Automating the creation of financial records - for example where there are multiple legal entities where data needs to be populated - or automatically aggregating such data sets is an area where automation offers the potential to be a significant time saver.

Automate reconciliation of financial statements of related legal entities - typically used for sophisticated and complex businesses operating across multiple legal authorities. This matters for providing an audit trail.

Determine optimal moment to bill accounts for missing payments - using historic and comparable data to optimise chances of maintaining paying relationship with a subscriber or other repeat customer whose payment has failed.

Predicting the optimal approach to paying suppliers given the characteristics of the counter-party and the contract.

Determine the risk of a customer not being able to keep to repayment schedule.

Predict potential issues in the audit process by assessing and cross-correlating financial data, seeking out potential discrepancies and highlighting potential risks. Typically this would act as an initial triage approach allowing expensive audit personnel to focus on key areas and higher value tasks.

Using a combination of known future cash movements with machine learning analysis of historic (and comparative) cash flow events to predict future cash positions of an organisation. This is preferably only fully relied upon in conjunction with experienced finance professionals to ensure its likely accuracy.

Predict migration volume based on different data sources and indicators. This can aid country policymakers and NGOs to prepare for changing migration patterns.

Determine risks in currency movements and / or risks in cash flow to help manage risk situation - including understanding reserves required from a prudent management (or regulatory) perspective.