The deal is set to include an agreement for BNP Paribas’ long term management of a large part of AXA’s assets. It is expected to be signed at the end of 2024 and close in mid-2025, pending relevant regulatory approvals.

The merger will create a mega-manager and leading player in the European sphere with roughly €1.5 trillion in assets under management.

Specifically, the new entity would be a leading player in long term savings assets for insurers and pension funds, BNP Paribas said in its Thursday statement.

“Benefiting from a critical size in public and alternative assets, BNP Paribas would serve its customer base of insurers, pension funds, banking networks and distributors more efficiently,” said Jean-Laurent Bonnafé, director and chief executive of BNP Paribas.

“The strategic partnership entered into with AXA, the cornerstone of this project, confirms the ability of both our groups to join forces. This major project, which would drive our growth over the long-term, would represent a powerful engine of growth for our Group.”

The joint venture is set to play into a much wider theme of consolidation seen across the street in recent years as many firms look to grow inorganically or cope with rising costs via the M&A route.

“Thanks to the quality of its teams, AXA IM is today a leading player, notably in Alternatives in Europe,” said Thomas Buberl, chief executive of AXA.

“By joining forces with BNP Paribas, AXA IM would become a global asset manager with a wider product offering and a mutual objective to further their leading position in responsible investing.”

Consolidation

Most recently we saw ABN AMRO confirm it was set to acquire German private bank, Hauck Aufhäuser Lampe (HAL) from Fosun International in May. The deal is valued at €627 million and is aimed at scaling the firm’s German activities.

In the same month, Amundi and Groupama confirmed they were teaming up to boost trading. The strategic partnership has seen Groupama AM combine its team of traders with Amundi Intermediation to help achieve its ambitions.

The years and months prior have been littered with announcements from all corners of the market announcing joint ventures or new combinations. In April, Tradeweb Markets moved to acquire Institutional Cash Distributors (ICD) for $785 million having entered into a definitive agreement.

In the same month, Kepler Cheuvreux subsidiary Ellipsis Asset Management announced it was set to expand its capabilities in the convertible bond segment through the acquisition of Rothschild & Co’s business.

Panmure Gordon and Liberum confirmed they were set to merge in January to create the UK’s largest independent investment bank, with ex-Barclays executive Rich Ricci stepping into the chief executive role of the combined entity.

Also in January, Impax Asset Management entered into an agreement to acquire the corporate credit assets from fixed income manager Absalon Corporate Credit, part of Formuepleje Group.

Looking further afield to 2023, several major deals were announced in a quick flurry on consolidation at the start of the year.

Among the headliners was news that financial services giant State Street was set to acquire outsourced trading firm CF Global, Deutsche Börse entering into a binding agreement to acquire SimCorp in an all-cash public takeover for $4.3 billion, and Deutsche Bank agreeing to acquire institutional broker Numis in a £410 million deal.

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Most elections have only a modest impact on financial markets, mostly limited to their local market. In 2024, we expect markets to focus on the US presidential elections, especially as the 2016 precedent (with Donald Trump’s victory) was followed by significant market price action (and most likely reaction). Our research actually shows that even US presidential elections have on average little impact on financial markets. However, because of the expected wide divergence in economic and international policies between the two candidates but also because of significant political polarisation in the US, we do expect a meaningful impact this year.

How does volatility alter trading strategies and are there any trading strategies that you expect to increase or decrease in popularity this year?

Rising volatility is most often associated with a risk-off market episode, with equities down and yields falling, hence long-dated government bonds and the US dollar gaining value. Volatility can also offer a buying opportunity. We are already witnessing an increase in derivative positioning around the US election day and we expect this to keep building up, especially if polls remain tight.

Which asset classes are geopolitical risks having the most impact on?

Commodities, especially oil prices, are usually the most and earliest impacted assets by geopolitical risks. Because most of inflation volatility comes historically from oil prices, this in turn has an impact on bonds. The impact on equities is not as obvious in aggregate and we often witness a late but sudden impact when geopolitical tensions morph from distant risks into much closer and more significant materialisation. Middle Eastern tensions illustrate this stock market short-sightedness with oil prices rising progressively, feeding into bond yields and, later on and more suddenly, affecting stock prices with a spike in volatility. Besides, equity reaction will vary considerably across sectors, first driven by the indirect impact of commodity re-pricing, later on via the potential increase in real rates and rise in volatility and risk aversion. by rising geopolitical risks.

