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Blue Pool arming London investors with A-share ammo

The Hong Kong-based fintech, which combines A.I. with capital-markets expertise, says China’s entry to MSCI’s index creates an opportunity for alpha-seekers.

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Hong Kong startup Blue Pool is preparing to raise money to finance its expansion to the U.K. and Australia, says co-founder Luke Waddington.

The company is using artificial intelligence to provide portfolio managers, analysts and sell-side traders with signals to make sense of the huge volume of information now available, helping them to try to beat markets.

Waddington argues that a major reason why actively managed funds have lost so much ground to index funds and exchange-traded funds is because human teams can no longer process the vast expansion of data available on companies.

“There’s a fundamental shift taking place [in financial markets], but the active investor process hasn’t been redefined,” he told DigFin. Although traders and analysts have the tools to crunch numbers fed from exchanges and other venues, they can’t manage the firehose of unstructured information, from analyst transcripts to media reports.

“The consumption of information has become a random walk,” he said, referring to the popular random-walk theory that says investors can’t consistently beat markets because of perfect information.

The MSCI moment
The founders, Waddington and Samir Rath, set up in Hong Kong partly because it is a smaller, less competitive city than London, and also because it is close to China.

China should represent a rich territory for A.I.-driven insights, Waddington says. A.I. can deliver information at scale, while in the case of China, its financial markets are immature and so there are plenty more opportunities for active managers to outperform.

With MSCI earlier this year deciding to include A Shares in its benchmark emerging-markets index, global institutional investors will now have to invest there.

The decision by Blue Pool to open an office in London reflects the founders’ belief they can offer the market not just a service to boost alpha, but one that can be especially useful in China, where few managers have experience or knowledge.

The business has so far been funded by the founders, or financed through revenues. The A-round is meant to raise $20 million. Some proceeds are to open the London office, while the rest will go to buying data, such as analyst transcripts.

The company has identified the people it intends to hire in London, but Waddington declined to name them. Blue Pool is also opening an office in Sydney with two people, complementing its offices in Tokyo and Mumbai.

Machine-driven mojo
The business is based on the assumption that active management can once again be successful if the process is modernized, meaning it can sift through vast amounts of information about companies and deliver insights and actions.

The team uses machine learning to parse and segment English- and Chinese-language texts, decoding symbols (letters or characters) to derive meaning. This process is scalable, but not smart, so a lot of development time has gone into building software that can establish a basic set of corporate-governance rules, and compare that to the market symbols being read. In other words, they are training their computers to think more like capital-market actors.

The next step, what Waddington calls A.I., is to create relationships between the basic framework of how companies are meant to be governed with a topic or outcome that a trader or investor might want to mine, such as a theme or a sector. It works by finding correlations, rather than causations, among assets (e.g. stocks, bonds or loans).

By putting the machine learning into context, the service is meant to provide value – by figuring out signals that affect company asset prices, which human analysts might not realize were relevant.

“This produces a set of signals that explain the truth,” Waddington said. “Then we let the client’s own process take over.”

Capital markets background
Blue Pool isn’t the only player trying to arm fund managers or traders with the ability to assimilate unstructured data.

Waddington says the team’s edge is their capital-market expertise: he was previously global head of electronic business and markets at BNP Paribas, in London and Hong Kong; as well as head of RBS’s prime brokerage in Tokyo. His co-founder, Samir Rath, has run trading and investment at boutique funds in the U.S. and Singapore, as well as also working at BNP Paribas’s capital markets desks in Asia.

The partners teamed up in 2014 after deciding it would be too difficult to build a business of making money from data while working within a big bank. “Incumbents struggle with the new means of production,” Waddington said, citing their reliance on mainframe servers and slow response times.

Blue Pool leverages AWS’s cloud to stay fast and low-cost. “My unit time and cost of production blows incumbents out of the water,” he said.

Capital Markets

What Citi Ventures’s incubator seeks in Asia

Victor Alexiev, the regional lead at D10X, talks about the technologies transforming institutional business.

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Victor Alexiev, D10X

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.

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Capital Markets

Hope for handling corporate actions?

The industry is shifting from evolutionary fixes to transformational change.

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Photo: Markus Spiske on Unsplashed

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.

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Capital Markets

Stablecoin weighs Anchor for investing in economic growth

“Everything has a unit of value, except money,” says Anchor founder Daniel Popa.

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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.”

Reimagining stablecoins

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 influence

Daniel 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.

Measuring money

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?

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Blue Pool arming London investors with A-share ammo