“Fixed income is so illiquid. You have to talk to each trader at J.P. Morgan or Merrill Lynch until you have spoken with every investment bank,” said Jeremy Son, a fixed-income trader at AllianceBernstein (AB) in Hong Kong. “I have more than a hundred chatrooms with various dealers and a lot of information gets lost.”
Whereas trading and execution in equities and foreign exchange takes place across digital channels, trading bonds is still done manually over the phone or in instant-messaging conversations. The advent of trading tools using artificial intelligence and machine learning, prevalent in those other markets, is still in its infancy when it comes to bonds.
While the largest, most liquid market such as U.S. Treasuries may have become largely electronic, that is not true for other segments – notably emerging-market credit and local-currency bonds.
Indeed, there are few statistics available in Asia, which remains a backwater when it comes to trade-tech. “No one knows what the split between voice and electronic trading is in Asia,” says Jesper Bruun-Olsen, head of Asia Pacific at Algomi, a software company that helps fixed-income fund managers aggregate data.
That’s because bonds trade over-the-counter, not on an exchange; in a big national market like the U.S., liquidity is less of a challenge, but corporate and high-yield bonds are still often voice-traded. In Asia, each market is small or information is hard to access, so fragmentation makes it impossible to generate liquidity, which in turn means there’s little data available to feed a trading algorithm.
This is less of a problem for small trades below $1 million: that universe already trades electronically. But posting larger trades, especially anything above $5 million, on an electronic platform is asking for trouble. You’re going to get front-run.
Fixed income is so illiquidJememy Son, AllianceBernstein
Things are changing, however, as a result of both the external trading environment as well as technological progress. Both individual buy sides such as AB and vendors marketing platforms, such as Bloomberg, MarketAxess and TradeWeb, are racing to create automated, direct relationships with other market participants. In effect, they are using technology to recreate the pre-GFC broker-dealer market structure.
In 2015, AB’s engineers developed a product called Automatic Liquidity Filtering Analytics, or ALFA. By drawing upon data from various channels including Bloomberg, Neptune, major dealers, inter-dealer brokers, it helped traders scour the market to see if other players had bids or offers out for bonds that AB’s portfolio managers wanted to buy or sell. AB sold the software to Algomi to commercialize it.
With ALFA gathering data from the market, AB then developed Abbie – a virtual assistant – on top of it to pick the best bonds and build orders. This lets a portfolio manager determine whether a bond is liquid enough to fit her desired portfolio, while saving time for traders trying to fulfill her instructions.
Son says AB is working on two enhancements. First is a momentum indicator that guides a trader’s execution tactics. It is already in use for investment grade and high yield bond in U.S.
Second is an execution-management system to let the firm’s bots transact directly in the market. It will be rolled out within three to six months, “perhaps even sooner”, said Son.
Traders like Son used to check upwards of 20 dealers to get a particular bond, week after week if need be. The more thorough the sweep, the more likely word would leak into the market that he was on the hunt, and prices would move against him.
ALFA saved him a lot of bother. But he still has to go to a vendor platform to actually execute the deal.
AB is now building a model to allow the transaction to be done bilaterally without needing to go through an intermediary platform. It is not the only buy side working on in-house, B2B solutions.
All to All
Centralized platforms such as MarketAxess’s ‘all-to-all’ open trading platform are anonymous, but investors are wary about sending large sized inquiries, because that can potentially impact the market.
On the other side, dealers ( mainly investment banks ) are only willing to share information about their axes with “selected buy-side real-money investors like us,” Son said.
The firm is working with sell-side dealers to integrate directly, so that an indicative offer can be transacted without the price being refreshed in the meantime. This, of course, assumes that banks can offer real-time prices.
Some banks are beginning to do so via Symphony, the capital-markets communication platform. Symphony and Bloomberg are the leading venues for marketplace chatrooms, and AB wants to use Symphony as the conduit to banks able to back up direct transaction.
Platform providers: centralizing liquidity
Platform vendors are also racing to overcome bond-market fragmentation. The more liquidity, the more electronic trading; the more trading, the better to prevent information leakage.
Craig McLeod, London-based head of emerging-market product management at MarketAxess, says liquidity has already improved a lot since the 2008 Global Financial Crisis. Before then, the major global banks owned 80% of secondary bond markets. Outstanding notionals in bonds have mushroomed, in part due to quantitive easing and other balance-sheet expansions, but traditional broker-dealers have pulled back from secondary markets, due to post-GFC rules restricting capital. So all of that expanded balance sheet inventory has moved to major banks from Asia and the Middle East.
