AI-fueled Expansion of SuperLedger Solution :
Today, Deloitte announced the introduction of autonomous SuperLedger, an augmentation of its current integrated cloud platform for transaction processing, financial planning and analysis (FP&A), and sub-ledger reporting powered by artificial intelligence (AI). SuperLedger provides advantages comparable to complete ERP consolidation that creates a reliable source of truth, but more quickly and inexpensively.
For large, complex enterprises that have implemented or are through an M&A expansion plan and are wanting to provide intelligent analysis across several ERPs through one comprehensive, secure, and cloud SaaS-based digital tool, Deloitte’s autonomous SuperLedger is especially well-suited. The solution can be customised for businesses in any sector that do huge volumes of low value non-ERP transactions, including those in the insurance, healthcare, technology, media, and industrial sectors.
In order to bring finance firms closer to real-time, touchless operations, SuperLedger leverages the most recent advances in AI technology and machine learning models. It has a number of improvements that go above and beyond what was offered by the previous version of Deloitte’s SuperLedger, which offers an integrated cloud platform for transaction processing, FP&A, and sub-ledger reporting without the need for full ERP consolidation. These improvements make use of Oracle Autonomous Database and Deloitte’s proprietary AI capabilities. These improvements consist of:
- Kinetic Start-up is a solution that scans the on-premise environment in a flash, pulls pertinent information from older systems, and makes it accessible in the cloud. Finance executives may rapidly see the type of their present data and the potential level of change needed thanks to this.
- Pre-built automations for accelerating and streamlining typical financial operations including consolidation and close, procure to pay, and FP&A are known as touchless processing.
- Machine learning algorithms that automatically fix faults in source data based on historical trends are known as self-healing and auto-correction. For situations requiring human interaction, the models additionally build a framework for handling exceptions.
- Intelligent suggestions Are alternatives for manually fixing problems based on computer analysis.
- Sensing, detection, and prediction are three terms used to describe machine learning models that enable continuous risk sensing and anomaly detection for high-volume, low-value financial transactions as well as predictive predictions about the future of the company based on specific characteristics.
“Since its introduction in 2019, Deloitte’s SuperLedger has been a compelling solution for many organizations, helping them to consolidate their data and systems, streamline their finance processes to drive better reporting and analytics, and deliver better experiences for their employees”, “The expanded autonomous capabilities in this new release take finance transformation up a notch. The solution can help companies to rapidly adopt a modern cloud platform and digitally evolve toward continuous, real-time operations — and in so doing, to better position themselves for growth.” Varun Dhir, principal, Deloitte Consulting LLP.
Test out autonomous SuperLedger for yourself
Connect with Deloitte experts at the Oracle CloudWorld Hub to learn more about the capabilities of their autonomous SuperLedger. Daily theatre sessions featuring talks on the solution by our experts will also include one-on-one demonstrations. The global sponsor of Oracle CloudWorld in Las Vegas from October 17–20, 2022, will be Deloitte. People from all around the world will congregate at this new conference to exchange ideas, learn marketable skills, and gain knowledge of cloud apps and infrastructure.
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