• KCL M&A Society

Leveraging Digital Tools to Maximise Efficiency in M&A Transactions

By Katy Welsh, Law Writer at KCL M&A Society

Every year, new challenges face the M&A landscape. Dealmaking is already a complex and time-consuming endeavour, but mounting regulation, surging data volumes and building pressure to deliver value within shorter timeframes have left traditional M&A methods fighting to cope. Organisations squander time and resources by dedicating teams to conduct largely administrative tasks such as scouring through the increasing amounts of data produced by target companies when their tacit knowledge could be better applied to higher-value activities. Furthermore, although rising data volumes enable acquirers to know more about the target, this data often ends up being under-utilised, as inherent human error means that potential liabilities may be missed or misinterpreted. Digital tools such as AI, VDRs, eSigning, data visualisation and document automation can streamline M&A transactions: saving time, reducing costs and helping to deliver increased shareholder value.

Current uses

These tech solutions are capable of being utilised at all deal stages of the M&A process — from pre-deal target identification, digital screening and analysis through to post-deal integration. In the early stages of the process, AI and data analytics can be used to extract the most viable acquisitions from a list of potential targets. By applying algorithms which use data on industry trends, growth paths and financial profiles of target companies, potential acquirers are able to make more informed decisions in relation to their acquisition strategy. Blockchain technology has the potential to disrupt M&A by creating marketplaces on decentralised blockchain networks, allowing negotiations between businesses to occur discreetly and anonymously. Blockchain can have an even more critical role in the form of smart contracts — computer programs which automatically execute coded terms of the contractual agreement without the need for an intermediator, hence lowering costs. Cloud-based systems in the negotiating stage allow for safe multiparty collaboration, reducing the need for email correspondence and linear document sharing. Transitional Service Agreements (TSAs) have long been used to enable a buyer to 'piggy-back' off of the seller's established infrastructure support (such as accounting, IT and HR) after the deal closes, for a specified period of time. Although they ensure business continuity for the buyer, TSAs delay synergies, limit buyer flexibility and generate higher operational costs. Tech solutions such as 'as a service,' on-demand arrangements and automated solutions can replace the elements of a traditional closing model, driving a deal to conclusion more rapidly and reducing the length of costly TSAs.

Due diligence

Despite the implementation of digital tools occurring at all stages of the transaction, the most significant impact of digitalisation is shown during due diligence. The current era of Big Data has seen an explosion in the volumes of data that due diligence teams have to analyse. Furthermore, the information is held largely in disparate and unstructured data sets from organisational silos which, along with a tendency to rush the due diligence stage in an attempt to reduce legal fees and gain market share more quickly, can lead to potential liabilities being missed.

Inadequate review of these documents can result in huge ramifications for the buyer, with HP having to write down almost $9 billion following their acquisition of Autonomy in 2012 due to overlooking inaccurate income statements and balance sheets [1]. Virtual Data Rooms (VDRs) are solutions created to facilitate more effective workflows by eliminating the need for printing and copying of physical documents. Usually a cloud-based platform which is able to cope with huge influxes of data, VDRs offer a secure space where parties can share thousands of highly confidential documents for the potential buyer to evaluate. Documents can be tagged and margin notes can be attached to encourage collaboration between the negotiating parties.

Although VDRs massively aid the due diligence process by organising the information into a more easily digestible format, sophisticated search tools are also required to be able to extract the key information. Whilst basic keyword searches and filters such as those found on Google are essential, more advanced platforms such as eBrevia, Kira and Luminance are using artificial intelligence (AI) to review huge numbers of documents in a much shorter timeframe, reducing the number of billable hours for due diligence which can make up more than 30% of the total legal bill on a deal. eBrevia [2] and Kira [3] use supervised machine learning, where the system can scan datasets and draw out specific provisions (such as those relating to change of control), which have been pre-described and pre-defined by the user. Luminance takes this one step further and also incorporates unsupervised machine learning, where the system does not require any a priori knowledge of specific clauses and provisions (and so no input from the user). Instead, by analysing huge data sets, the system is able to identify patterns and hence abnormalities, surfacing ‘unknown unknowns’ which the user would not have even known to search for [4].

