Mergers and acquisition (M&A) deals are increasing both in developed economies and emerging markets. An important process within the M&A process is due diligence, which is the investigation of the target company.
But ~70-90% of M&A deals fail. Some reasons could be:
- Asymmetry of information, thus limiting evaluation opportunities.
- Lack of standardization between business units, thus making it difficult to efficiently identify red flags.
- Time constraints, thus stopping the fact-checkers from analyzing potential threats thoroughly […]
[…] which could stem from manually doing some of the due diligence processes. Due diligence automation solves these problems. By having intelligent automation tools and digital workers scan documents, identify discrepancies, create reports, etc., companies can better mitigate the growing risk exposure of an M&A.
For due diligence automation, you can leverage end-to-end solutions, such as Nexis Diligence. However, companies with shrinking budgets can use specific automation tools to partially automate some due diligence tasks. In this article, we’re specifically discussing the top 8 use cases of robotic process automation (RPA) in the due diligence process.
1. Data extraction and analysis
A robust risk management process finds potential risks when there seem to be none. RPA collects data from multiple sources, such as public websites, disclosed documents, and ERP applications, quickly and automatically.
By having more data, you have more evaluation opportunities. RPA carries out rule-based analysis of data to identify patterns, discrepancies, and inconsistencies. It will then flag them and inform the relevant person. Especially with the current negative socioeconomic factors, due diligence should be comprehensive and data-driven.
Learn more about RPA’s benefits in analytics.
2. Document review and verification
Due diligence papers are in high volume. So, because there are a lot of documents to revise, assess, and verify, there’s the possibility of human error. Intelligent robotic process automation tools can scan documents and extract specific pieces of information more quickly than a human. So, one of the measurable benefits of robotic process automation in the due diligence process is a faster reviewing time.
Learn more about intelligent document processing.
3. Compliance checks
RPA bots with artificial intelligence capability can scan documents and other third parties’ data to assess which parts of the company are regulatory-compliant and which parts aren’t. Especially if the M&A deal is in a heavily regulated industry, robotic process automation accelerates the pace of compliance checks and, therefore, the due diligence.
Learn more about compliance automation.
4. Financial modeling
RPA and intelligent automation tools can use the gathered data to create financial models. Alternatively, they can automatically do evaluation calculations by inputting the numbers into pre-written formulas. Accurate financial models are important because they give insight into the target company’s performance and potential.
In 1993, for instance, Quaker Oats was told to be evaluating Gatorade $1B too much. When the deal didn’t work, QO offloaded Gatorade 2 years later, it sold for $300M. So, it’s important to evaluate appropriately.
5. Market research
Due diligence processes can benefit from alternative data, such as satellite images, social media sentiment, public sentiment, competitors’ monitoring, etc. These unconventional data types can help paint a fuller picture of a company’s health and will assist managers in making confident decisions as to whether to invest.
Robotic process automation-web scrapers integration can provide analyzers with alternative data. The benefit is they have higher chances of identifying hidden threats that would have gone unnoticed otherwise.
6. HR analytics
Human resources analysis is important in due diligence because it provides insights into the company’s culture, management practices, employee morale, and potential liabilities.
Robotic process automation can extract employees’ contract details, compensation packages, past performance analyses, etc. Sometimes, there’s a need for employee turnover, retraining, an educational webinar, etc. The sooner HR analysis is done, the sooner arrangements and decisions can be made. And robotic process automation accelerates human resources analysis.
Learn more about RPA in HR.
7. Vendor list analysis
A part of due diligence is learning about the target company’s global networks of partners to assess conflicts of interest, supply chain issues, and pricing challenges and learn more about new vendors and other factors for successful risk management.
Robotic process automation robots can scan vendor lists, extract factors of interest quickly and accurately, and store extracted data on centralized databases.
8. Intellectual property analysis
A comprehensive intellectual property analysis is essential in due diligence to identify, value, and protect a company’s IP assets, assess potential risks, ensure regulatory compliance, and identify future revenue opportunities. Robotic process automation bots can automate the scanning of IP analysis. Factors of interest would be the number of patents the company has applied for, the remaining length of copyright ownership, etc. Likewise, it’s essential to efficiently identify red flags about copyright infringement, existing litigations, or regulatory actions.
For more on RPA use cases
To learn more about RPA use cases, read:
- Top 100+ RPA Use Cases/Projects/Examples
- Top 10 Business Processes an RPA Chatbot Automates
- Top 12 Use Cases of RPA in Procurement Process
If you’re ready to invest in RPA, we have a data-driven list of RPA vendors.
We can help you through your journey selection process:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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