Channeling Darwin: Big Firms Tackle Innovation

Steve Grob, director of group strategy at financial technology provider Fidessa, said large firms can be just as innovative as smaller rivals if they borrow from the principles of natural selection to take advantage of their scale and resources.

Grob told Markets Media: “Innovation is a function of resource and effort so larger firms should be better at innovation if they are organised properly. Most large firms have the resources but they are poorly co-ordinated and they need to focus on a smaller number of areas.”

He has written a paper, “Natural Innovation: A theory of innovation for larger firms in financial markets”, inspired by Charles Darwin’s theory of evolution by natural selection. Darwin’s premise was that a random mutation that favours a particular species’ survival is automatically selected and makes it through to the next round of evolution.

“Natural selection is the most creative force and I wrote this paper to see if there were some self-evident truths which could hang together and be implemented around Fidessa,” added Grob.

He said smaller firms have an advantage in being able to develop and deploy products more quickly, more commercial flexibility and that customers are more forgiving of smaller, new suppliers.

Large firms can compete by acquiring newer innovative rivals, but the results have generally been disappointing; by setting up innovation committees, incubators and labs, which can become strangled by bureaucracy while a third approach is to set up a separate investment business to finance new firms, although this indicates a corporate shift into venture capital. The paper argues that larger firms need to play by different rules.

“Innovation doesn’t work if it is done by committee or if it is the responsibility of ad hoc teams and initiatives without a focus,” Grob added. “The fanfare over incubators has waned as innovation needs to be in the DNA of a firm. Everyone needs to be cognizant of innovation and it needs high level executive support.”

Innovation can come from a steady stream of intuitive improvements and can be a function of sheer effort and resource. However large firms need a mechanism to simplify, direct and focus these efforts and repeatedly communicate the set goals to all staff.

For example, a firm might decide to focus on a new asset class, area of workflow or the application of a specific new technology to an existing business line. This should be picked up by the technical, commercial and business thinkers and turned into incremental, innovative – yet directed – evolution. For example, at FIdessa the firm started writing in different programming tools in order to think about problems in new ways. In nature not all species will evolve successfully and similarly, not all business innovations will work.

Grob said: “Measurement is crucial. It is possible to have concrete quantitative goals but they don’t fit into a typical management spreadsheet”

Goals and targets such as “grow sales by x% per quarter” or “reduce operating expenses by y%” work for established business lines but not for innovation. Better goals and targets for innovation are more incremental and need to reviewed more regularly, such as “prove the efficacy of the core business idea to five potential customers” or “build a prototype in a new technical infrastructure.”

Nature is also full of symbiotic relationships where two seemingly diverse species find a way to cooperate to their mutual benefit.

“At Fidessa we learnt that evolution is not precious and it did not matter if ideas did not come from within the firm,” said Grob.” In the fourth quarter we launched a partnership program as our customers told us they would use new technology if it was embedded in the Fidessa workflow.”

The partnership program allows multiple vetted third-party applications to be integrated into Fidessa’s workflow so that innovative new firms can meet the security, scale and resilience requirements in capital markets.

The first partner in this program was OTAS Technologies, which provides a range of market analysis tools in live trading conditions. The OTAS tools sit alongside Fidessa’s Order Performance Monitor. James Blackburn, global head of sell-side equities product marketing at Fidessa, said in a statement: “They provide traders with detailed market micro-structure analysis and the ability to drill down and understand why their orders are trading the way they are, as well as what factors might be influencing them.”

Tom Doris, chief executive of OTAS Technologies, told Markets Media that the firm was launched with idea that incumbent trading platforms would eventually open up to third-party content.

“We had no idea whether that would take two, five or 10 years or whether it would happen in a piecemeal fashion or all at once,” Doris added. “Fidessa saw the logic of doing this and took the risk and the industry is fortunate they are prepared to be a good citizen in developing the ecosystem. They have taken the leap and had the intellectual conviction to anticipate trends.”

Doris said OTAS benefits from tapping into Fidessa’s distribution channel, which is a tremendous potential accelerator, and from Fidessa’s reputation for being reliable and robust.