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Societe Generale – FORGE’s CoinVertible (EURCV) stablecoins were used as part of the transaction, which is an effort from AXA IM and Societe Generale to adapt to technological developments to benefit their client base.

This initiative was carried out in two phases. Firstly, AXA IM, on behalf of AXA France, purchased €5 million of CoinVertible stablecoins (EURCV) from Societe Generale – FORGE, a digital asset deployed on the Ethereum public blockchain, pegged to the Euro.

A €5 million investment was then made by AXA IM in a green bond issued by Societe Generale in the form of security tokens on the Ethereum public blockchain, using the acquired CoinVertible (EURCV) stablecoins.

The green bond provides access to the reporting on carbon footprint impact of the security issuance chain infrastructure.

“Following our previous experiments with blockchain technology, we are delighted to have successfully completed our first market transaction using stablecoins,” said Laurence Arnold, head of innovation and strategic initiatives at AXA IM.

“The aim of this initiative, carried out in collaboration with Societe Generale – FORGE, was to enable us to experiment with the use of a stablecoin as a settlement asset to purchase a digital bond. Our ultimate objective is to optimise our existing processes by adopting the most advanced technologies, so we can offer the best possible services to our clients.”

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Ines de Tremiolles

In the opening session of the Fixed Income Leaders Summit 2022 (FILS) in Nice this week, buy-side keynote interviewees identified key themes including technology, connectivity, liquidity and diversity as the defining elements of the year for the fixed income market.  

In the conversation featuring Inés de Trémiolles, global head of trading at BNP Paribas Asset Management and Yannig Loyer, global head of trading, securities financing and derivatives at AXA Investment Managers, a key point was that these themes are all interconnected, and cannot be viewed independently but must be curated in combination.  

“To get data you need connectivity,” explained de Trémiolles. “Today, thanks to connectivity, with all the different platforms and systems we have, we can go a lot faster, capture better bid offer spreads. While doing that, we create data, and when we have data we can analyse it and learn more.  

“We talk about machine learning but first we need to talk about human learning – what lessons we can learn to improve our trading going forward. So connectivity is also about human relationships.” 

“We talk about machine learning but first we need to talk about human learning – what lessons we can learn to improve our trading going forward.”

Loyer also stressed the importance of tailoring solutions to buy-side requirements. “We need technology that adapts to the environment we’re in and responds to the challenges we have. There are many solutions out there, but there are also still some black holes, with very manual processes – like onboarding, where technology is still lagging. Every step in the onboarding is still manual, pretty much, from KYC onwards.”  

Regulation was unsurprisingly another focus point, with consolidated tape, transparency, clearing reciprocity post-Brexit and corporate social responsibility rules (CSR) identified as important themes. Loyer emphasised that: “We need to look at what’s happening in the future as well as keeping up with what’s happened in the past,” and de Trémiolles agreed. “By the time to rules come out you already need to be ready to put them in practice, so you need to be looking ahead all the time.” 

She also reminded the room that “regulation for the buy-side is central but we also need to keep track of regulation for the sell-side, as that can also have an impact on prices. It’s difficult to decide what to focus on, because there’s so much out there all the time. The important thing is to sit down and understand the key risks you need to mitigate, then implement that across the whole team, bringing all internal stakeholders on board.” 

According to an audience poll, having the right data is the most important factor for an FI trading desk to get right on the buy-side this year (43%), while technology connectivity came second (22%) and employing the right traders who understand the fixed income market came third.  

“Liquidity, diversity and motivating the younger generations” was also highlighted as crucial in developing the desk going forward.  

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AXA Investment Managers has started offering outsourced trading services to smaller asset managers as it becomes the latest player to enter the space following a supposed increase in demand.

A spokesperson at AXA confirmed the move, citing ongoing pressures on margins that has seen smaller and mid-size fund managers increasingly look to outsource execution and middle-office functionality.

