Anyone who has read through a commercial lease document will understand the intricacies that can be involved in distilling the information contained within the lease to arrive at the most important data points.
Lease abstraction – the process used to extract essential information from lease agreements to arrive at the key terms and provisions of a lease – makes it easier for stakeholders to quickly understand and manage the terms and obligations of various leases.
From an accounting perspective, lease abstraction is absolutely critical in complying with the relevant lease accounting standards such as ASC 842 and IFRS 16.
AI has a massive role to play in lease abstraction: companies not using AI are at risk of being left behind, not to mention being vulnerable to increased compliance risks, while those embracing AI for lease abstraction are not only ensuring compliance but are freeing up time and other critical resources to focus on strategic, high-impact activities.
Leases: Key Data Points
There are many more data points in leases that are required for accounting and regulatory compliance than people think. This makes manual lease abstraction increasingly difficult and provides the perfect use case for technology-oriented solutions, including AI, Natural Language Processing (NLP), Optical Character Recognition (OCR), and others.
Key data points in leases include:
- Lease commencement date
- Lease term (including renewal options)
- Lease termination date
- Lease identification number or reference
- Lease payments, including fixed lease payments and variable lease payments
- Incentive payments
- Residual value guarantees (if applicable)
- Right-of-Use Asset Information, such as initial direct costs (e.g., broker fees)
- Restoration or replacement obligations
- Discount Rate: the lessee’s incremental borrowing rate or implicit rate (if known)
- Lease Modifications, including any changes or amendments to the lease terms and the effective date of modifications
- Lease options, such as renewal options and termination options, along with related terms and conditions
- Termination clauses and penalties
- Disclosure-related information such as future lease payment obligations, maturity analysis, and other qualitative and quantitative information
As seen from this list, there are many nuances in the lease abstraction process, making AI an essential part of any severe organization’s lease accounting efforts.
The Role of Lease Abstraction
Lease abstraction plays a pivotal role in lease accounting and management, serving as the foundation for efficient and accurate lease portfolio oversight. First and foremost, lease abstraction enables organizations to extract and organize crucial lease data from often lengthy and complex lease agreements.
Lease abstraction supports effective lease portfolio management. It allows companies to proactively monitor lease milestones, such as upcoming lease expirations, renewal opportunities, and important dates for compliance and financial reporting. This proactive approach helps in avoiding potential pitfalls and capitalizing on strategic advantages, such as renegotiating favorable lease terms or optimizing space utilization.
In addition, lease abstraction enhances risk management by highlighting critical elements of lease agreements that may impact the organization’s financial health and compliance. This comprehensive understanding of leases empowers decision-makers to make informed choices regarding lease portfolio strategies.
Where lease abstraction is most critical is when it comes to accounting and compliance. The key data points of the lease are the foundation upon which the accounting entries for leases – and indeed, the company’s financial statements – are based.
Ensuring Data Accuracy
What are the methods and best practices to ensure the accuracy of abstracted lease data? The following are accepted as some of the key ways to ensure data accuracy:
Traditional methods
Quality Assurance Procedures: Implement quality assurance processes, including peer reviews and cross-checks, to catch any errors or discrepancies in the abstracted data.
Use of Technology: Consider using AI-powered lease abstraction software to automate the process and reduce the potential for human error.
Standardized Templates: Develop standardized templates for lease abstraction to ensure that all key data points are consistently captured and formatted correctly. This helps prevent inconsistencies in the data.
Expertise and Training: Ensure that the individuals responsible for lease abstraction have a strong understanding of accounting standards like ASC 842 and IFRS 16 and are trained in the nuances of lease agreements. Expertise is crucial in correctly interpreting lease terms.
Cross-Functional Collaboration: Collaborate with cross-functional teams, including accounting, legal, and real estate professionals, to validate the abstracted data. This multidisciplinary approach helps in reconciling any differences in interpretation.
Data Validation and Reconciliation: Regularly reconcile the abstracted data with financial records and other sources of lease-related information to identify and rectify any inconsistencies.
Clear Documentation: Maintain comprehensive documentation of the abstraction process, including details of who performed the abstraction, dates, and any decisions made regarding interpretation. This documentation is essential for audit purposes and ensures transparency.
Testing and Validation: Conduct periodic testing of the accuracy of the abstracted data to confirm that it aligns with the organization’s financial statements and disclosures.
Stay Informed: Keep up-to-date with changes in accounting standards and regulations, as these can impact the accuracy of lease abstraction. Regularly review the latest guidance to ensure compliance.
Data Governance: Establish strong data governance practices within your organization to maintain data accuracy not only during the initial abstraction process but also throughout the lease’s lifecycle.
Continual Improvement: Maintain a process of continuous improvement by learning from past discrepancies and adjusting abstraction procedures accordingly.
The modern approach
While these are important processes, if you implement AI-powered leading lease accounting software like Trullion, the vast majority of these elements are taken care of for you.
With AI, lease abstraction is automated, human error is eliminated, journal entries are suggested, a complete audit trail is available, compliance is ongoing, and accuracy is ensured.
Lease Abstraction Challenges and Solutions
Lease accounting professionals face a range of challenges when abstracting lease data from complex agreements. These challenges can include deciphering intricate legal language and industry-specific terminology within lease documents, standardizing information from inconsistent lease agreements, dealing with missing or incomplete data, and keeping up with changing lease terms due to amendments or modifications.
For companies not using AI-powered lease accounting software, data entry errors and differences in the interpretation of lease terms can lead to discrepancies in the abstracted information, which can pose risks to accurate accounting and financial reporting.
To address these challenges, accounting and finance professionals are turning to dedicated lease accounting software solutions to mitigate these risks and provide numerous benefits.
AI for lease abstraction
What’s clear from all of this is that AI is the key to ensuring accurate and seamless lease abstraction.
And while there are tools out there that attempt to extract data from leases using AI, only Trullion is a complete end-to-end accounting oversight platform that uses AI for lease abstraction and to simplify lease accounting workflows.
It’s the preferred solution for leading accounting teams and CFOs for lowering risk, making work easier, slashing the time spent on leases, and ensuring constant accuracy and compliance.
To learn more and see how Trullion can add value to your company right now, connect with Trullion today.
