IFRS 16/US-GAAP Meets Machine Learning with SAP & LEVERTON
In January 2019, the new IFRS 16/US-GAAP lease accounting standards will come into effect, requiring companies to put more than $3 trillion worth of assets onto their balance sheets. The transformation race towards the new standards has started and businesses are now preparing for the changes. As the interest in this topic is rising and corporations are demanding a simple solution, LEVERTON and SAP teamed up to help simplifying the transition.
Recently, LEVERTON and SAP organized a joint event in Frankfurt to discuss what needs to be done and what the joint solution looks like. We welcomed a full house of representatives from multiple corporations to speak about the impacts of the new accounting standards and how advanced technology can boost the transition. For those who could not make it to the event, we have gathered the highlights and main takeaways below.
As the first speaker, Dr. Carl-Christian von Weyhe, CFO of SAP, started with outlining the background to the regulatory changes. He clearly stated the need for change, as “over 85% of lease commitments do not appear on finance sheets today.”
High volume of data which needs to be processed in short time, inefficient lease management, and lack of transparent lease data, which also results in difficulties to create an accurate picture of a company’s lease assets & liabilities, were identified as the main pain points for companies affected by the new standards. Structured and accurate data is crucial for correct reporting and thus transparency over lease data is key to successfully manage the transition. Especially, because the changes will not merely affect finance and accounting departments but also have to be reflected in companies’ strategies. To mention one example, companies will for instance need to consider lease vs. buy options.
The challenges arising from the transition can be overcome though. Combining Artificial Intelligence with SAP’s solution to IFRS 16/US-GAAP enables clients to save cost and time. LEVERTON CEO Emilio Matthaei, Managing Director Micha-Manuel Bues and Product Management Director Dan Wucherpfennig presented in detail how advanced Machine Learning technology can do so in few steps.
Firstly, the platform allows you to compile and store all leases in a centralized and structured way – from documents in more than 20 languages. Secondly, automated data extraction will help you find and read out all relevant information. Finally, once the relevant data is identified and extracted, you can sync it with your ERP-system, such as SAP. Once the data is in your system, it can be easily consumed and reported within finance and accounting departments.
Having structured information ready in the accounting system enables you to solve major pain points. Visibility into lease data is given through easy reporting functionalities and leads to more efficient lease management and effective financial decision; e.g. “lease or buy” simulations can be run on large data volumes in real time.
By applying Machine Learning, the challenges surrounding IFRS 16/US-GAAP can thus be solved more easily. By avoiding manual data aggregation and thereby achieving drastic time savings, companies can instead focus on analyzing the results and the impact. With the help of Machine Learning technology and the seamless integration of data into your ERP system, your new lease accounting strategy can be built upon complete and structured data, eliminating the need for advanced guesswork.