towards the utopian end goal of a self-optimising, machine-learning enabled process. Since then, however, global events have had a significant effect on the pace of that progression.
As a recap, the Reconciliation Maturity Model outlines five key stages to maturity:
- Manual: All reconciliations carried out manually, using spreadsheets, or via home-made applications.
- Hybrid: One or more point systems in place for specific data types. Other reconciliations carried out manually.
- Automated: All reconciliations consolidated onto one or more automated systems. Risk is reduced.
- Improving: One automated intelligent system reconciles all data. Additional data quality controls are active throughout the data lifecycle.
- Self-optimising: Full automation enabled by machine learning across the entire lifecycle of a reconciliation – from onboarding through to exception resolution.
While most businesses remain in stage 2 (hybrid) the pandemic has increased the urgency of moving to consolidated automation of their reconciliation processes.
This acceleration was prompted by changed working practices and has taken place against a very difficult backdrop. Covid-19 has forced many organisations to rethink the big topics, such as business continuity, operational resilience and data management, in order to adjust to a world where most employees are now working remotely.
Right across the globe, the financial sector has been forced to make significant operational changes – that would usually have taken months or even years to deploy – in the space of weeks or days.
Competing in a changed environment
With customer needs shifting and business priorities suddenly refocused, we’ve seen many of the long-held barriers to fintech adoption fall pretty quickly. And while a rapid readjustment was necessary to keep organisations running smoothly and compliantly earlier this year, this is much more than a short term fix.
As the year has progressed, it has become obvious that workplaces are unlikely to make a complete return to normal ways of working, and that a more fundamental rethink of how to better achieve compliance and operational excellence is needed.
One major question is how effective deployment of technology can help financial firms achieve – and retain – a competitive edge. And so the real debate is no longer “are cloud-based solutions safe?” but “how can my firm thrive in this new environment?” – and fintech is at the very core of that solution.
At Duco, we’ve seen a rapid increase in platform adoption since March, and our biggest clients are now peaking at 60 million lines of data processed every day. Needless to say, the customers processing the largest numbers are the big, global institutions with the most rigorous security measures in place.
The drive for collaboration and productivity
The requirement for teams to access company data quickly and efficiently from their homes is a major driver for organisations to seek out more effective, intuitive IT solutions – but it isn’t the only one. More than ever, teams need to be able to collaborate remotely.
A reliable data management platform that empowers dispersed operational teams to work together, while simultaneously reducing the possibility of human error, is key to maintaining productivity and reducing risk as the working world transforms. And the ability to implement these improvements without placing unnecessary pressure on already-stretched IT departments will further support organisational resilience and growth.
These are not only trends that we’ve seen at Duco, they are also key topics for industry working groups. For instance, the notes from the ECB Operations Managers Group’s September meeting focus heavily on the advantages that major global banks have seen by deploying smarter fintech solutions to their operations. These include the positive impact Duco’s own solution has had in transforming reconciliation, and the benefits of AI in supporting processes such as OTC matching.
By exploring new solutions and techniques, these organisations are improving efficiency right across their respective companies, and are better equipped to manage change, even from a distance.
In pursuit of automation
In a world where firms are increasingly operating in a digital environment – and with no signals that this situation will change anytime soon – forward-looking firms should look to address three key barriers to automation:
- A lack of standardisation – In many cases across the wider financial services sector, there are no strict data standards. For example, different counterparties provide trade and position data in different formats. Traditionally, each one would require a bespoke reconciliation process or expensive data normalisation. There is a need for intelligent technology able to normalise different types of data with ease.
- Increased complexity – Cash or stock assets can be matched on a few basic fields, but much more information must be taken into account for more complex products. Most current systems are unable to deal with every asset type that crops up in a timely manner. And that’s before we get to the range of data needed for regulatory reporting, and the associated reconciliations required. A fresh approach is vital to keep ahead of the curve and ensure compliance.
- Poor data quality – The enemy of automation. Missing fields, inconsistent coding schemes and unavailability of common keys make automation difficult when using current solutions, due to hardcoded assumptions within those systems. Techniques such as fuzzy matching really come into their own here, enabling users to match data without the need for a defined schema or primary keys, making effective and reliable data management far easier.
Those firms that do make it to stage three of the Reconciliation Maturity Model will then find the transition to stages four and five much easier, as all reconciliation is automated and the data is digitised. They then stand to make the greatest gains in terms of responsiveness to market changes, regulatory compliance, cost reduction and customer service. In short, the ingredients for competitive advantage.
To learn more, download the Reconciliation Maturity Model.