Company valuations in the age of AI
The 5 most important questions to ask your company valuer
Many industries are being empowered by AI and we expect that company valuers around the globe will consider this too. Precision, speed and judgement in valuation work requires a combination of data and human experience. Adding AI into that mix will, without doubt, confuse many traditionalists and lead many revolutionaries down a risky path.
Here is our take on AI in company valuations and what we think business owners need to ask their valuers.
AI’s role in modern valuations
There’s more to business valuations than crunching numbers. Assessing a company’s worth demands an intimate knowledge of market trends, industry benchmarks and comparable transactions. AI tools excel at processing vast amounts of data, analysing patterns and identifying comparable businesses faster and more efficiently than people.
However, AI is not great at understanding the difference between price and value; in other words, AI can tell you what the notes of the music are, but it cannot truly hear the music. What this really means is that, in the absence of being able to distinguish between price and value, AI cannot convince a reader (IRS, HMRC, a buyer, a seller, an investor, a litigator, a jury, a judge etc) of the value gap. Funnily enough, many human valuers cannot either and so perhaps AI is only as good as a bad human valuer when it comes to understanding the business-level differences in price and value.
That being said, AI will have a role in processing large amounts of structured and unstructured data on an industry or perhaps a company at a whole and, without a doubt, it will make the first few hours of this work far more efficient than a human could do alone.
The data dilemma
But there’s a catch. Despite the potential benefits it brings, AI is only as good as the quality and breadth of data it has access to. Most AI valuation tools rely on one or two data providers, which limits their ability to generate comprehensive and accurate analyses.
This of course relies upon the valuation firm having (paid) access to data and then plugging it into the AI agent (or indeed the human!) to work from.
There are two levels of external data that matter most; firstly, the one most small valuers ignore or skimp on, the industry data. Secondly, the comparable data for revenue, EBITDA or PE multiples and costs of capital.
“Businesses need to prioritise working with valuation advisers with diverse data sources,” says Chand Chudasama, Corporate Finance Partner at Price Bailey. “We use multiple providers to minimise blind spots and increase the accuracy of our valuation models. Although we don’t use AI in valuations yet, this approach sets our clients up for success.”
“The ideal valuer has enough data for there to be conflicts; this is a good thing as numbers can lie! It’s a bit like the old adage ‘ask two accountants the same question and you get two different answers’ – the difference isn’t a problem at all, the value is in knowing why there is a difference and using the difference to solve the problem in the most appropriate way.”
Fundamentally, valuations need to embrace data that is not black and white and conflicts that are understood are a power way to achieve this. AI should enhance a valuers capacity to cost effectively uncover these conflicts and then use human insight to consider why they matter and what the consequences are.
Human oversight: The missing link
Even with robust data, AI tools are not yet advanced enough to fully understand the intricacies of every business model. Valuing a company involves more than just analysing financial metrics; it’s important to consider intangible factors too, from intellectual property to market position and organisational culture.
Such nuances are often missed by automated tools, which is why we need human expertise. Experienced advisors play a crucial role in interpreting AI-generated insights, adding context and addressing gaps that AI might overlook. Just as courts rely on human testimonies to interpret evidence, valuation analyses still depend on human judgement to ensure reliability.
The risk of the average
A major risk for both weak human valuers and AI is the risk of the average – in other words, after reviewing a data set the processor settles on a mean or median and then concludes that is the answer without considering why that is the appropriate answer. Tautologically (please don’t judge us for using that word), most of the time, the median will be the right answer. But equally, it will often not be.
If a human reaches an unsubstantiated average, then arguably they’re no more valuable than a machine that could have done the same. Perhaps that is forgivable if a junior member of a valuation teams put forward the average due to lack of experience, but upon query, the senior person whose opinion it is should have a very good reason for that being the answer.
The opportunity for value growth
A good valuer with a broad enough scope will be able to tell a client why some businesses sell for higher multiples than others. AI should get there one day but isn’t there yet. Weak valuers certainly miss this – the hallmarks of AI or valuers getting this wrong are when they say things that are obvious such as: grow profits, pay down debt, use less capital to deliver the same outcome (actually, there are plenty of AI’s that would understand the third point better than weak human valuers so perhaps the final point is beyond the capability of many).
In essence, a good valuer with enough time should be able to talk about what drives multiples up where the answer isn’t driven by the financial statements.
Practical advice for businesses: the 5 questions to ask your valuer
- What is the difference between price and value?
- What are your sources of data that will help you understand the dynamics of our industry?
- What are your sources of comparable data for multiples?
- How will you measure us relative to averages?
- What would drive up my multiple that isn’t part of my financial statements?
“Many firms are racing to be the first to use AI,” says Chand. “But it’s a balanced approach—using diverse data sources and investing in human expertise—that will deliver valuations that are both precise and actionable.”
Chand went on to say, “there will be a greater emphasis on the quality of the advice connected to a valuation, the quality of opinion and judgement and the underlying calibre of the human valuer – if the human can answer those 5 questions well, then they are well placed to give great advice and make the most of technological change to benefit their clients.”
If you have any questions about how Price Bailey can support you with your valuation, please get in touch.
We always recommend that you seek advice from a suitably qualified adviser before taking any action. The information in this article only serves as a guide and no responsibility for loss occasioned by any person acting or refraining from action as a result of this material can be accepted by the authors or the firm.
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