“Due to the squeezing of margins and the need for significant investment in execution and middle-office activities, we see small or medium-sized players outsourcing these functions to larger players with this critical size,” said a spokesperson from AXA Investment Managers.

“AXA IM is one of the important players, we have the critical size and have made the necessary technological investments to enable us to become an aggregator and to recover external mandates on execution and middle-office activities.”

The team of around 70 traders at AXA, with 10 dedicated to derivatives trading, is led by Yannig Loyer, head of trading and securities financing and derivatives.

The investment manager currently executes orders for its own funds and mandates, and other AXA Group companies. Its new outsourcing mandate will offer execution, operations and liquidity management including financing and the optimisation of cash and inventories.

“Our critical size and our link with the AXA Group make us a first-rate player in most markets with traders present in several countries,” added the AXA spokesperson.

Loyer took over as head of trading following the departure of AXA IM’s former head of trading, Daniel Leon, who left the firm in June last year to join rival HSBC Global Asset Management.

The trend towards outsourced trading has been further fuelled by the global pandemic in recent months, with major banks Northern Trust, State Street and BNP Paribas stating in April that it was one of the most in-demand services from buy-side clients.

Several senior buy-side traders have also recently joined outsourced trading providers. Most recently, head of trading for Asia Pacific at State Street Global Advisors departed for Outset Global, to become managing director in Hong Kong.

The TRADE recently explored the outsourced trading trend as part of a special digital feature. To view the feature, please click here. 

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AXA Investment Managers has appointed the chief executive of its e-insurance business as chief operating officer.

In a statement, AXA said that Godefroy de Colombe will start the new position on 16 January based in Paris, and reporting to executive chairman of the firm, Gérald Harlin. He will be responsible for the operations, IT, data, digital, innovation, security and risk, compliance, and trading operations, AXA added.

Colombe takes on the role from Direct Assurance, AXA’s P&C (property and casualty) e-insurance business where he has been chief executive since 2012. He first joined AXA as chief of staff to the group COO in 2008, before he was appointed head of retail lines. 

“Godefroy has a deep understanding of how COO functions bring value to the business. Godefroy’s recognised leadership skills, drive and energy, business acumen, knowledge of AXA as well as strong people focus will be great additions to AXA Investment Managers,” Harlin commented. 

News of Colombe’s appointment follows the departure of AXA Investment Manager’s chief executive officer, Andrea Rossi, who stepped down last month after leading the investment firm for six years. Rossi assumed the role of chairman of the board and became a strategic advisor to Harlin, who took on a more senior role.

Harlin, who has been with AXA Group for 29 years, was due to retire at the end of last year but decided to push his retirement date back in light of the management changes. He was chief financial officer and deputy CEO at AXA Investment Managers. AXA’s CEO of Hong Kong, Etienne Bouas-Laurent, replaced Harlin as CFO as part of the management changes.

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AXA Investment Managers (AXA IM) has confirmed that its chief executive officer, Andrea Rossi, will step down from his role in December after six years leading the asset manager.

In a statement, AXA IM said that Rossi will be replaced by CFO and deputy CEO, Gérald Harlin. Rossi, who also assumes the role of chairman of the board as of today, will become strategic advisor to Harlin from 1 December when the leadership reshuffle takes effect.

“It’s often said that it is the people who make the company, and I share that sentiment entirely: in my (nearly) seven years at AXA IM, I have met people with relentless energy, unrivalled professionalism, and a constant commitment to the company and their colleagues within it. They have truly made a difference for me, and I am honoured to have collaborated with them,” Rossi said in a post of social media, announcing his decision to step down as CEO of AXA IM.

Harlin, who has been with AXA Group for 29 years, was due to retire at the end of this year but has decided to push his retirement date back to take on the more senior role. AXA’s CEO of Hong Kong, Etienne Bouas-Laurent, will replace Harlin as CFO as part of the management changes.

“AXA IM is a core asset for AXA, and I am grateful that Gérald has accepted to take up this mission for the Group and push back his retirement date,” CEO of AXA, Thomas Buberl, commented. “Building on the successful growth strategy and transformation led by Andrea over the last years, Gérald’s experience and leadership will be instrumental in harnessing the potential and energy of AXA IM’s teams, to initiate this new phase before handing over to his successor.”