“Yet they have been willing to take risks and open up their platform,” Doris added. “Other platforms have been more protective and took longer to realise that third-party content will not disenfranchise, but will strengthen their offering. Fidessa made the right move and in the last six months everyone else had been running to catch up.”

OTAS now has partnerships with five trading platforms and expects to have another four by the end of this year. Doris said financial services can learn lessons from other industries where third-party independent developers produce apps demanded by users and OTAS would like to have an API (application program interface) to allow more content providers to easily join their platform.

“We have taken a lot of features from the App Store model such as the need for access to an API, which we might have to build ourselves, and centralised tracking and user entitlements,:” Doris added.

This month Fidessa announced it has signed a partnership agreement with Alpha Omega, which provides FIX-based solutions for affirmation processing through its post-trade service.

Alpha Omega, which is used mainly by the fund managers, can access the sellside through a single conformance to Fidessa’s Affirmation Management Service, to significantly reduce the time taken to on-board customers. The two firms have also agreed to collaborate on other asset classes, including derivatives.

Grob concluded: “Only time will tell if ‘natural innovation’ will prove to be the answer for larger firms, but it does offer an approach that plays to their strengths rather than those of the fintech newcomers.”

Sell-Side Technology Awards 2016: Best Sell-Side Analytics Product – OTAS Technologies

After establishing its position on the buy side as a proven provider of decision support and trading analytics, London-based OTAS Technologies announced in late 2014 that it intended to move into the sell-side space.

The strategy has apparently paid off as OTAS fought off fierce competition to secure the title as the best analytics provider to the sell side.

The role of analytics is both a desired and misunderstood one within the capital markets—while no-one wants to miss out on gathering and harnessing any data, many have little idea how to fully utilize the information they do have access to. It’s an issue of contextualization, as traders demand a seamless experience in which they’re receiving the right information at the right time and in the right context.

OTAS has positioned itself to address this demand with its suite of analytics solutions to provide live and intra-day advanced trade analysis and decision support powered by artificial intelligence and big-data analysis. The OTAS Core platform provides decision-support functionality; OTAS TradeShaper delivers pre-trade and “in-trade” analytics to traders; OTAS Base is an application programming interface (API) and visualization toolkit; and OTAS Views allows traders to create user-customizable views and analytics to help them make more judicious trading-related decisions. Users are able to select any combination from over 200 unique factors that can then be used to filter, rank and score a stock, as well as create an unlimited range of custom views.

By inputting orders manually or automatically through an order management system (OMS), users are able to factor in expected share price moves over the life of an order, the likely impact of the order on the share price, the level of risk aversion, and any other existing market insights. Alerts are sent to users to provide real-time support to identify whether to accelerate or slow down a trade in real time, based on statistically-backed information, pinpointing where risk lies on order pads or across trading desks at any given point.

In April, OTAS unveiled Lingo for Microstructure, a new extension of its existing natural language reporting technology. The service provides intra-day reports and analysis of stock activities covering the previous two years, available for both OTAS users as well as users of FlexTrade’s FlexTrader execution management system (EMS). Lingo also integrates with the Symphony messaging system, to provide traders with contextual analytics overlaying traditional transaction-cost analysis (TCA) data in a universal language to facilitate both pre- and post-trade decision making.

OTAS Bows Natural-Language Trading Report

UK-based analytics provider OTAS Technologies has extended its Lingo Suite of analytics tools with the release of Lingo for Microstructure, which produces intraday reports containing up-to-date analysis of all standout and unusual stock market activity.

The Lingo Suite, originally launched last June, encases the vendor’s Lingo natural-language reporting technology, and leverages the OTAS Core market intelligence platform to generate easy-to-interpret, on-demand analytical reports detailing calendar events and highlighting the most significant changes in price performance, short interest, options, credit, valuation, yield and technical factors, as well as recent director dealings.

The new on-demand Microstructure reports include the latest developments in the markets and their impact on users’ portfolios, allowing clients to keep up to date with market activity and make more informed risk management decisions, while also providing an audit trail of their activity, officials say.

Clients will have access to an intraday narrative on single stock behaviour to overlay with other transaction cost analysis metrics. Analysis will also cover all stocks in a trader’s universe, with a two-year record of daily stock behaviour.

