Deal-making in private equity (PE) has traditionally been and is likely to remain dependent on interpersonal relationships. But technology is playing an increasingly critical role in helping PE firms take quicker, more informed decisions on deals and in cutting through the sometimes exaggerated claims made by companies that they intend to acquire.
In DealStreetAsia’s last webinar for the year, held on 12 October, Apis Partners operating partner Nigel Lee, and Quadria Capital founder and managing partner Abrar Mir discussed the scope and limitations of AI and technology in the PE space with Adam Nguyen, co-founder and senior VP at eBrevia, a DFIN company.
Moderated by DealStreetAsia’s editor-in-chief Joji Thomas Philip, the discussion delved into not just the impact of COVID-19 on deal-making, but on how PE firms who were behind the curve when it came to technology adoption, could sensibly deploy AI. The webinar was organised in partnership with DFIN.
Joji Philip (JP): Nigel, to set the context – in the last 8 to 10 months, what has really changed in terms of deal-making for Apis? Has your speed or strategy changed? Have certain sectors or geographies become more relevant?
Nigel Lee (NL): The strategy has not changed. We focus on fintech-enabled, capital-light financial services in emerging markets. While many others have focused on B2C investments in fintech, we have focused more on B2B. We have invested in infrastructure plays that rise with the tide of electronic transactions and financial services. That strategy has been supported by what has happened over the last 8 to 10 months. Companies in that space have grown dramatically or not seen the downside, that perhaps physically-based commerce has seen.
Our aim has been to do a couple of deals every six months. We closed our last deal at the tail end of last year. We have closed three in the second fund since the first close, which was about July to August 2019. We built up a head of steam going into the period of COVID. In some sense, the deals have slowed down. Partly, though, that’s been of our choosing. We have taken a call that we need a couple of quarters of new information on companies that we are talking to. It will help us understand where they are going to land, to make sure our valuation expectations are sensible.
While deal closing has slowed, the strategy hasn’t changed. We have backed away from items in lending. Particularly in Indonesia, where we did a lot of work looking at P2P and supply chain lending over the last 18 months to two years. We decided not to make investments in there until we got more information. It’s a nascent sector and we know it is hurting now, but we will come back to it, maybe in the next 12 to 18 months.
Geographies haven’t changed, either. Many people might think we’re mad or brave by being involved in places like Africa and in some of the more emerging Asia countries. But being a sector specialist helps us. Combined with being a specialist in emerging markets, it means that you continue down that track. We’ve done enough to know what works and what doesn’t.
JP: Abrar, I am assuming this must be the best phase of deal-making for Quadria – you largely focus on health tech, medtech, hospitals and pharma. Has the pandemic thrown up opportunities that would have taken a lot longer to emerge?
Abrar Mir (AM): There has been a huge amount of capital coming towards healthcare that predates COVID. Around 10 years ago, healthcare accounted for about 5 per cent of PE capital flow. Over the last two years, it has been the second-largest sector after technology at about 15 per cent. With COVID, we will see even more money. It’s not just the private sector, but also the public sector. People are calling healthcare the new defence industry.
Many businesses in healthcare have gone through phases that are not yet over. The first was led by safety and capitalisation – ensuring that the supply chain remains strong and that balance sheets are resilient. The numbers of patients coming into hospitals, particularly for elective or chronic disease, fell off a cliff. Certain parts of the ecosystem benefited dramatically, whether it was devices, diagnostics, or drugs.
Our customers and the way that they access our products have all changed. The hardest part for us as an investor is to figure out the consequences of these changes. Are they short or long term? It will probably take months, maybe even years to fully understand. These changes can impact opportunities. By definition, businesses in home healthcare, telemedicine, or that are technology-led will benefit. Infrastructure hospitals with physical space may suffer.
Many players in healthcare, particularly those that weren’t very well-capitalised and who lack scale, have come under a lot of pressure. We hope there is going to be consolidation, but it hasn’t happened yet. We don’t know if it has created greater opportunities.
JP: Adam, since you deal with so many general partners (GPs), have you seen any changes in terms of PE deal-making in 2020? Has the pandemic impacted the demand for your services?