Harlin also commented that he believes AXA IM can leverage its strength in a combination of alternative and core capabilities for the Group and third-party clients, to accelerate the development of the franchise.

“The quality of AXA IM’s investment teams, our diversified footprint on geographies and investment solutions as well as our strong convictions on ESG and active management are powerful assets that will help us progress AXA IM’s strategic journey,” he said.

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The next European Commission has highlighted there will be a review of certain aspects of regulations including MiFID II and AIFMD, particularly around the reporting process. However, one asset manager speaking at the InvestOps Europe conference raised concern that while the intent from the regulators is good, the outcome could be damaging.

“After the review, we may end up with additional elements of reporting, on top of the already heavy burden of AIFMD and MiFID transaction reporting to regulators,” said Stephane Janin, head of global regulatory development, AXA Investment Managers.

“In this case, we would prefer to keep the existing reporting regime. We are concerned that if it will lead to new fund reporting requirements, it will generate a significant amount of cost at a time where we want to keep fees low. It presents a significant danger.”

Patrick Pearson, head of financial market infrastructure and derivatives at the European Commission, highlighted that the body is underway with a project to map out how data is reported to each national regulatory authority, and identify ways to streamline the process and make it more efficient. However, there is some contention between the EU27 on what areas of the reporting process should be scrapped.

“Each regulator has a different perspective on reporting in order to carry out their statutory requirements. There has been difficulty in agreeing over what to scrap. We intend to have a serious discussion on this, which we hope will come to fruition,” said Pearson.

Asset managers are already gearing up for a new set of reporting rules on their securities finance transactions under SFTR, which will go live for them in October last year. They will also have to prepare for money market fund reporting as of Q1 2020.

As buy-side firms mature their reporting processes to cope with these regulations, many are now considering ditching the delegated reporting model, in which they outsource the process to their sell-side counterpart.

“As we look closer at our governance process and at the quality of data that is required, that delegated arrangement becomes less satisfactory. Institutions are open to taking this in-house as there are more middle-wear solutions available to meet your reporting obligations,” said Darryl Cornelius, head of European regulatory projects at State Street Global Advisors.

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Moreau will join HSBC GAM from Deutsche Bank’s asset management business, DWS Group, where he has held the role of chief executive since mid-2016. Prior to that, Moreau held a number of senior positions with AXA, including chairman and chief executive of AXA France, and Group chief executive of AXA UK and Ireland.

Based in London, Moreau will take on the role in September, replacing the current CEO, Sri Chandrasekharan, who is to move into a separate senior role at HSBC GAM, to be confirmed at a later date.

“We’re delighted to welcome Nicolas to HSBC. Asset management is a key area of focus for us and one we are committed to growing in line with increased client demand for products and solutions that help meet their long-term financial ambitions,” said Charlie Nunn, CEO of Retail Banking and Wealth Management at HSBC.

“HSBC Global Asset Management passed the $500 billion threshold for its assets under management this year, and Nicolas is the ideal candidate to lead the business going forward.”

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The application of artificial intelligence (AI) and machine learning (ML) technologies in financial services is being increasingly positioned at the vanguard of technology-focused industry discussion and strategies, as discussions focus on the practical implications of deploying such tools beyond middle- and back-office functions.

As margins are squeezed and costs continue to rise in light of fee compression and an increased regulatory environment, the buy-side is increasingly turning to AI and ML in the search for further efficiencies.

There can be no doubt that huge increases in data and trading volumes that the buy-side is now transacting, is forcing the need for new technologies. While taking part in a panel discussion at this year’s TradeTech Europe conference, AXA Investment Manager’s global head of trading, Daniel Leon, told delegates that his firm has no choice but to invest in new technologies because his trading desk simply cannot keep up with the sheer amount of data and information required to maintain its trading activity.

“We are not able to do what we used to do 20 years ago,” said Leon.  “Yes, you can have a specialist on leverage loan, but on the big credit market or medium and small-cap you cannot have all that information on one guy. We are trying as well to solve problems that we used to do a long time ago. For the more vintage traders it used to be that the trader would know the market and what’s traded for one month, what happened last week, they had information and that’s what typical trading used to be.

