Adopting AI for Superior Reconciliations
Rising compliance costs and greater competition are narrowing margins in financial services, even as the adoption of new technologies in other industry segments are raising customer expectations across the board. As a result, financial institutions are looking at how to wring more value from their activities, while streamlining their operations in order to minimize costs.
In response, financial services firms are turning to emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to automate processes and activities that previously required a human being.
Firms’ reconciliations and exceptions management processes represent a kind of low-hanging fruit for the application of emerging technologies. They are human labour-intensive, and as such expensive and prone to error. In many cases, posttrade systems are fragmented, organised by silo, and incapable of meeting the new demands being placed upon them by the business side.
By streamlining their reconciliations processes through automation, firms see an opportunity to reduce the number of exceptions they manage and the time it takes to deal with them. This approach furthermore can reduce operational risk, boosting the firm’s overall financial position, both in terms of reduced losses and regulatory capital. This white paper looks at the current state of play and the opportunity for the adoption AI and ML in the reconciliations process. It explores what’s needed to streamline exception management and minimize the need for human intervention. Finally, it outlines the capabilities of SmartStream AIR, and explains how this new AI-based initiative can help improve firms’ reconciliations processes in terms of speed, accuracy and cost.