Adam Nguyen (AN): We are like the canary in the mines. eBrevia uses AI to analyse contracts and automatically speed up the process of contract review. I’ve seen a pause in terms of deal-making. That said, there’s a lot of liquidity. And of course, governments around the world are propping up the market, so we have an issue with valuation as well. What we’re seeing at eBrevia is that GPs are coming in, kicking the tires, and doing preliminary due diligence, without committing or going to term sheet. With AI, you can do that quickly and cheaply. You don’t have to bring an entire law firm for extensive due diligence exercise. If things change six months from now, the GPs can pull the trigger.
JP: A follow-up question for you Adam: you have mentioned how tech can help. But, broadly speaking, are PE and VC firms even equipped to use the technologies that we have talked about?
AN: The big players – the KKRs of the world – are investing heavily in technology, as they scale. On the other hand, smaller players are not really focused on building a solid foundation using technology, because of lack of resources or a focus on growing assets under management and finding deals.
The clients coming to us tend to be larger PEs and other larger players – big law and accounting firms and corporates.
JP: Nigel, most analysts believe this recession will have second-order effects that impact everything from business models to consumer behaviour. Is the strategy to look for long term survivors rather than for short term winners?
NL: The PE strategy is always about long term survivors. It’s not VC – increase the multiple by five and ship it out of the door. Our fund time-frames are 10 years, our investment holding periods are around 5 – depending on macro conditions, 5 plus 1.
JP: Abrar, you are in your fourth fund now. How do you pick long term survivors in medtech and healthtech?
AM: As we speak, we have been introspecting around the best ways to use technology and pick winners of the future.
When I first started in the early 90s, Excel was a new – not fully adopted for a while, even by investment banks or early PE firms. We did an analysis in a very different way. But what is startling is that a lot of PE funds still run on Excel, 20 or 30 years down the road! This should not be our Kodak moment, where we keep beating up our portfolio companies for not digitising, even as we – as investors – are not driving that agenda forward.
We have started by looking at the data on markets in which we are making an investment. How do we predict who the winners are going to be using AI? We had no idea and started working with a local university. We were quickly told there are two big types of AI: artificial narrow intelligence – just analysing data. And artificial general intelligence. The latter is more exciting – it analyses data, growth rates, consumer trends and gives us a better way to predict which companies will emerge as winners. If the result is a new insight that we can leverage, it will definitely revolutionise the way we do business.
Usually, when we meet entrepreneurs, we are given a hockey stick projection. So, we can have the Excel mindset or try to bring in something new. It hasn’t worked yet but we are hopeful that we will get a tool that will help us navigate this going forward.
JP: Adam, when it comes to GPs, is familiarity with technology, regardless of the domain they are operating in, a unique advantage?
AN: By and large GPs are not familiar with technology. Many VC and PE deals historically have been successful because of interpersonal relationships. But going forward, there is a role for technology and AI.
My recommendation is to find narrow niches where you can start to make improvements. As powerful as AI is, there are limitations including the need to train the algorithm. And access to data – where is it coming from and how much do you need? What are the variables? And what weights do you give to certain variables?
It starts with adopting the technology, learning what it can do, and deploying it to different aspects of the organisation. At eBrevia, we look at things like unstructured data and textual language in contracts at the various stages. There is a role for technology but you have to manage your expectations. GPs in their ambition to do things quickly to solve all problems at once, often get stuck with inaction. They are unable to decide on the technology to use.
AM: We acknowledge that technology can be a great enabler. We are trying to figure out better ways to predict companies that will be winners as well as to monitor and monetise those businesses. But to be clear, ours is a relationship business – to identify companies with whom we can partner with. Even with Zoom, it’s very difficult to build chemistry with an entrepreneur. Compare that with a relationship that you can build over various meetings, dinners, getting to know his family and their aspirations. Across my entire career, the companies that really succeeded are the ones where we had the best relationships. That’s something that I wish technology can help with.
Theoretically, we can still do meetings, virtual due diligence and examine data in a data room. But can I build that trust? That’s probably the main reason, that deal flow has slowed because of COVID and the greatest limitation of technology.
AN: AI and technology are not there to replace the human component. They cannot take over the entire human value chain.
But technology can speed up repetitive, inefficient tasks. Having been a founder myself, one of the pain points that we went through is how slowly the investors move. You may have a good relationship, but can you move, review documents quickly, make a decision, and then get back to us one way or another? When I was running eBrevia as co-founder, it was frustrating to see VCs drag their feet. Meanwhile, we were burning through cash. Technology can help with processes that are taking away from the building of relationships between PEs and founders.