MarketAxess has an open trading framework that allows broker-dealers within its walled garden to transact, so a trader at, say, First Abu Dhabi Bank can trade electronically with ICBC.
“Asia is predominantly voice traded, but the rest of the world has woken up to the need to be invested here,” McLeod said. More buy sides are putting bond-trading desks in the region, which have to conform to European regulations around best execution. So they are keen to find electronic solutions, and platform providers like MarketAxess have a readymade venue.
“It’s not going to be a Big Bang like you had in the equities world,” McLeod said, given fixed income’s OTC nature. “Clients aren’t getting rid of voice trading but there’s more discussion around e-trading.”
From data come the tools
With electronic trading, and the data underpinning it, comes new applications for A.I. MarketAxess, for example, is building solutions for private bankers, which would give them the kind of alerts and liquidity analysis that was previously available only to broker-dealers.
“The liquidity pool is becoming one,” he said of the vendor’s all-to-all marketplace. MarketAxess is developing A.I. tools to match risk by valuing bond prices, with information sourced from client blotters. It also serves as the central counterparty between the buyer and seller, settling trades. It’s not quite a clearinghouse (which, in a futures market, would require margining and guarantee trades) but it’s a step towards the kind of centralized marketplace that exists in the equities world.
By aggregating more liquidity, and using A.I. tools, the vendor can better protect buy sides against information leakage. Each client has a profile that is tagged; the system keeps track of who honors bids and offers and their advertized prices. The idea is that users can see which accounts are honest players and which are not.
Solutions such as these are eating into the traditional inter-dealer business. But banks are constrained by regulation, and they’ll access risk via MarketAxess or another vendor if it gets them the liquidity they need, particularly in emerging markets. “We want to keep the flow monster going,” McLeod said.
A.I. in the driver’s seat?
Yet these platforms also have their limits. For fragmented markets, the likelihood of a trader pinging a counter that matches – the right bonds, at the right volume, at the right price – is low. Vendors are using alerts and other tools to help, but the majority of volumes will have to remain voice-traded, says Bruun-Olsen at Algomi.
Before big buy sides can start using A.I. and machine learning for notifications, chatbot alerts and so on, they need the data. It’s big data that creates efficiencies. But that becomes a problem in Asia because of its fragmented markets. Traders like to say that ‘liquidity begets liquidity’, but it also begets the data required to make A.I. useful. By itself, A.I. doesn’t beget anything.
So even as firms like AB develop tools to guide traders’ tactics, source liquidity and measure performance, we are a long way from A.I. taking over fixed-income execution.
What Citi Ventures’s incubator seeks in Asia
Victor Alexiev, the regional lead at D10X, talks about the technologies transforming institutional business.
Victor Alexiev is Singapore-based Asia-Pacific lead for Discover 10X (D10X), the new product incubation arm of Citi Ventures. He joined in 2018 and now covers incubation, programs and strategic partnerships for Citi’s institutional clients group.
D10X launched in the U.S. in 2016 to foster innovation from within the bank, encouraging lean-startup thinking as well as coordinating third-party build, buy or partnership decisions with other parts of the bank and its clients.
The following is a transcript of an interview with DigFin, which has been edited for style and conciseness.
DigFin: What kind of innovative models are you trying to develop?
Victor Alexiev: In Asia, it’s about new products and new services in the ICG [institutional] part of the franchise, so the projects we work on are mainly B2B and B2B2C. We’re not just looking internally. We also try to partner with technology companies as we find pain points they address.
What kind of business models are you looking for in this region?
Finding solutions for Citi’s markets, commercial and investment bank business.
Why not for the consumer side, which is such a big part of Citi’s P&L?
We do have D10X in our consumer business for North America, but not in Asia, at least not at this stage. In Asia, consumer fintech and quite fragmented and competitive, and my personal view is that you will need to put in a lot more resources in order to achieve meaningful results.
Is innovation within a huge bank, particularly if you’re focused on B2B – is that an oxymoron?
Yeah, a lot of people think that innovation with corporations is too slow. It’s true in part, as we have to go through a lot of compliance, sourcing and H.R. checks. But we’re looking after companies and people’s money. But once you identify a product fit, you scale much faster. I’m here to build something meaningful within a large institution that has a global footprint.
