Banks Still Struggling with Data Quality: Research

Although data continues to form the backbone of nearly all trading businesses in banks, new research claims that nearly two-thirds of banks are struggling with data quality and integrity and that the “poor health” of their data is impacting profitability and client service levels.

The research, published by Mosaic Smart Data, says banks are facing a challenge in getting their data to a fit-enough state to deploy AI-powered analytics to improve efficiency, productivity and profitability. The firms says it studied more than six million FICC transactions from banks in the Americas, UK, Europe, South Africa, Japan and Australia and then surveyed front office staff as a follow up.

Mosaic says the research and interviews revealed that 66% of banks struggle with data quality, gaps in important data points and that some transaction flows are not being captured at all. Further, 83% of banks have no real-time access to transaction data and/or data analytics, largely due to the lack of a central repository and 66% say that the data they find most useful for their analytics is challenging to access because it is fragmented or they have no access at all.

Half of banks also believe they have reference data that is unfit for purpose, with no unified counterparty identifier, especially for client static data, and sometimes the data is missing altogether.

These findings come, Mosiac observes, in spite of bank making “sizeable” investments in data management. It estimates that around $88 million per year has been spent by banks, but suggests there has been little return on investment in the front office, largely due to a failure to adequately aggregate, standardise and enrich data before implementing an analytics programme.

“As AI continues to evolve, so does the sophistication of the data analytics solutions it underpins – but before banks can take advantage of this, they must first address the ‘state’ of their data,” says Matthew Hodgson, CEO and founder of Mosaic Smart Data. “No powerful analytics or AI can fully function if data is not normalised, maintained in an orderly fashion and gaps in the data enriched. This must be addressed before an analytics programme can progress successfully.

“It is now a crucial time to invest in data and analytics to revolutionise the front office of investment banks – but ROI must be guaranteed in the current economic climate, and this begins with better data health,” he adds. “Making the right changes today can deliver significant long-term returns.”