{"id":22274,"date":"2023-10-02T16:07:43","date_gmt":"2023-10-02T16:07:43","guid":{"rendered":"https:\/\/www.imprima.com\/?p=22274"},"modified":"2024-05-16T08:20:40","modified_gmt":"2024-05-16T08:20:40","slug":"challenges-of-making-summaries","status":"publish","type":"post","link":"https:\/\/www.imprima.com\/blog\/challenges-of-making-summaries","title":{"rendered":"Close, but no cigar: why pseudo AI fails to provide a solution to Due Diligence"},"content":{"rendered":"\n

Time Pressure and Error<\/span><\/p>\n\n\n\n

Understanding the risk or value of a company by reviewing its documentation is a time-consuming task, particularly when dealing with large volumes of documents or complex information. Time pressures can give cause to oversight. and we\u2019ve seen this in the past with examples such as Caterpillar and Siwei <\/a><\/strong>(2010) in which \u201cdue diligence oversights on Caterpillar\u2019s part and alleged \u201cdeliberate, multi-year, coordinated accounting misconduct\u201d at Siwei were uncovered months after the deal closed and Caterpillar took a $580M non-cash goodwill impairment write-down in 2012.\u201d Missing something during the Due Diligence (DD) process can cause not only financial damage but reputational as well.<\/p>\n\n\n\n

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Manual Error<\/span><\/p>\n\n\n\n

Even if there is ample time to conduct DD, there\u2019s still a high chance that something is missed – it is only human to do so. Humans, unlike machines, are susceptible to being tired or distracted, especially if a task is repetitive or laborious. The piece of information a reviewer is looking for can be buried deep in a very long document and clauses can be worded in countless different ways.<\/p>\n\n\n\n

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The problem with traditional search methods<\/span><\/p>\n\n\n\n

Your organisation may have moved on from purely manual techniques and may be using search techniques as available in Word or Adobe. Your organisation may even be using or looking into the use of \u201cregular expressions\u201d (regex<\/a><\/strong>)?<\/p>\n\n\n\n


Well, in practice, these don\u2019t cut it either. We will explain why…<\/p>\n\n\n\n


First of all, there may be unexpected spelling errors or other inaccuracies caused by low-quality scans, which will make simple search methods very difficult. But there are many more problems when you are trying clauses or key data points.<\/p>\n\n\n\n

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Finding Clauses <\/span><\/p>\n\n\n\n

Clauses can be phrased in numerous different ways. Entering an example clause with a simple search method will only return exact matches. Not very likely to yield satisfactory results: differently worded pieces of text will be missed. The fundamental issue is that it does not consider the semantics of the text.<\/p>\n\n\n\n

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Finding key data points<\/span><\/p>\n\n\n\n

If you want to find particular data points such as start dates, notice periods, or monthly rent (for example), regex can partially support this. However, while regex can help you find dates, monetary values, or names, there are two problems:<\/p>\n\n\n\n