Arif Ahmed, ACMA, CGMA, Ph.D., author of Quantum Finance: The CFO’s Survival Kit for an Uncertain World, joined the FM podcast to discuss the relationship between quantum theory and corporate finance.
Ahmed explains why financial models are hindered by mindset, strategies for rethinking financial modelling and risk management in an increasingly interconnected era, and how finance professionals can use technology to emulate quantum principles in financial models.
“If I may use a quantum thought process, things move in small bits, but overall, once they speed up, when they start moving other things, it can create a huge wave on the shoreline,” Ahmed said. “The stimulus may not necessarily be very big, but because of one stimulus, because of the interconnection, somewhere else there’s another stimulus that comes around. And if those waves join together, they may also offset each other, or they may also join hands together. And when they join hands together, that can be massive.”
What you’ll learn from this episode:
- Why Ahmed believes quantum principles are relevant to finance professionals today.
- Some reasons that traditional financial models can fall short in today’s market.
- Why uncertainty is not a problem that models and leaders can eliminate.
- Considerations for preparing for unexpected business outcomes.
- Why technology will not replace finance professionals’ role in this unpredictable era.
Play the episode below or read the edited transcript:
— To comment on this episode or to suggest an idea for another episode, contact Steph Brown at Stephanie.Brown@aicpa-cima.com.
Transcript
Steph Brown: Hi, listeners. Welcome to the FM podcast. I’m Steph Brown. On this episode, I’m joined by Arif Ahmed, ACMA, CGMA, Ph.D. Arif is a chartered management accountant in the UK and India. He holds a doctorate in finance and is the author of Quantum Finance: The CFO’s Survival Kit for an Uncertain World. The book, which became one of Amazon’s top 50 bestsellers in the accounting theory category, explores where traditional financial models fall short in today’s markets.
We’ll discuss the relationship between quantum mechanics and finance, ways finance leaders can future-proof their approach to risk management, and tips for responding to challenges through insight instead of fear.
Welcome, Arif. Thanks for coming on the podcast.
Arif Ahmed: Thank you, Steph. Thank you so much for inviting me and allowing me a field to talk about my passion.
Brown: You’re welcome. It’s great to have you on.
Your book examines the relationship between quantum mechanics and corporate finance. In a few words, what inspired you to explore this topic, and why do you think it’s relevant for finance leaders today?
Ahmed: I’m a hardcore accountant. I’ve been away from science, let alone physics, and never even dreamt about quantum mechanics as a subject, right? Always avoided that. But when we were looking into the various aspects of models, model failure, how we try to model uncertainty, a question came into my mind: How do physicists [operate] with so little information about the outer world, about particles that they’ve never seen? So much so that a person like Einstein referred to that uncertainty or acknowledged that things are there which even he couldn’t understand.
So that led me to this area of [starting to think], can I apply the quantum principles? So that’s when I went into study it. I went to a physicist, kind of took his tutelage, and sat across from him trying to fathom out what those major concepts mean to us. And that’s when exactly I felt that there are certain errors, if I may say so. I would rather rephrase it by saying weakness, not errors, that we unknowingly fall for.
One of them is we start considering that once we have created a model, I have replaced uncertainty. Think over the finance world. I create a model, then I’m fixated on the model. Then I start believing this model is going to work. I even have a calculation of [what percentage of the time] it would not work. But what we are often not prepared for [is] that if it does not work, am I ready for it?
Because deep in my mind, I have kind of gone through a process of self-hypnosis. If you look into an organisation [and] try to even change their budget by reflecting a new change in the environment, you would find a huge amount of opposition to it. Not because they don’t want to do it, not because they are not aware of the changes, but that comfort of the static. We accountants have learned to live with a figure. I’ve been given a figure, I swear by it, if not for a year, at least for the next quarter. And you’re suddenly coming and trying to shake up that very foundation over which I have built my career, over which I have built my decisions.
I’m extremely uncomfortable. So, the first thing I do, not as a professional but as a human being, as somebody who reacts to a threat, I start believing, “No, it can’t happen to me. It can happen to somebody else, but it can’t happen to me.” It hasn’t happened to them, or it may happen to somebody very big or very small. Look at my risk management department. Twenty-three people working day and night, have the best of the data, best of the software. We almost know everything. And the little we do not know, let’s forget about it.
So, that’s what inspired me in thinking, can we bring a change in the mindset?
Brown: That’s really interesting about being clouded by optimism and believing that certain things that have happened to other businesses can’t happen to your business. Am I right in thinking that this is something that you relate to the observer effect?
Ahmed: One aspect, yes. In the observer effect, what’s happening here is various possibilities exist and they come to a static state only when I’m observing it. How’s my organisation doing? So, what I’m doing [is] asking the person, “OK, can you tell me a specific ratio?” Or, “Can you tell me how many days’ cash requirement I already have?” Now this figure is true at that moment when I asked it, and then it starts moving again. And I am starting and making my decision irrespective of that movement based on the value that I have got.
Again, a very fair question: How do I decide if everything is uncertain?