“But now we have to gain efficiency, we have to trade so many bonds that you can’t ask one trader to remember everything, to know that this sector last week had this event. We have to reconstitute the experience that the trader used to have: What has traded, what was the liquidity and what was the market impact. You can’t do that on a comprehensive basis.”

BlackRock’s global head of trading, Supurna VedBrat, echoed Leon’s sentiment on the importance of AI and data for the future of the industry at this year’s US Fixed Income Leaders Summit in Philadelphia. Focusing on fixed income markets, VedBrat told delegates that not only will AI be a key element in the next evolution of buy-side trading operations, but it will likely morph the role of the buy-side trader in the process.

“Data science and AI give us the ability to truly augment human intelligence with computing power, and you are able to do that at scale. I think it is going to materially change trading strategies that the buy-side uses. You don’t need human intelligence to pick trades, so you can automate a lot of that flow and the trader is now much more of a risk manager overseeing that the market is working the way we expect, and if not, they have the ability to step in and correct it,” VedBrat said.

Ahead of the curve

Research from TABB Group earlier this year has, in fact, suggested that the buy-side is slightly ahead of the curve in terms of AI adoption compared to the sell-side and exchange operators. Over 80% of asset management respondents stated that they were at least in the planning or research phase of implementing AI, compared to 73% of their sell-side counterparts and exchange operators. At the same time, more than 60% of buy-siders said they expect spending on AI to increase over the course of this year.

According to the research, the majority of asset managers agree that actionable insight is the biggest benefit of deploying AI technology, followed by increased efficiency and automation, strategy selection and risk management.

However, there is a false perception can sometimes be that AI and ML are relatively new to institutional trading; the truth is that both buy- and sell-side organisations have been exploring, developing and implementing such technologies for many years now.

“The key takeaway from all of this is that most capital market participants are bullish on the use of AI and big data in the near future. It is high on the change agenda at most firms, with the main use case being around the investment process, but also in trade execution and operations,” the research from TABB Group concluded.

As with most technology trends though, hyperbole has a way of dominating the discussion. Similarly to the way blockchain exploded into the financial markets’ consciousness in 2016, AI and ML have become industry buzzwords, or at the very least a misleading shorthand, that risks overstating practical applications.

Ian McWilliams, investment analyst at Aberdeen Asset Management, detailed how the understanding of what ML technologies are capable of is being distorted by a lack of understanding and exaggeration, during a panel discussion at TradeTech FX Europe at the end of last year.

“I joke that when you are advertising externally you say AI, but inside you say machine learning and actually you are just doing logistic regression and things like that,” he said. “I don’t think that’s disingenuous, maybe it’s a bit of hyperbole, but it’s not wrong in terms of definitions, because when we talk about machine learning it really is anything where you are getting an algorithm to learn from data.

“We’re taking a lot of market signals and sentiment signals, forecasting what markets are going to do in the future and using those to build trading strategies.”

McWilliams explained that the hype around elements of ML such as deep learning, image recognition and natural language processing (NLP) are distorting expectations around what are essentially tools to better model data for trading strategy decisions, particularly when it comes to conversations with fund managers.

“The interesting thing we need to think about as an industry and maybe where attitudes need to change is around interpretability of the models, which is a big question in a lot of areas, not just finance,” he said.

“Whenever we come out with a trade a question we get asked by the traditional fund managers is ‘Why is it making that trade?’ and they generally expect a very causal, A to B explanation, but that often defeats the point of these very complex algorithms. The middle ground is not good enough to just say that the algorithm says to do it, so we are doing it, but there needs to be more conversation between the quant people and more traditional people to understand there is a trade-off there.”

Beyond the middle-office

As asset managers continue to experiment with AI and ML, the goal has always been to automate manual and often repetitive tasks for greater efficiency and cost savings, freeing up time for traders to focus on more pressing tasks or complex order flow.

But, according to market participants and technologists, the use of AI and ML elements are now permeating into more intricate parts of the business. AI and ML are beginning to show value when it comes to pricing and seeking liquidity, challenges that are often highlighted by buy-side traders in the current market conditions.

