A flexible, fast and efficient tool for automating the analysis of tax-sensitive transactional data using cutting-edge machine learning technology.
A tool for automating the analysis of tax-sensitive transactional data.
With HMRC’s increased focus on reviewing risks associated with preparing tax computations, existing manual processes for analysing large amounts of tax-sensitive transactional data cannot be relied upon in this new environment.
KPMG Tax Data Analytics Engine is a fast and efficient cloud-based solution, with the ability to analyse thousands of transactions in minutes, clearly summarising results for transfer to tax computations. It is designed to work with expenditure of any kind, facilitating the analysis of fixed asset additions, refurbishment projects, legal and professional expenses, employee expenses and more. Machine learning algorithms, trained using KPMG’s many years of advisory and compliance expertise across all industry sectors, help to categorise data as quickly and robustly as possible.
Keyword-driven rules help ensure the same logic is applied from one year to the next, across all companies in a group, even if different team members run the analysis due to the use of a managed service centre, or staff turnover.
Once the rules have been set up, they can be applied to large data sets in a matter of seconds. Machine learning even helps fill in the blanks, helping you get to the final answer as quickly as possible.
Detailed reports show how the data has been categorised, and why. Custom templates can be imported, allowing you to create your own reports without further KPMG involvement.
A full audit log is available, allowing all user activity to be seen at a glance. Users can be denied or granted read-only access to individual projects, ensuring they can only see or change what they’re supposed to.
KPMG Tax Data Analytics Engine can be used to demonstrate to Revenue authorities that businesses have a robust process in place for analysing tax-sensitive data, while at the same time reducing costs and allowing Finance and Tax teams to focus on more value-adding activities.