Lingo for Microstructure is essentially “Lingo History” says Charlotte Wall, managing director and head of product sales at OTAS. It records on a daily basis what happened to individual stocks, and links this to a trader’s orders to provide an audit trail, and can be used to answer generic questions or provide a general narrative on the activities of every stock in a trader’s universe. Instead of having to “scramble together information and data” on something that happened to a trade months ago, traders can “click on that stock on that day, and immediately get a full narrative,” Wall says. “That’s very powerful… in a live trading environment, because you don’t normally have that information in one place.”

The reports are available to current OTAS clients and to users of trading systems vendor FlexTrade’s EMS platform—with which OTAS partnered last year—and a number of other third parties. Wall says the main appeal of partnering with Flextrade was its work with startup secure messaging provider Symphony. In February, FlexTrade integrated Symphony’s chat function to allow users to communicate and distribute content to portfolio managers and brokers directly from their trading blotter. Wall says Symphony works “very well with the Lingo narrative,” which is why they’re the first third party to gain access to it. “You can take the natural-language text and automatically be able to message that through to an end user without any human intervention… instead of having to write it out manually or copy and paste” she says.

Now that OTAS has begun to establish metrics around trade execution, it will continue to link Lingo to other products to create bespoke offerings, Wall says, adding that the vendor plans to take “a lot of the narrative and really analyze more trading behaviour in more depth. This could be to do with the schedules that are calculated in the market, it could be analyzing algos that exist and their behaviour that you can actually then write a narrative around.” This can then evolve into other products, such as intraday TCA, using the narrative to make TCA reports more robust, or more in-depth alerts on certain trades. “We also see requirements from regulators and… about market surveillance. When you have this type of audit trail and narrative, it becomes quite powerful for others to be able to have an insight without any human bias at any point in time, and to be able to reference that,” she says.

Artificial Intelligence: Robo Rules & Regulation

The rise of artificial intelligence has raised questions on its uses and possible regulation – The Trade investigates “robo rules” and we ask industry experts the question on everybody’s lips: will there still be a place for human traders?

Artificial intelligence has dominated headlines recently, highlighting the best and worst of its capabilities and suggesting there is still work to be done and improvements to be made.

News of Microsoft’s Tay, an artificially intelligent bot which was created to mimic the personality of a 19-year old woman, quickly turned sour as it seemed to transform into a ‘bitter racist’ on the social media website twitter.

When Microsoft was asked to confirm whether the bot had been shut down, it responded: “The AI chatbot Tay is a machine learning project, designed for human engagement.

“As it learns, some of its responses are inappropriate and indicative of the types of interactions some people are having with it. We’re making some adjustments to Tay.”

A more successful venture into AI was seen in Google’s AlphaGo artificial intelligence after it defeated Go world champion Lee Se-dol twice.

Se-dol said after the second defeat: “I am quite speechless… I feel like AlphaGo played a nearly perfect game.”

Both scenarios outline that machines are rapidly becoming more intelligent, and in some cases, outsmarting their human creators.

The use of AI in the financial sector has already been implemented in some cases, and investment from major players like Goldman Sachs and JP Morgan are pouring into the technology in the fight to get ahead of each other.

AI machines possess capabilities to evolve, adapt and search for patterns so asset managers can use them to enhance their investment and trading strategies.

Algorithmic trading, for example, is the most widely used form of AI and its uses complex mathematical models to make transaction decisions on behalf of humans.

Microsoft’s Tay however, has proved there is still work to be done and AI has the potential to go ‘AWOL’. So how do we control the use of AI? How do we ensure it cannot be manipulated, like Tay has been?

Robo Regulation

With AI at the forefront of discussions, questions of its uses and how it will be regulated in the financial world have been raised.

“There are likely to be layers of regulation around artificial intelligence, some sandboxed for low risk and low value trading,” said Jet Lali, head of digital at consultancy Alpha FMC.

A regulatory sandbox allows FinTech firms to test new products without “incurring the normal regulatory consequences”, according to the FCA.

