Getting Reconciliation Right In The Decade of Data

Fully automating reconciliation processes continues to be a hurdle for financial institutions, particularly when faced with complex data, multiple formats and changing requirements. For many, innovation in this area has stalled and a reliance on people power and spreadsheets remains prevalent.

Duco’s Douglas Greenwell recently spoke with Fintech Futures about the reasons firms are still finding reconciliation so hard – and the options that exist for those who want to consolidate systems, automate processes and take advantage of new machine learning technology. He believes that there are three key reasons why firms are failing to innovate in this area:

• A lack of standardisation
• Increasingly complex data requirements
• Poor data quality

This was the reasoning behind the creation of Duco’s new whitepaper: The Reconciliation Maturity Model (RMM). It’s a best practice guide for firms who want to move towards widespread automation and beyond; to achieve a self-optimising system powered by machine learning.

The RMM lays out five key stages of reconciliation maturity, with most financial organisations stuck at stage two, or the “hybrid” stage. Duco believes that moving forward requires a fundamental rethink of the reconciliation architecture – from point solutions that specialise only in certain types of data – to agile technology that can onboard and automate new reconciliations quickly and easily, even when presented with completely new types of data.

To find out more about the Reconciliation Maturity Model and how the right technology could accelerate much needed change, read the full article here.