Forensic Due Diligence: Another Tick in the Box?
According to Refinitiv, a financial market data provider, the overall value of mergers and acquisitions in India amounted to US$41.6 billion in the first half of 2019.1
Furthermore, given the Indian Government has eased Foreign Direct Investment norms, with the aim to entice heavy foreign investments, and is looking at market growth in the interest of the buyers who are consolidating businesses, India will remain a lucrative investment destination in the coming years. There are multiple steps which investors undertake to ensure a profitable return on their investment — due diligence being one of the steps.
Furthermore, the depth of diligence is also influenced by a number of factors including the value of investments, type of business, timelines and competitive biddings amongst others. So, how much diligence is adequate?
There is no straight answer to this question. In this article, we highlight some key areas to be evaluated, and the possible repercussions of undertaking inadequate due diligence. While most investors carry out financial and legal due diligence, forensic due diligence is, perhaps, less common. A failure to conduct in depth forensic due diligence may result in financial loss, as well as other exposure, since certain inherent risks are likely not to be detected.
Broadly, forensic due diligence aims to address the following concerns:
- Authenticity of the reported financial numbers
- Existence and background of key suppliers, employees and customers
- Adverse issues surrounding the promoters or key management personnel
- Political connections and impact on business activities
- Undisclosed related parties and transactions
- Undisclosed liabilities or potential claims and litigations
- Exposure to bribery and corruption
While financial due diligence, a critical step in any transaction, gives the investor a broad overview of the trends and sustainability of a business based on a macro-level data set, forensic due diligence delves into the transactional-level data to find anomalies and irregularities.