Not only can AI increase the speed of the due diligence stage, but it has also been shown to operate with a higher level of accuracy than its human counterparts. The AI software can parse through documents and draw out potential liabilities or clauses in contracts that hinge on a change of control and could be problematic for the deal. In December 2018, the Düsseldorf office of leading international law firm Bird & Bird [5] took on a high-volume due diligence exercise concerning 20,000 employment contracts of a subsidiary company the client was looking to sell. By using the machine-learning technology of Luminance, they were able to increase the number of documents they reviewed from 79 documents per hour — when done manually — to 3,600 per hour. In February 2019, Luminance was again deployed by a Global Top 100 law firm to conduct a high-pressured M&A due diligence exercise, under an aggressive timescale. The target organisation was a subscription-based service, and on the first morning of the review, Luminance was able to identify that only 30% of the customer contracts contained an automatic renewal clause, meaning the business could lose more than half of its customer base in less than a year. These findings were delivered to the client within 15 hours, representing a 70% time saving compared to initial predictions. Furthermore, the wording of these automatic renewal clauses was subtle and varied between contracts, meaning they would likely have been missed by an individual conducting a manual review. As well as avoiding human error, AI removes emotions and influential biases from the process, allowing an accurate and objective assessment of the documents. The results are accelerated deals, reduced costs and lower risks of the transaction being derailed by an undiscovered issue further down the line.

The Future of Digitalisation

Although there has been a gradual transition towards digitalisation of the M&A landscape over the last 5 years, COVID-19 has expedited digital transformation by forcing organisations to operate within a largely virtual environment. Pre-existing digital tools have been utilised and have allowed dealmakers to continue to operate despite the challenging business environment. A Deloitte survey, conducted between August 20th and September 1st 2020, of 1000 executives at US corporations and private equity investment firms showed 87% of respondents reporting that their organisations were able to effectively manage a deal in an entirely virtual workspace [6]. Ten years ago, this would have been impossible. However, digital tools are not without their drawbacks.

Cybersecurity and deal integration remain a concern, along with fear of job losses due to automation of certain facets of business operations. If legal teams are able to conduct due diligence of the same number of documents, but in significantly less time and requiring significantly fewer people, will the throngs of junior lawyers who were previously tasked with these routine tasks become redundant? Furthermore, issues surrounding the allocation of blame may arise when AI has been used in the decision-making process. If a problem is identified before a deal is closed, the parties can walk away unscathed. If the problem is discovered further down the line, who is there to point the finger at? There are also substantial limitations on the types of questions that these tech solutions can answer. Whilst they may be able to consistently outperform humans on financial issues relating to the valuation and performance, questions relating to the cultural compatibility of a target company may pose more of an obstacle. The worst merger in American history, between AOL and Time Warner, was in part due to an oversight of such “culture” issues in the due diligence stage [7], and there is no guarantee that the aforementioned digital tools would have picked up on this any more than the human team at the time.

It is clear that whilst AI and other digital tools will have an undeniable role in the development of M&A, deal-making will require some form of human input for the foreseeable future. People are still required to label the data that gets fed into the algorithms, and neural networks are "only as good as the data available to them” according to Ben Taylor, an adviser to the All-Party Parliamentary Group on AI [8]. The digital tools that we have available are incapable of providing the 'human touch' required in commercial and strategic decision-making. Rather, they function to reduce friction in the M&A process (particularly by reducing the length of time required for the legal teams to conduct the extensive due diligence phase), decrease the time taken for deals to complete and supplement human intuition by taking on some of the drudgeries, freeing up time and valuable legal resources for employment elsewhere.

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Reference list:

[1] Aaron Ricadela and Amy Thompson, “HP Plunges on $8.8 Billion Charge from Autonomy Writedown” Bloomberg (20 November 2012) [2] ‘M&A & Other Transactional Diligence’ EBrevia https://ebrevia.com/ma-other-transactional-diligence [3] ‘Accurate Due Diligence, Done in Minutes’ Kira https://kirasystems.com/how-it-works/due-diligence/ [4] ‘The Market-Leading Technology for AI Technology Lawyers’ Luminancehttps://www.luminance.com/technology.html [5] ‘M&A Due Diligence Case Study: Bird & Bird’, Luminance (December 2018) [6] ‘M&A Trends Survey: The Future of M&A’ Deloitte (1 September 2020) [7] Berkeley Lovelace, “Steve Case to AT&T: Learn from my AOL-Warner Time Warner failures” CNBC (13 June 2018). [8] Sandra Vogel, “How AI can simplify mergers and acquisitions” ITPro. (3 July 2019)