KPMG applying IBM artificial intelligence to help businesses efficiently meet IFRS 16 lease accounting requirements

KPMG applying IBM AI to help businesses meet IFRS 16

Major global rental car company is able to analyze thousands of real estate contracts in a fraction of the usual time to ease its compliance burden.

Kathryn Wright

Director, Global External Communications

KPMG International


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For companies with a multitude of leasing agreements, meeting the requirements of the IFRS 16 lease accounting standard (effective 1 January 2019) can be an arduous undertaking. Extracting the required data from a contract that may be hundreds of pages long is a complex, manual task that can take several hours. Multiply this across tens of thousands of contracts globally and the scale of the challenge is daunting.

One entrepreneurial global car rental company is enjoying a step change in its IFRS 16 compliance experience. A new automated solution, the KPMG Contract Abstraction Tool (PDF 436 KB), extracts data many times faster than traditional methods, enabling the company to swiftly and easily analyze real estate agreements for its rental stations worldwide. In addition to real estate, the tool helps simplify IFRS 16 compliance for the leasing of automobiles and IT services.

A growing range of organizations across sectors such as life sciences, telecommunications and retail are also using the contract extraction tool, which uses artificial intelligence (AI) and cognitive technologies from IBM's Watson Explorer, with KPMG's accounting advisory services and data and analytics (D&A) expertise from the KPMG Lighthouse Center of Excellence for D&A and Intelligent Automation.

“We've effectively trained the solution to read and understand contracts just like an attorney would,” explained Markus Kreher, Global Head of Accounting Advisory Services and Head of Finance Advisory, KPMG in Germany. “It can work its way through any type of unstructured documents - and identify trends, patterns, anomalies and relationships. A job that would normally take several hours per contract can now be completed in as little as 10 minutes or even less, with far greater accuracy.”

The extracted data is rendered in a convenient format that can be entered directly into the company's leasing software or ERP system, making it simple to meet IFRS 16 requirements.

“This solution represents a perfect partnership of IBM technological know-how and KPMG's expertise in lease accounting and compliance” said Dirk Heitmann, Chief Digital Officer, IBM Germany, Austria and Switzerland. “And the great thing about the KPMG solution with IBM Watson Explorer is that it continues to get better via machine learning, using advanced algorithms and a strong cognitive capability to help achieve reliable and consistent contract evaluation.”

The cost of data extraction also becomes more predictable, as the service is delivered on a fixed price per contract. And the entire process is overseen by leasing specialists from across the KPMG network, to help ensure that everything is in line with regulatory requirements.

KPMG's Christian Rast, Global Head of Technology & Knowledge, said the KPMG Contract Abstraction Tool offers clients a sense of the power of artificial intelligence: “These kinds of disruptive, machine learning technologies are having a hugely positive impact. As well as saving time on laborious manual tasks, they also help people make sound decisions by providing richer D&A intelligence. We see a very wide range of exciting applications that go beyond meeting regulatory requirements.”

For more information, contact:

Jennifer Samuel
KPMG International
+416 451 8185

About KPMG International

KPMG is a global network of professional services firms providing Audit, Tax and Advisory services. We operate in 154 countries and territories and have 200,000 people working in member firms around the world. The independent member firms of the KPMG network are affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. Each KPMG firm is a legally distinct and separate entity and describes itself as such.

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