NL: We are expected to improve the companies we invest in. But the old saying that ‘don’t use the toilet in the plumber’s house’ is very true. For the most part, when I’ve talked to GPs, they rely on the fact that life is about relationships and deal-making individuals rather than in supporting the infrastructure behind them.
A lot of the infrastructure that most corporate sectors have employed in order to improve themselves – even putting AI aside for a second – does not really turn up in funds. In my experience working with consumer sector companies, if you have got data that is not visible, you can’t make decisions. It may as well not exist.
We now look at our infrastructure for sales sourcing. We have over 30 to 100 companies that we haven’t been back to talk to, in the last six to 12 months. People are starting to realise in terms of COVID, it’s much easier to go back to those companies and understand where they are in the cycle, rather than knock on new doors. So oddly enough, COVID is forcing us to look at the way we source deals based on technology, rather than on the last person I had a meal with. GPs actually do have to get better at being able to use technology. When you are doing a full buyout, like a KKR, and you’ve got a company with hundreds of thousands of contracts, you absolutely have to find a better way to go through them than employing an army of lawyers.
JP: As PE firms a large part of your work is also raising money for yourself for funds. Many GPs say that LPs (limited partners) rely very little on technology. What are you seeing in the LP space?
AM: One of the first issues is that GPs tend to only meet LPs when they are fundraising. They only share information at that point in time and even then, the information is very selected or even selective. Even if they’ve invested, the flow of information is at a bare minimum: quarterly and annual reports. There isn’t enough data around how the deals have done – especially when compared to the original plan.
Also, about deals that GPs have walked have away from and where the LP has been charged broken deal costs. Has the GP made a good or bad decision by not investing? LPs have become far more sophisticated. They get the data from folks like PEI or Cambridge Associates, which gives them a broader view of the market and the performance of GPs. But what they’re really seeking is granular candid information from GPs themselves.
There is a bit of resistance among GPs and I am a GP, myself. While we want to give as much data as possible, giving away proprietary company information that is very granular, has a risk of getting into competition and creating barriers. Technology can play a very important role in fixing both those gaps. We are trying to create a new dashboard for LPs to say, ‘Look, even if we mask the names of companies, you can get a view of how these businesses have done against our original plan, or of the deals that we have walked away from’. We certainly hope that improves our transparency.
We are trying to get rid of the opaque shadow that covers PE. Many PE firms are criticised for being a blind pool asset class with very little information flow. We’re trying to uncover that and technology does play a very important part in shedding some illumination.
JP: Since LPs tend to go back to GPs that they have previously invested in, does that put newer managers at a disadvantage? Can this be addressed with tech?
NL: It is the responsibility of GPs to take a thesis-based approach of more transparency which will be good for us with our current LPs. It will make them want to continue supporting us going forward. LPs themselves are not very technologically sophisticated when it comes to looking across information pools to make decisions.
They do revert to managers who have delivered in the past. That makes it extremely difficult for new managers. You can be thesis-based and go to a theme-based fund and to the pool of LPs there, but frankly, they are going to fall back to where their money has been best handled in the past. Technology can help, but it’s difficult to see who’s going to take an initiative to pull information from GPs and normalise it, such that it can be consumed by LPs.
JP: Adam when it comes to the LP-GP dynamics, what role can tech really play?
AN: I’m less optimistic when it comes to LPs and technology if GPs are still using Excel! LPs include endowments, pension funds, foundations and family offices who barely touch technology. And so, they go back to the track record. If your name is recognised and you came from a prior fund that might help.
But it’s very hard for new VCs or entrants into the marketplace to get quality LPs without that personal relationship. There absolutely are limits to technology. The LP-GP dynamic is an area where I see those limits play out.
NL: I need to correct the thinking on one of the comments I made. As a fund, we have invested significantly in technology, even though we are relatively young. In the front end and middle-office technology to manage portfolio companies, and examine the risk. If we are going to be a successful fund, we actually need to have more information about the marketplace, and what we are doing with our current portfolio. From my understanding, we are probably more an exception than the rule.
JP: We have talked a lot about the PE space, but both of you have VC arms. Specifically, for early-stage investments where a lot of data may not be available, can VCs use AI or tech to better navigate potential deals?