Within B2B, what kind of ideas are you looking at?
Most projects are new models of customer engagement. Our most public project that was built and rolled out via D10X is Proxymity, an end-to-end proxy voting platform offered to custodians, that directly connects issuers and investors in real time.
Customer engagement sounds very, um, consumery.
A lot of corporate and institutional business platforms for banks is clunky. Or it’s based on business models that just seek to skim basis points by processing large volumes. What will next-generation banking look like? What happens if banks become platforms for others to create value? What do direct-to-consumer models look like for our transaction or investment banking?
So even at the corporate level, you need better customer engagement.
That’s right. For example, an increasing number of clients want to consume our products via an API instead of calling our salespeople. We’ll still need salespeople but we have to be realistic that our evolving client expectations demand a different experience.
What does engagement mean? Can you give me an example?
We’re finding, for example, that buy-side clients are less interested in reading a full research report. But they’re very interested in parsing the underlying data that made that report. Decisions are becoming more quant-driven, so we don’t need to offer as many products. It’s about helping our clients make data-driven decisions and providing them with data-driven products
Is that just a matter of better product design?
No, it means we need to transform the entire organization, to be an end-to-end digital driver – “customer engagement” can’t be just about our front office. “Digital” is about culture and people.
I often hear about banks changing their culture, changing the ways they do business, the mindset – yet the rhetoric doesn’t describe the reality. At best it’s a partial change.
There’s an increasing urgency within banks in general. Margins are thinning, and there is a realization, or a willingness, to transform. We’re trying to speed up the process by providing examples of what “good” looks like.
Where have you implemented new solutions so far in Asia?
Initially we rolled these out in our markets and securities services business. We focused on custody, securities services, equities, and foreign exchange. Gradually we’re bringing new technologies to spread products, corporate banking, investment banking and transaction banking.
And within those divisions, what parts of Citi are you focused on? Operational efficiencies?
Efficiency is important but lots of departments are already looking at this. I also see at other banks a lot of innovation labs doing proof-of-concepts that may not reflect the actual business needs. The projects I work on all have separate, independent P&Ls, and are focused on client-centered new value creation.
You had mentioned client engagement at the institutional level. What are your clients asking help with?
Long-only funds want data to help them with things like modeling ESG portfolios (for environmental, social and governance standards). More short-term trading clients want data-centered models to take faster data-driven decisions.
We explore questions like what do next-generation pension funds look like? What about insurance? How do we support sovereign funds in managing impact-oriented portfolios?
You’re not big on blockchain consortiums and such?
We are, if it meets business needs. We participated in Komgo, a blockchain consortium for documentation in letters of credit that finance commodities trades.
What are the particular technologies that you’re trying to adopt?
Machine learning, APIs and blockchain are the three deep, transformative domains. For these to flourish requires a bigger internal transformation, a broader regulatory understanding of them, and a cultural mindset change.
That’s a lot. Any anecdotes you can give, to make that a little more concrete?
We’re about to publish with ASIFMA a white paper on STOs [securities token offerings] exploring what it would take to make these go mainstream. Our takeaway was interoperability. A fintech can issue a real-estate token, say, in their local jurisdiction, operating under the same local regulation for securities or property. But how do you open that to international investors, or institutional investors, or create a global marketing capability? The complexity quickly goes up. The same goes for, say, using A.I. with certain clients for real-time pricing and execution of F.X. or overnight collateral. What does that mean, how could it change the market? We’re exploring use cases, doing experiments – to do it right, we have to get out of the lab.
Are you finding lots of B2B technology companies in Asia who fit into these needs?
There are few startups that are enterprise-ready, globally scalable and that could deal with our clients. They need to be either close to the customers – meaning they already have insight, client integration of lots of data – or have differentiated tech that it is scalable, high performance, and can help banks solve specific problems.
But I’m bullish on tech in Asia. We’re seeing the dawn of Asian tech: the technology itself is maturing as companies shift from copy-and-paste to developing more core tech. And we’ve seen more B2B fintech move from trying to compete with us to partner with us.
Hope for handling corporate actions?
The industry is shifting from evolutionary fixes to transformational change.
