Contract transition in M&A: Accelerating value through AI

Deals move at speed. Procurement is expected to take the lead in the always complicated task of disentangling and transitioning supplier agreements. The technology driving the KPMG Cognitive Contract Management tool, powered by the Ignite platform, has no problem setting the right pace.

By Steven Kloepfer

The deal is signed and time is of the essence. You need to transition thousands of contracts for suppliers, not to mention customers and business partners but who’s counting? The buyer is already requesting your transition plans and is laser-focused on minimizing dis-synergy. Forget about understanding all the legal transition terms within each document. You haven’t even located all the contract files scattered across the organization.

Are you ready to move at deal speed?

This is becoming an all-too-common scenario for procurement leaders. A manual approach to contract review makes sense when volumes are low, but the effort becomes much larger when tens, or even hundreds, of thousands of contracts are involved, each with varying structures, supporting documents, and languages—even some in different languages!

That’s when streamlining—and automating—the contract review and dispositioning process quickly goes from “nice to have” to “mission critical.”

The need for deal speed

Merger and acquisition (M&A) deal activity surged globally in 2021, easily surpassing prepandemic levels and setting the stage for continued expansion through 2022. In 2021, $5.1 trillion worth of M&A transactions were announced, compared to $3.8 trillion in 2020, representing the highest level of activity since 2015.¹

With such an active deal market and soaring valuations, exploiting technology to accelerate value, increase focus on synergy/dis-synergy, and mitigate risk has never been more important. Organizations are looking for new ways to handle the many tactical elements of the contract transition process. With accelerated deal timing continuing to be a priority, the KPMG Cognitive Contract Management platform helps organizations execute quickly by automating the most time-consuming elements of the contract transition process.

Curbing separation anxiety

Let’s say an organization is divesting a portion of its business. That means all the existing contracts for that organization—across its customer, supplier, and business partner bases—need to be examined to determine the degree of contract entanglement, which contracts will stay with “remainco,” which will transition to “newco,” and by what mechanism the transfer will occur.

A well-thought-out contract transition strategy and approach goes a long way in defining transfer scenarios and the mechanisms that will be used during the transfer. However, contracts often show significant variation. Relevant contract language and terms need to be identified, reviewed, and interpreted to truly understand the legal intent of the language and how that language impacts the proposed contract transfer approach.

Technology to the rescue

A number of contract management solutions are available in the marketplace to address contract review in the context of various M&A scenarios. However, our experience shows that the majority of commercial off-the-shelf (COTS) contract management software packages merely focus on ingesting, digitizing, and extracting relevant information (but not always), but this simply will not be enough during M&A events.

Where COTS solutions fall short is in the ability to read and interpret the contract language, as a human would, to make decisions on how to treat each contract. This is where significant effort lies and, with most technologies, it is still left to human intervention.

But who says the intervention always needs to be human?

Ignite is the KPMG enterprise-level Artificial Intelligence (AI) platform that includes domain knowledge, proprietary and integrated open-source algorithms, frameworks, and automation, as well as strategic technology partnerships. The KPMG Ignite ecosystem helps enhance, accelerate, automate, and augment decisions that drive growth and profitability. AI—combined with and based on deep industry and analytics knowledge—helps clients embrace intelligent technologies confidently and responsibly.

Building trust in automated decision-making

The major difference between Ignite and COTS solutions is Ignite’s ability to make decisions based on the data extracted from contracts in human terms. It doesn’t simply locate the information. It understands and can automatically interpret data, and then propose a decision based on trained machine learning algorithms. Legal language can be difficult—even for humans—to interpret. Machine learning algorithms are “trained” to interpret this language. This drives consistency in the application of decision logic and has tested to be not only much quicker, but also even more accurate than human interpretation.

Interpretation can be difficult, especially when arriving at a correct answer requires maintaining objectivity and consistency across hundreds of variations of the same language. Take, for example, an Assignment Clause. Beyond just understanding if an Assignment Clause is present, you may be interested in understanding whether the contract can be assigned to a third party, what type of consent is required in order to assign the contract, and how many days’ notice is required before assigning the contract. In this example, we want to decompose complex legal language and return structured, and standardized, results for each question.

14.4 Assignment

Neither party shall assign any of its rights nor delegate any of its obligations under this Agreement, by operation of law or otherwise, to any third party, in part or its entirety, without the express prior written consent of the other, non-assigning party, by providing 30 days’ written notice.

Anecdotally, we’ve seen that highly skilled domain experts typically achieve an accuracy of 85 percent to 90 percent while reviewing and analyzing contracts. Ignite’s machine-learning algorithms can consistently exceed human accuracy—in some cases producing results with 99 percent accuracy. Additionally, the speed at which a machine can complete the same activity as a human is significantly accelerated. In some cases, machine learning has tested to provide efficiency gains upwards of 99.9 percent. 

Legal language is only one example. What do you do when you have one (or many, many more) amendments to a contract, some of which may materially change relevant transition clauses?

Ignite can handle that, too, analyzing each contract file independently, creating contract families and consolidating relevant files into a master contract record.

The Ignite tool also has various dashboard views that can track analytical results across thousands of documents. The fact it was developed by KPMG data scientists provides more flexibility to present data in the way you need to see it—either using standard data visualization tools or more traditional views like Excel.

These examples underscore the value of a tool such as Ignite to automate contract dispositioning, provide a highly accurate confidence level, and potentially remove weeks of effort from an already compressed deal timeline.

Looking ahead

Maybe someday, transitioning supplier agreements in the context of an M&A transaction will be as simple as barking a command at your AI-powered digital home assistant. Every machine learning tool gets smarter with use, allowing it to continuously learn. That leaves the future wide open.

As an enterprise, we have that same goal: to continuously learn and generate new ideas to better serve our clients.

That same type of philosophy is what led to the development of Ignite, and it’s that same mindset that will also keep this tool, and KPMG, hungry to learn.

For more information, visit KPMG Cognitive Contract Management

Footnote

1. 2021 data through November 15, 2021. Source: CapIQ, Refinitiv, Pitchbook