For organisations looking to use AI to streamline their data operations, there are several questions to take into consideration before making a firm commitment. Companies need to ask themselves which AI-enabled technologies fit their data and exception management requirements best, for example, ML is well suited to bringing added efficiency to the reconciliations process.
When building AI use cases, they must take a careful look at the business challenges they face and operational process changes required. In addition, organisations should work out a realistic time frame for the actualisation of any AI use cases, while they also need to ask themselves whether, before introducing AI, there are other, more near-term improvements that can be made.
SmartStream has a great deal of experience working with AI-based technologies. Our innovations team focuses on the application of AI and ML to the business challenges faced by customers. We do not partner with third parties and the innovations team is solely devoted to creating AI and ML applications.
The efficiency gains AI and ML can bring to financial institutions’ reconciliations operations is demonstrated by two recent customer use cases, in which SmartStream’s observational AI module, was deployed.