DigFin moderated a webcast last week on the topic of using new tech to handle the thorny old problem of processing corporate actions. Mention “corporate actions” and you mostly have ops and tech people at financial institutions reaching for aspirin, or something stronger.
Corporate actions are anything a publicly traded company does that impacts its securities, debt or equity. Even straightforward things like a stock split come in all different flavors. There’s no one cone to hold all this ice cream. Banks, brokers, fund managers, and trading venues have invested zillions into processing transactions, but corporate actions is always “the poor cousin”, as Dean Chisholm, Hong Kong-based COO for Asia Pacific at Invesco, put it during the webcast. And because of the complexity, vendor solutions have been too expensive.
Mention ‘corporate actions’ and you have ops and tech people reaching for aspirin, or something stronger
But the industry can’t ignore corporate actions. Alan Jones, Singapore-based head of business development for Asia at SmartStream Technologies, pointed out that corporate actions today represent the highest point of risk to operations. As firms look to scale their businesses – with new markets, new products to handle, and an ever-increasing variety of actions to handle – they need to deal with this final barrier to straight-through processing. Do that, they can then begin to add value, like analytics on top that can give investment firms, for example, a view as to how good a job their service providers are doing.
The good news is that technology is evolving to the point that automating corporate actions is looking possible. The biggest enabler is cloud computing. Cloud isn’t just about saving on cost, noted David Fodor, Sydney-based head of business development for financial services at AWS. It’s about scalability and flexibility. Moving to cloud computing is the precursor to handling the vast amounts of data required to come to grips with something like corporate actions.
There’s no one cone to hold all this ice cream
Cloud is just a starting point, though. One challenge is that corporate actions involves many players, said Satyan Patel, senior VP for global client development at Hong Kong Exchange. Stock markets like HKEX connect to depositories, custodian banks, securities brokers, data vendors and investment firms. And then you have the issuers themselves, whose announcements are often in the form of unstructured data (like text on a PDF). The good news is that, beyond firms’ own IT spend, the finance industry is gradually adopting new standards, like ISO 20022 for messaging. That will help reduce the amount of unstructured data.
However that still leaves a lot of data of questionable integrity out there, which defies manual processing. Francis Breackevelt, chief operations head for Asia at BNY Mellon, in Singapore, said the full range of new technology needs to be brought to the fore. Whereas for years, transaction processing was an evolutionary process, he thinks the industry is at a point of major change. From simple robotics to natural-language processing and other forms of artificial intelligence, firms are on the cusp of tackling the variety of corporate announcements. They are looking at distributed-ledger technology to enable industry-wide processing.
Corporate actions processing isn’t going to be solved like flipping a switch. It requires a critical mass of industry player involvement, guidance from regulators, confidence in the data, greater adoption of enabling tech like cloud, and successful implementation of A.I. Then all of that needs to be implemented to the extent great enough to bring processing costs down, a lot. But fintech is making possible the goal of automating corporate actions in a way that until now has been just a dream.
Stablecoin weighs Anchor for investing in economic growth
“Everything has a unit of value, except money,” says Anchor founder Daniel Popa.
Anchor AG, a financial services company, is about to launch a dual-token stablecoin that is intended to give investors exposure to economic growth removed from the vagaries of currencies and commodities.
The company is calling for currency traders, hedge fund managers, and private investors to test its Anchor coin in advance of its inaugural listing on Japan’s digital exchange, Liquid, in September.
Anchor is domiciled in Zug, Switzerland. Its founder and CEO, Daniel Popa, is a serial entrepreneur who was born in Romania under its Communist regime but was raised in the U.S.
“Most stablecoins are mapped to gold or a fiat currency,” he told DigFin. “But currencies are all depreciating, whether it’s due to monetary policy, quantitative easing, inflation, whatever. It doesn’t matter how you peg a currency when the U.S. dollar has lost 50% of value over the past 30 years [to gold] and 98% over the last century.”
A relative latecomer to bitcoin, he wondered how a stablecoin could be created that would bypass inflation altogether. Other business interests kept him from commercializing his ideas until 2018 when he devoted his efforts fulltime to what became Anchor.
The company has developed a proprietary algorithm that generates an index that Popa describes as “non-flationary”, denominated in “monetary measurement unit”, or MMU, whose value is derived from many inputs.