Well, of course you have to take a proxy for it, but not realising the inherent weakness of that measurement. That the measurement held true only when I saw it. Moments before, moments later, there was something else, and worse still, there could happen something else. Just because it did not happen, I did not book a huge sale, or suddenly my bank did not fail and went into a liquidity shock. Just because it hasn’t happened does not mean it cannot happen.
I jokingly tell people that in the city I come from, “In the zoo, we actually have a black swan.”
Brown: We think about the economic environment, how that impacts businesses, and technology changes. We don’t always see our role in how things have failed or maybe don’t want to see how that can happen. What are some other common reasons that traditional financial models are failing in today’s business environment?
Ahmed: The other part is in the business world, it is so interrelated, with a lot of hidden interrelations, that we actually fail to recognise the entire chain of events possible.
For example, when Lehman Brothers failed, I’m very sure that 20 years down the line, one of the primary school teachers who will retire after 20 years will get a wee bit less pension benefit. Now, how would this fiasco on Lehman Brothers move on to the budget of the bread and butter of that Norwegian primary school teacher 20 years down the line?
The line is so faint that we often overlook it. I just gave an extreme example. So, the rice producers may decide whether to switch crops depending on whether in another environment, another staple food is in demand, or a doctor has suggested that you move to a particular kind of rice. So, all these are so interrelated, but when we create those variables into our models, we replace them with a static figure.
Again, don’t get me wrong. I’m not saying that you can run a model without a static figure. All I’m trying to say is if there are five variables and each variable can assume 50 dimensions, then I can create a table in which I run all those dimensions to get a complete picture. I may choose one of them, thinking that this is most likely to happen. That does not remove the possibility of others happening. However low a probability it may have, it is still possible.
So, this fine line of difference of possibility and probability, somehow, we need to bring into our computational framework.
Brown: I guess thinking about how we have to now prepare for worlds or universes or positions in our market that we can’t even see yet, how can finance leaders then make those models and those systems more resilient?
Ahmed: We would need to be very clear about what we mean by resilience. Resilience does not mean accuracy. Resilience means adaptiveness.
The moment my inputs change, scenarios change, can this model survive those shocks? I’m not even talking about the output. Would the model itself become irrelevant? Or can the model have plug-ins which will automatically fit in, drop something else, and take some new variable as new economic dimensions emerge? That’s what I would call resilience.
I’m told that the common house lizard is the nearest relative of dinosaurs that is still living. So maybe they knew something. They evolved in some way that they stayed. I’m also told that a cockroach would survive a nuclear holocaust. So that’s what I would call resilience. I am relevant today; I’ll be relevant tomorrow.
What is important is to realise the uncertainty. In all my posts and discussions — people have now started almost associating me with that — I say that uncertainty is not a problem that you solve. It is a reality you live with. So, your models will remain, will fail. That’s taken. The question is, can you survive that failure? So, all of us in risk management departments must think, can we survive that failure? And not think the model is likely to fail only once in 10,000 times and “I don’t think that’s not going to happen on my desk”. So, get out of that comfort zone. Tell people, go up to the management, tell the board, tell the risk management committee, this is only a model. This is not replacing reality, and this is a product of a certain process.
This is not an oracle. I’m not going to talk about tomorrow. I’m going to talk about tomorrow as I perceive today, as I perceive at this moment, as I perceived at the moment when I created the model and ran the model. Nothing beyond it. Don’t expect magic out of it. I think this realisation itself will tone up the top management, tone up the owners, the shareholders, to come out from this sense of false expectation.
Brown: Leading into the book’s title, that preparing for this and living through this uncertain environment and becoming more adaptive is a key part of a CFO’s survival. What are the two or three top key elements of surviving into the next 10 or 20 years in the fast-paced environment that we’ve got now?
Ahmed: All right, that’s, I think, a very, very pertinent question, and the question I was afraid of.
The areas I must recall are to understand first the input variables. Do the input variables to my model change? Is my business model changing? Would I call the app cab services a travel business or is the service an IT business? Is the pricing a product of market demand alone, or also a product of psychology?
When a certain person comes up on the stage to make a declaration, and when we have gone there, have we already entered the room with a biased mind? “That person’s a genius, we can’t fail.” So I am already gullible. So, whatever the person says clouds my thought process, resonates with my inherent fan following, and makes me biased. It creates a smokescreen which does not let me see. And worse still, I don’t even recognise that I’m driving through a foggy territory.
So, I think that part, the clarity of understanding the process, how the model works, how the business works, and to what extent the model reflects reality — that I think is the major part of what we need to do. We need to come back from that high citadel of saying that I have a magic wand which can convert the future into a model which will hold. The law of averages is a very interesting and a very unkind tool. It holds in the long run, and the long run may be a very long run.
Just to give an example, I know there’s a 5% chance of failure, or let’s take a 5% chance of a product return. Now, finance professionals have a, I should say, comfort in placing everything against the financial calendar. We were hardened into that process. Budget, one year. Accounting, one year. Quarter ending. First January to 31 December, July to June, April to March. That has gone into the system. Now we don’t recognise that the concept of average is not time-bound. So, if I’m expecting 5% and I have 10,000 products to roll out, it may be very possible that in the first year itself I’ll get 20 back, nothing in the next three years, and on the fourth year I’ll get five back.