AM: We are trying to get much more predictive around using technology, to help us find the platforms for the right opportunities in the VC space. What is relatively easier is using technology and potentially even AI to predict big themes for growth, going forward. What specific customer behaviour can help us predict that one type of business is better positioned than another? That gives us a much clearer perspective going forward.
However, that has not yet helped translate into which specific businesses within those platforms or themes are best positioned to succeed, because of the lack of data. 99 per cent of businesses operating or competing in that space is private. They won’t share details like the number of patients, the uptake of the product, or whatever the key statistic is. You won’t find that in the public domain. We can possibly think around that problem and find other data points, but that is extremely difficult. Technology and AI in particular are only as good as the data.
One of the big issues with Asia historically has been a lack of data. We get the big picture but don’t make money out of it as a macro investor. We make money out of company-specific circumstances, backing the right management teams in a very individual situation.
JP: Nigel, in the VC world, success has largely been driven by a relatively small group of individuals with access to the best deals, who typically come into them early. Can tech platforms or solutions break that structure?
NL: I’d love to say ‘yes’. And having been a CIO, I do want to believe technology can solve every problem. The reality, though, is that being sector-specific helps.
Ultimately, a lot of information is private. And it’s very hard to figure out how anyone is going to step into that space and make it public in an accurate enough manner for it to become predictive. It’s hard enough in the VC space without talking to management teams and getting a gauge on whether or not they are capable of riding a cycle through and growing a business.
To then step back and say let’s allow machine automation to make some predictions around these things – my personal view is it won’t happen in the near term. In terms of decisions about whether or not individual companies are going to do better or worse, I just can’t see it happening.
JP: Adam, what are your thoughts? Can the traditional VC industry be disrupted by AI?
AN: It is easy for VCs to get lost in the rosy outlook presented by every portfolio company. Where AI plays a role is after the initial relationship – in finding out whether the annual recurring revenue (ARR) is real, for instance. We had a situation where after due diligence using eBrevia, we saw that the ARR was by and large for six months or less. So, was it really ARR or temporary revenue? With AI, you can quickly go through large volumes of contracts and have a more accurate view.
Over the last year, we have seen WeWork and some other companies with crazy valuations. They have very charismatic founders who really led VCs and other investors down a treacherous path. With AI, VCs can make decisions that are more fact-based, with greater speed. It will differentiate the more effective profitable VCs from ones who operate purely on gut instinct. I wouldn’t go so far as to say it will revolutionise the industry. But it will differentiate between powerful players and the ones who will fall behind.
JP: An audience question: once the deals are done, when it comes to both PE and VC players, how much are they using tech to look at the risk-returns attached to certain investments?
AN: They use this a lot – even more so than during acquisition. If you are looking to improve the P&L by changing management teams or the customer mix, there is a lot of room for machine learning and AI. Especially in terms of looking at new markets or segments and understanding what you have, once you buy the company.
Many PEs and VCs, tend to look at the risk, post-purchase, but not at opportunities. There were contracts that we found, that had an automatic increase in charges on renewal. The company didn’t know those clauses existed and so were not capturing that revenue.
JP: Both Quadria and Apis manage specialist funds. Do you think specialists will have a unique advantage post-COVID?
NL: It’s an advantage even now. Having a specialist view and knowledge allows you to quickly understand what a company does and why. As a specialist fund, having looked at enough of these companies across sectors allows you to quickly make decisions, even remotely.
If you are operating in the emerging market spaces and across multi-geographies, specialisation allows you a better chance of succeeding. Both in terms of discovering companies that you can invest in, but also in terms of being able to know how to take learnings from one of those sectors in one year and translate them to companies in another.
AM: Both of us are arguably biased since we represent sector-specific funds. But being a specialist beats being a generalist. Entrepreneurs who have a lot of choices. You should aim to be someone who can actually add tangible value because of your understanding of and history with the sector. If you’re only representing capital, it is harder to establish a relationship. As a specialist, you represent access to better quality deals. But more importantly, because you can add value, you become a preferred partner to the entrepreneur.
On the other side, which is with an LP, when you are setting up your first or second fund, it is very difficult to have a generalist strategy. You will be compared to everyone else. But if you have a differentiated strategy – and that does not just mean a sector-specific focus – you’ve got a credible argument about why you are better positioned to execute on an opportunity than a generalist. Being sector specific transcends COVID.