The FCA says its sandbox will provide better services for users, further innovation and an increased range of products and services to market.

The scheme is part of the FCA’s plans to expand Project Innovate, with proposals on how it can work with the government and the industry “to further support businesses.”

Industry participants agree that AI will be regulated, and human “oversight” will be imperative to being compliant.

Chief executive officer at financial services firm, OTAS Technologies, Tom Doris, told The Trade: “What we see emerging is sophisticated behaviours but with human oversight and the ability to override the machine at all times.”

Alpha FMC’s Lali resonated Doris’ thoughts, and said: “Some will require human co-pilots to sign off, where more scrutiny or risk is required. Organisations will still need to indemnify retail customers for losses due to bad advice (rather than bad decision making).”

Aside from regulating AI itself, it could help regulators with implementing and enforcing rules across the financial market, as Josh Sutton, global head of AI practice at Sapient stressed.

Sutton said: “From a compliance and monitoring standpoint, AI is a game-changer. It can be deployed for policing markets and ensuring illegal activity is flagged quickly to regulators – creating a more level playing field.”

Doris at OTAS Technologies echoed Sutton’s view and explained that AI could be used to ensure a safer and less volatile marketplace.

He said: “AI systems can help with exceptional market conditions by automatically recognising when the market isn’t operating normally and alerting traders proactively and removing orders from the market while the traders assess the situation.”

Regulating AI is, however, a complex task as Henri Waelbroeck, director of research at EMS provider Portware, told The Trade.

Waelbroeck agreed with Doris and Sutton, and explained it is useful for monitoring markets: “Regulating AI itself is really an unrealistic concept.

“It may however, have a place in reducing the risk of manipulation of markets by not opening doors to practices which are misleading or incorrectly price stocks.”

The complexity of AI leads some to suggest that regulators need to learn more about its processes before setting rules on its uses.

Doris explained the concept of AI can often be confused with popular culture, and regulators need to be fully aware of its capabilities.

He said: “Regulators should know more about the route of developing autonomous entitles, with clear specifications that describes the behaviour of the machine.

“People can be confused about the capabilities of AI, on both sides, people think AI can do things it can’t and can’t do things it can. The general awareness isn’t well correlated with reality.”

Human or machine?

What does the future hold for AI? Will human traders still have a place on the trading floor?

The Trade asked industry participants whether they thought AI, with its mass of capabilities, could replace the human aspect of trading altogether.

The consensus was clear – it’s unlikely.

Henri Waelbroeck at Portware explained this would depend on the size of the company, but human traders would be facilitated by the implementation of AI on the trading floor.

He said: “It realistically depends on the firm, as some may outsource their trading to machines internally.

“Larger firms will always want to have people on the floor to watch over things, but AI will enable traders to be productive.”

Josh Sutton at sapient believes AI will, instead, shift the role of those in the industry, possibly leading to less human traders on the trading floor.

He explained: “AI could possibly replace traders, but portfolio managers will be empowered.

“The role of a portfolio manager or analyst will shift dramatically, as they understand the recommendations of AI systems.”

So it’s good news for portfolio managers, but traders may face the chop?

Not necessarily…

Jet Lali at Alpha FMC explained that even though AI ‘s capabilities are game changing, particularly in the financial markets, humans will always have a role in trading.

He said: “Despite its huge potential, AI can only take us so far; when transaction costs, large data sets and speed are not the most important factors for decision making, there will still be a role for a human trader.”

Sutton at Sapient made an interesting point when asked this question, drawing similarities from the rise of computers in the financial sector.

He explained: “The financial world will indeed become more AI driven, but computers, for example, didn’t replace traders, instead they shifted the way the financial sector operates. It’s exciting and terrifying at the same time.

“The impact of computers happened over decades, but the early stages of AI suggest the impact will be over years rather than decades.”

A combination of human and AI capabilities has the potential to shift the financial landscape spectacularly, just as the rise of computers once did.

AI is still in the early stages, as Microsoft’s Tay has exposed, but as Josh Sutton at Sapient explained, AI is being developed and implemented rapidly.

For now, it seems the job of a human trader is safe, but who knows where AI could take the trading world in the near future.