With the 1 January deadline for complying with new lease accounting rules such as IFRS 16 and ASC 842 fast approaching, you can imagine that corporate accounting teams are working hard to comply.

Yet according to a recent Deloitte poll, only 15.6% of respondents say their companies are “very” to “extremely” prepared to be compliant, a surprisingly low number given the deadline for adoption is now around the corner.

One issue facing accounting teams is the time it takes to abstract data from leases. This work, often done by an in-house team at great time and expense, does not have to be done manually. Providers of artificial intelligence (AI), machine learning software can help speed up the process of lease data abstraction. The benefits are self-evident, but there are a few things to consider when selecting a vendor.

What questions should you ask when evaluating a lease data abstraction software provider, to ensure you make the right choice? Here are six to start with.

1. How easy is your platform to use?

There are many AI-based lease abstraction software solutions out there, and not all are created equal when it comes to ease of use. Some technology was developed by technical people for technical people, not necessarily for your average business professional.

The user interface may be complicated, or the software may be downloaded on-site, and thus only accessible from your office desktop, not on-the-go via laptop, tablet, or phone.

2. Does your software integrate with target systems?

Analyzing data and arriving at insights from your lease data requires having a centralized data repository. This means that whatever solution you are using to extract and structure data automatically should integrate with your target system, whether it be SAP, MRI, Yardi or another platform. Lease abstraction should be a road to your end system, not a cul de sac you’re stuck in.

3. In how many languages can you platform extract data?

For many companies, assets are leased from Detroit to New Delhi. A global company needs to understand the language capability of their data abstraction solution provider, and weigh that against their potential needs. Some companies, like LEVERTON, have built multi-language capability into their product to meet this demand.

4. How easily can I check the veracity of your data?

There’s nothing helpful about getting lease data abstraction completed quickly, if the data is not accurate. Make sure the technology you choose has an easy-to-access data audit trail, so you can double-check that the data is true without downloading a half dozen PDFs.

5. How long does it take train the machine learning? If it takes several weeks or months, doesn’t this do away with any efficiency gains?

You have a right to be concerned about training time for AI solutions. It is important to know that with natural language processing (NLP) for any new type of document, you need to put in time at the start of a review to train the machine learning. That learning is then retained for the next review, but is obviously not helpful in improving efficiencies for your first batch.

Thus, you should look for a solution provider who has experience with your particular type of document, since their technology will come “pre trained”. This is the case with real estate leases with LEVERTON, as an example.

6. How secure is our data using your technology?

Any technology provider you are using for data abstraction should be employing top-of the-line data security protocol. This means ensuring that their servers run on ISO 27001 and ISO 9001 certified data centers, which will guarantee the highest security. Cloud computing is the way the marketplace is going, just make sure your solution and your CSO are on the same page.

These questions are just a starting point for your search for a technology that can help ease the burden and shorten the time spent on lease data abstraction.

If you’d to find out more about LEVERTON’s capabilities in this area, send an enquiry here.