Sibos 2023 has come and gone. Again! As always, the days were packed with presentations, discussions, events and conversations covering topics ranging from ESG (top of mind for so many firms right now), to technology and AI, to the growth in digital assets, to everything between.

What was clear is that data sits at the heart of global finance, and managing and leveraging this is top of mind for the industry.

T+1 is Going Global. Eventually.

An animated talking point at Sibos was the promise of a world in which all capital markets share the same settlement time – T+1. China and India are already doing it, and the pressure is mounting for rapid transformation in the US, Canada, Mexico, Latin America, the EU, UK and Australia. Across the board, Sibos delegates appear to agree that successful achievement of T+1 hinges on the strengthening of automation capabilities to reduce the time and resources required to manage settlement processes, counterparty risks, margin requirements and capital deployment.

While increased automation is crucial to T+1 settlement, there’s nonetheless still quite a low awareness of what changes are needed to deliver these results. Automation can solve many problems, but they need to be defined first. 

Can AI Meet the Challenges of Complex Data Sources?

The need for data quality and governance is widely accepted as central to the deployment of automation and other technology tools.

Many organisations are hindered by highly complex data types that don’t confirm to existing standard infrastructure. Classic examples include PDFs, Excel spreadsheets, contracts and even faxes. These data sources exist outside of the main business data hubs or “centers of excellence” and are difficult to integrate. AI may well be the technology with the most power to transform the processing of this data. In fact, it’s likely to be the most transformative technology within global finance.

But it’s not infallible, nor without risk, and many discussions centered on the importance of ensuring that even the most sophisticated AI platforms have rigid guardrails and rigorous post-extraction processes to identify and rectify data discrepancies. There’s also a strong understanding that AI is only as powerful as the quality of the data that’s inputted.

Overall, Sibos delegates largely agree that there’s little doubt that AI will become more important to the industry and that when it’s coupled with robust guardrails, it has remarkable promise, not least in improving the speed, efficiency and accuracy of reconciliations.

Unlocking Efficiency through Automation

The ongoing transformation in reconciliation processes is on track to render manual reconciliations obsolete in time. More and more manual processes are becoming automated and the data challenges, including the particular difficulty of unstructured data, are being tackled.

As with other areas in which technology and AI are set to transform data management processes, data integrity continues to be a top priority. Reconciliation solutions that offer ongoing data integrity and security will also drive efficiencies, while the automation of sub-optimal processes will clear the path for larger volumes of reconciliations to be onboarded at pace.

Unstructured Data Must be Conquered

There was some talk in Toronto about the need to pay more attention to the growing volume of unstructured data being generated from sources such as PDFs, spreadsheets, emails, financial documents and contracts and even faxes. The need to extract, sort and leverage this data is urgent, but it’s hobbled by outdated legacy technology. This can push financial institutions into adopting risky practices.

We believe that AI and other technologies are crucial for financial institutions to digitise, cleanse and standardise their data to meet settlement and regulatory requirements. Technology also facilitates the automation of data management tasks and improves data accuracy. All of will enhance their businesses and provide a clearer view of their customers.