Data analytics increasingly important in M&A financial due diligence

Financial due diligence has typically centred on examining financial statements, management accounts, and interviewing sellers and management teams. However, the advent of data analytics has created new possibilities for gaining more profound commercial insights into transactional risks and post-deal opportunities.

Data analytics have made the process far more efficient, Early and Ashton say. Financial due diligence involves assessing the financial health of a target company by analysing its financial performance, cash generation and financial position. Traditionally, this was a time-consuming, manual process that relied heavily on historical financial statements, and offered a static view of the business.

Data analytics tools make financial due diligence a more dynamic process. It enables acquirers to process vast amounts of data quickly, uncover hidden patterns, and assess financial and operational health. Rather than simply confirming what is in the books, data analytics tools and techniques enable potential buyers to detect outliers and spot potential risks or opportunities that may otherwise go unnoticed.

There are key advantages to using data analytics in financial due diligence. “Data analytics tools can automate many repetitive tasks involved in financial due diligence, including data cleansing, aggregation and reconciliation. This reduces human error and enables a faster execution of financial due diligence.

This efficiency potential can also provide a compelling benefit to management teams on sell-side engagements by reducing the burden of preparing information for diligence purposes.

The application of data analytics techniques can quickly and accurately identify anomalies, discrepancies, and potential red flags. For example, trend analysis can uncover irregularities in revenue streams, detect unusual expense patterns, or pinpoint areas of financial risk, such as delayed payments or inflated earnings.

And, with access to current transaction-level data, financial analysts can dive deep into granular metrics like customer churn rates, SKU-level product profitability, and revenue contributions by geography and business unit. This provides a more comprehensive view of the target company’s true financial performance drivers, aiding better decision-making. In addition, this deeper dive can be relevant on sell-side engagements to provide robust analytically-based evidence to support a seller’s equity story or investment rationale.

Finally, financial due diligence does not operate in isolation and is increasingly becoming integrated with other aspects of due diligence, such as operational, legal and technological assessments. Data analytics tools can enable integration by aggregating data in different formats and from a wide range of sources.

For example, data analytics can be used to review operational metrics and KPI data from both a financial diligence and operational diligence perspective. This holistic view is especially valuable in identifying the cross-functional risks or synergies often critical to a successful acquisition.

In short, our team says that data analytics are now crucial for successful M&As.

The rising importance of data analytics in an M&A project cannot be overstated. It enables buyers to make more objective, data-driven decisions by enhancing the accuracy, efficiency, and depth of their analyses.

The breadth, depth and complexity of data relating to company performance is only going to increase over time so applying data analytics techniques will soon become a routine part of the M&A process, giving companies a competitive edge in identifying and executing successful deals. 

Here at KPMG we have a dedicated Deal Analytics team within our Transaction Services practice, specialising in providing data analytics services for financial due diligence and exit readiness planning assignments.

Our team works on both buy side and sell side due diligence assignments, where Deal Analytics services have significant potential to support efficient diligence processes with a focus on identifying key risk considerations and value creation opportunities.   

Leveraging advanced analytical tools and techniques to deliver deeper insights and more accurate assessments, our team ensures that clients are equipped with high quality, objective data to inform their M&A decisions. The team also has access to a suite of AI tools which augment our analytics offering and ability to deliver deeper insights at deal speed.  

The Deal Analytics team also plays a crucial role in the delivery of KPMG’s proprietary Diligence+ financial due diligence methodology, which brings value creation perspectives into every deal.

This integration of data analytics into the Diligence+ methodology not only enhances the accuracy and efficiency of due diligence but also underpins potential risks and opportunities, ultimately contributing to the overall success of M&A activities.

This article appeared in the Business Post on 16 February 2025 and is reproduced here with their kind permission.