“The simple trade automation, the idea of creating rules to take some of the more liquid or easier to trade orders off the books, makes sense,” said Ian Mawdsley, head of buy-side trading for EMEA and APAC at Refinitiv, during a webinar hosted by The TRADE in March.

“The reality is that we have been using both of these processes [AI and ML] for some time. If we look at algo trading supplied for the sell-side in particular, much of that was formed in the first place to automate some of the more menial tasks sales traders were performing. That has now been taken to the next level where people are looking at price discovery and liquidity discovery.”

Further to this, looking at the practical applications of AI and ML, an area that has been of particular interest to the buy-side is the algo wheel, or broker selection processes. While an algo wheel is technically a form of AI, it is on the more basic, rules-based end of the spectrum, but it does provide a solid foundation to build upon.

JP Morgan Asset Management has homed in on this space and produced a framework, known as STARS (Systematic Trading Algorithm Recommendation System), which aims to optimise the way in which traders choose algorithms using ML technology. According to the firm’s global head of equity trading automation and execution, Ashwin Venkatraman, the vast amounts of data now accessible in the market underpins and is at the heart of implementing these new tools on the trading desk.

“We’ve had [STARS] since 2017, we’ve had 90% of our algorithm placements, even back then, going through the framework and we are rolling it out globally as well,” Venkatraman said on the webinar alongside Refinitiv. “In many ways we have been there and we’ve been optimising that wheel over time. We are trying to think about this more holistically. It’s really about being data-driven in the sense that wherever we look at all functions of trading, there are different aspects to it and it is about trying  to leverage that data in the most appropriate way.”

Taking part in a keynote discussion at this year’s TradeTech conference, Antish Manna, head of execution research at MAN GLG, said that the firm went live with a machine learning-based framework for order flow and broker allocation last year.

“This framework effectively takes away the need for human to set an arbitrary target for ‘my first three brokers are going to get this amount of flow’ and continuously updating that target to having a machine that automatically does that”, Manna explained.

“The beauty of it is that it becomes a very clean conversation with our brokers; they know how we are doing things and that they will get more flow, and this machinery also adapts to changing market conditions.”

Man and machine

Despite all of the potential benefits that may be realised, there are significant obstacles when it comes to deploying AI or ML processes, mainly in the form of compliance hurdles, transparency concerns and the build vs. buy dilemma that most firms will consider at some point during implementation.

Firms are urged that they must engage with compliance departments when undertaking any technology project, and the importance of continuously assessing the model to overcome some of those transparency barriers is paramount.

The adoption and successful use of AI or ML comes with a significant resource cost attached, and as such, firms that expecting to realise quick results will be sorely disappointed unless they are prepared to play the long game.

Addressing these unrealistic expectations, MAN GLG’s Manna said that the majority of time spent on machine learning projects is used to clean data before research and development can take place, and that those firms that are only now starting their journey with machine learning should be not expect to see results in the short-term.

“The truth is, it is a fallacy and it takes a huge amount of time to build a framework where you can deliver things at scale that work,” he said. “On the machine learning and AI side of things, problems are best solved by teams of people, because you need the challenge, rigour and time to learn and fail, learn and try again; that process takes a lot of time.”

Another significant challenge is in finding the right balance between man and machine, as market participants and technologists attempt to dispel the myth that AI and ML is even close to replacing the human buy-side trader.

“Technically there is a bit of truth that everything could be automated, there is no doubt that most processes could be run without a human being, certainly within our industry,” Mawdsley explained. “The point is that the world isn’t that flat and there are certainly unusual things that happen in life every day that don’t follow the patterns and I am not sure that we are 100% there, where the AI is able to interpret all of those black swan events and build them into a model.

“There is an element that says the human brain is trained to deal with these outliers, and the machine giving help to follow those patterns is probably where you want to be… It’s about using technology to make more informed trading decisions and as such that means not fully automating everything at all and ensuring that we are bringing in an element of human intelligence, but we are presenting people with options.”

As data becomes more readily available and the size of that data continues to grow, there is little doubt that asset managers implementing AI and ML technologies are at the forefront of the future of buy-side trading, and this is happening now. As some funds struggle to adapt to the changing trading landscape, others are ready and willing to seize the opportunity using AI and ML to overhaul traditional trading processes.

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