Have you heard that Machine Learning (ML) and Artificial Intelligence (AI) are enabling computers to win at chess, using weather data to improve profits and providing insights previously never imagined? It’s true, and Trintech is in the process of building out ML and AI technologies that help you improve your controls in your financial close process to detect fraud and lower costs without increasing your risk profile and still satisfying your audits. Trintech believes this will be the next revolution in financial close automation.
Within Cadency, Trintech has built up large datasets on how your users execute your system of controls and can compare them to your compliance framework which documents your risk profile. This means we know:
This is done by the Machine Learning engines that study the trends in your data over time to profile them and identify normalities (clusters of data points that look the same) and abnormalities or risks (data points that stand out) over time. For example, you have 20 journal entries that are auto-approved each n-5 day in your close and 3 which are manually approved by Joe above $100,000. These patterns and the supporting AI algorithms then examine items in the next close and look for alignment (low risk) and differences (high risk) and are then flagged by your risk profile in Cadency.
This functionality then enables Cadency (in real-time) to:
Our goal is that via ML and AI, we will continue to improve efficiency and effectiveness, reduce cost and risk all in the goal of enabling you to produce non-restatable financial reports. Trintech is actively developing these capabilities and is excited to be bringing this innovation to market in a way that leverages the customers system of record in their ERP system, their system of controls in Cadency and drives unique value.
Written by: Michael Ross, Chief Product Officer at Trintech