So, if I take the average, my 5% holds. Can I survive the first 20? That is where the job comes in. That is where the understanding comes in. And if I cannot, do I take the risk? And if I’m taking the risk, have I informed all my stakeholders? Profit is a road of uncertainty. Taking risk. Let’s believe in that. Let’s believe that I’m taking a risk, so I may not get a profit. I take a risk and then I start thinking that I will mitigate away, or wish away, the risk, least of all by creating models. That does not hold.
We have fantastic, brilliant finance professionals working around. Once this thought process goes into their mind, they will know how to change this. They will know how to change the models, how to present it to the board and to the shareholders. It’s very much within their competence. All I’m looking for is to instil this thought process in their minds. If I may use a quantum thought process, things move in small bits, but overall, once they speed up, when they start moving other things, it can create a huge wave on the shoreline.
The stimulus may not necessarily be very big, but because of one stimulus, because of the interconnection, somewhere else there’s another stimulus that comes around. And if those waves join together, they may also offset each other, or they may also join hands together. And when they join hands together, that can be massive. Are we ready for the massive? Is it possible for us to be ready for the massive? If not, it’s fine. You cannot change it. I must know it.
Brown: There’s expected to be, anyway, technology that can help us prepare for these uncertain futures. And some researchers expect quantum computing to be a reality by 2030. What are your thoughts on that, and how can organisations prepare for that level of technology?
Ahmed: Well, quantum technology by 2030 is very much expected, but may not be within the reach of many organisations at that point in time. There are some lovely experiments that have been done with MIT, IBM, and the finance industry per se. Unfortunately, most of them happened on the investment management side. You won’t find much on the corporate finance side, and the majority of the finance community are in corporate finance.
To make a small beginning, what we can understand, even in the normal machinery that we have today, there are certain tools on quantum machine learning, right? Just like we do normal machine learning, there’s quantum machine learning. And there are certain libraries which can emulate quantum computing. Not too much, not to a very great extent, but the number of variables they can play with may jolly well solve a standard corporate finance problem.
So, I think if we start learning how those quantum machine-learning tools operate, how they treat the data, what kind of simulations they create, and what kind of superpositions, as we call them, they can emulate, that would be a very nice beginning. Because in the back of my mind, I will know what kind of data set I need to fit in, what kind of qualitative improvement I can expect in my decision-making, and how [to] make my stakeholders ready for it.
Again, keeping in mind that we should not think that just by running it through a quantum computer, I have solved the problem. I will never solve the problem.
Brown: I think that’s a really great note on the kind of realistic expectations we can have on technology in its infancy in a lot of ways.
It’s such an interesting topic. Uncertainty is something that makes people quite fearful and avoidant. What are two or three steps organisations can take to ensure their decisions are informed by data and not by fear?
Ahmed: The first thing I’ll put on the top: Organisations [need] to recognise that uncertainty is constant.
Now, coming from that, we need to understand again that the zone of probability, the timespan of probability, and the timespan of my accounting reports are not the same. They’re not coterminous, if I may use a technical word. They don’t terminate every year. A doctor does not sit up and say, “OK, my mortality rate of patients is 3%, and 3% have already died, so the rest all will survive.” They’re not coterminous. They run across over the period. That’s where I think the accounting profession, and the management accounting profession in particular, has to do a lot of soul-searching.
I am breaking up a profit-and-loss account and a balance sheet. I am looking into a moving object in a profit-and-loss account, and I’m looking into a balance sheet, seeing where they can terminate or where they have terminated. They’ve never terminated. They’ve just stalled there for you to observe. They have moved far beyond that point when you’re taking the decision, but you’re looking at that still image to take that decision. That is the other area.
The other one you spoke about is bringing in technology. There is lots of confusion in people in terms of thinking whether technology can do the work of a management accountant. If we can model everything, are we irrelevant? I tell people that the first time my relevance was challenged was in the early 1990s, when something called a Lotus 1-2-3 came up as a spreadsheet. When Excel came up, we were challenged again. When ERM came up, we said you were out. They didn’t win. We have all survived.
We have all survived because we have changed our role from a bookkeeper to an accountant, from an accountant to an in-house analyst, from an analyst to a strategic adviser. That’s the leap we now look into. And to help bring that, the data is there.
Data is our comfort. My decisions may be wrong. The problem is that when I take a decision, I do not have the advantage of future. I do not have foresight. But when I’m evaluated, the person evaluating me — they all enjoy the advantage of hindsight. My future is their hindsight. So, it’s easier for them to ask me, “Why did you take that decision?” But if my data is there, if my model is there, if my understanding is clear, I’ll go back and say, “Yes, it went wrong, but give me the same set of data, give me the same environment, and ask me to take the decision today, I’ll still take the same decision.”
That confidence, that arrogance of knowledge, I think all of us must practise that.
Brown: Arif, thank you so much for being on the podcast today. I’ve really loved this conversation.
Ahmed: Thank you, Steph.