Like another project in the making, Facebook’s Libra, Anchor’s algorithm uses inputs from leading world currencies and major bond-market yields. But unlike Libra, Anchor’s most important input is GDP movements from 190 countries, using data sourced from institutions or companies such as the World Bank and Bloomberg. “This gives it intrinsic stability,” Popa said, in contrast to other stablecoins.
It’s really telling you the value of the dollar or the yen, without any government influenceDaniel Popa, Anchor
The index data tracks back 25 years to when Eastern European countries ditched Communism and joined the liberal world. Since then, global growth in real terms (adjusted for inflation) has been 0.4% to 0.5%, on a 25-year average (or around 2.5% per annum in notional terms). Popa says Anchor’s value is tied to this absolute economic growth, instead of the vagaries of fiat currencies or commodities (whose value also vary over time against the dollar, making them unpredictable).
Anchor versus Dock
Anchor’s value will have to be managed actively. The company’s plan is a dual-currency launch. First is the Anchor coin itself, which Popa describes as a “payments token”, built on the Ethereum blockchain. The plan is to issue 700 million tokens on Liquid, with MMU currently trading at about 79 U.S. cents to one Anchor; the company is aiming to raise a total of around $600 million.
This money will go to seeding a fund that will invest in currencies and bonds to stabilize the Anchor token (ANCT), as will any returns on investment. As those investments gain in value over time, they will support an increase in value of Anchor tokens. The fund will be actively managed by Anchor to cover market events.
One of the vulnerabilities of stablecoins is that they can be broken in severe market conditions. Anchor is therefore launching a second Dock Token, which Popa describes as a “utility token”. ANCT is the main payments or currency token, while DOCT is utility token used systematically to buy or sell ANCT to maintain its price to MMUs. DOCT’s algorithm is built to provide incentives to ANCT users to contract or expand the supply of ANCT.
Dock Tokens are not tradable on exchanges, but serve as the gateway to access Anchor Tokens: upon purchasing DOCT, users automatically agree to its terms and conditions that build in this rebalancing mechanism, in return for benefits such as discounts when new ANCT is being minted.
“The Anchor token gives you a financial anchor in choppy waters,” Popa said. “When there’s a storm, we ask users to Dock their boat, and we burn the excess tokens in what we call a contraction phase. In other periods we ask users to expand the market.” He says this is just one of several tactics devised to maintain the stability of ANCT.
Popa declined to detail how the company defines a payments token or a utility token, saying he didn’t want to be drawn on legal issues. The company’s legal team is confident the firm is in compliance with Swiss regulations, and it will seek licenses in other jurisdictions where necessary. One of the company’s goals is to expand to other markets, with Asia a priority.
Popa, who has founded and run large-scale businesses before, wants to see the company grow quickly. It now counts 30 developers on staff, based around the world, a number he hopes will rise to 200 over the next 24 months. The priority is to grow the stablecoin and its ecosystem, with more traders using the associated Anchor app. This by itself won’t generate much in the way of revenues, but a critical mass of users would enable Anchor to launch financial services on its wallet (similar to how Libra would offer credit and other services via its Calibra app).
Popa says he hopes Libra also gets off the ground, which has many structural similarities but is fundamentally valued on fiat currencies. “The more participants, the sooner we get mass adoption of cryptocurrencies and stablecoins,” he said, adding that he expects other big corporations to enter the fray.
If the project gains currency (ba-dum-dum) then its biggest risk would be that global growth slows down. Against a backdrop of buffers against further exploitation of natural resources, climate change, and aging demographics in the world’s leading economies, is Popa worried about this?
He says no, noting that for decades growth has been constant. Even in 2008, when most countries fell into recession, aggregate business growth grew year-on-year. Moreover, he says, a momentary fall in growth would be smoothed over by the algorithm’s cumulative calculations of growth since the 1990s.
What excites him the most is how this calculation can be used. The firm’s website has a simulator measuring MMU against 19 fiat currencies plus bitcoin and Tether, going back to 2012. “It’s really telling you the value of the dollar or the yen, without any influence by a government,” Popa said.
He says the purpose of MMU is not a stablecoin per se, but to serve as a unit of monetary measurement. “Everything has a measure of unit value,” he said, noting physical phenomena such as distance, volume, pressure and so on. This endows these categories with predictability and stability.
“Everything has a unit of value, except money,” Popa said. The challenge he faces is that money is a social phenomenon, subject to human agreements rather than physical or mathematical laws of nature. Has digital finance changed that?