Wednesday, September 02, 2020 / 11:50 AM / By Proshare Research / Header Image Credit: EcoGraphics
"Throughout my financial career, I have continually witnessed examples of other people that I have known being ruined by a failure to respect risk. If you don't take a hard look at risk, it will take you."- Larry Hite
The new evolution of trading in financial markets rests on digital platforms that enable clients and traders to develop relationships that save time, improve quality and hedge risks. Fintech institutions in Nigeria and collaborating stockbroking companies have noted that working through new products and sharper service delivery channels would enable greater market intimacy and provide a friendlier environment for a new generation of investors. Generation Z and Y, the new investment kids on the bloc, represent a demography that will increasingly dominate both the equities and fixed income market as they gradually improve their financial savvy and deepen their understanding of how local and international capital markets work.
The ecosystem will see greater intervention by fintech companies who will likely provide mobile applications that will enhance trading opportunities but at the same time provide options for the aggressive risk-taking younger generation to hedge their bets and reduce their susceptibility to 'animal spirits". The new fintech platforms that allow trading in a wide variety of asset classes must equally have a risk-protection mechanism that ensures that younger investors can buy financial assets but with a clear understanding of the downsides making them equipped with the knowledge of how to use loss-breakers to stabilize the overall value of their portfolios.
Financial markets can be brutal and tormenting leaving the unblooded with deep scars, but with CMOs using artificial intelligence (AI) to profile investors the 'hot' passions of youth can be tamed and allowed to mature into seasoned decision-making.
The rise of AI would enable a smoother market transaction process with traders gaining deeper insights into the requirements of their clients and the asset combinations and risk/return expectations that fit into the preferences of investors. So far technology is still fairly rudimentary as digital sandboxes are still undergoing development and testing. More sandboxes need to be deployed to provide a richer ecosystem of alternative solutions from which the best would be chosen.
To be sure, local Nigerian financial markets are steadily rising to match global standards. Fintech companies are putting pressure on the brick-and-mortar paradigms of classic trading platforms and raising the performance bar for younger investors insisting on a different consumer journey from their forbears. Indeed the new user of financial products is fixated with speed, governance, responsiveness and accuracy. Capital Market Operators (CMOs) that cannot fit into the revised framework of client expectations have one choice, to fold up. The evolving capital market environment is gruellingly competitive and crushingly innovative, the time for genteel paper-pushing has ended and operating firms that do not rethink, reimagine and restrategize their businesses could kiss such businesses farewell as digital innovation becomes an ever more powerful force for change.
In the online digital trading report for 2020, analysis shows that CMOs have become more aware of the pressures to build robust online platforms that communicate interactively with customers. The outbreak of the coronavirus pandemic in late 2019 has made the case for remote business interface compelling. The report notes that the fixed income securities market is the largest and possibly the most attractive segment of financial trades. With the government increasing activity in the treasury bill and bonds market to cope with the challenges of widening budget gaps, the market for public treasury instruments has grown phenomenally over the last decade 2010-2020. While the Nigerian Stock Exchange (NSE) market capitalization rose from N11.48trn in 2014 to N12.96trn in 2019, reflecting a six-year growth rate of +12.89%, the bond market saw growth from N104trn in 2014 to N232.68trn in 2019, showing a much faster-paced six-year growth rate of +123.73%.
The Digital Deal: Asset Class Spread
Despite the faster growth in the fixed income market and the relatively larger size of government treasury trades, the digital market still favours equities. The report discovered that 72.90% of online trades are equity transactions, 14.18% mutual funds transactions(mainly equity), fixed income 5.29%, forex 2.19%, commodities 0.90% and others 3.35%. Investors appear be feel easier handling traditional equity businesses online than any other asset class. The limited nature of online trades means that the online market of asset trading in Nigeria is thin and narrow, thereby representing an opportunity.
If traders educate their clients and show them how to make decent returns on trading different asset classes, the volume of traded online business would increase exponentially and investor portfolio diversification would improve risk/return ratios. The online financial asset trading business appears constrained by a lack of strategic effort at getting investors to migrate to digital mobile trading platforms. The problem appears to be a lack of CMO-friendliness with digital technology and constraining 'muscle memory' that compel CMOs to revert to the comfortable and familiar. Fintech companies are, however, shaking things up.
COVID-19 may have wobbled CMO perceptions and their operating preferences as remote interaction increasingly becomes the new normal, with clients increasingly expressing a preference for transaction journeys that reduce a human interface. Gen-Zers in particular would want the customer experience to be plugged into a mobile digital journey similar to their daily consumer retail transactions. To improve digital online trading, CMOs will need to rethink their service-delivery buckets and drive more business to digital platforms.
Eyeballing The Survey
On reviewing the outcome of the 2020 survey that received 785 responses, the top five fastest online platforms were:
These platforms, according to the survey, provide investors with the fastest trading journeys but most of the experience relates to equity trades. What informs the choice of online trading platforms? The survey result suggests that users of online platforms made choices based on the following considerations:
The consumer experience journey has shown that financial sector clients continue to discriminate amongst online service providers for the following key reasons:
S0 where do online clients desire to see improvement in service delivery experience? The research survey suggests that the most significant areas of online service improvement required by clients are in the following areas:
The survey covers other areas of importance to retail and wholesale customers, building a body of information of strategic importance to CMOs who would need to Rethink, Reimagine and Restructure platform operations in a way that feeds into a product and process value chain that fully recognizes the needs and wants of younger demography of investors.
The Wrap Up
Most of the CMOs surveyed would need to ramp up digital service quality if they are to improve their digital conversion rates. The report shows that digital conversion rates are still relatively low for most capital market operators. Transitioning clients from brick-and-mortar trades to digital transactions have been a hard long walk because most CMOs are yet to figure out the dynamics and functional architecture of a truly virtual trading structure. CMOs appear locked in tradition and find it difficult to connect with emerging realities despite the powerful statement on a new remote work culture dictated by external business shocks such as COVID-19.
The report wraps up with the admonition that to meet client's demand along a rising expectations curve of wants and needs they must plug into a product and process culture driven by big data, artificial intelligence (AI), and a visceral understanding of generation Y and Z, anything short of this could mean the difference between corporate survival and the other side of business daylight.
Trading Technology and The New Digital Customer Experience: The J-Curve
Trading asset classes on formal Exchanges are no longer matters of physical space but that of digital cyberspace. Investors in equity and bond trades now conduct their affairs on computer devices loaded with software that drives bid and offer transactions.
The consequence of a formal format shift for the trading of traditional asset classes has been the creation of new consumer expectations and the adoption of revised methods of the interface between floor traders, analysts and investors. Technology is the new lifeblood of asset trading and so, beyond fundamental and technical analysis of equities and bonds, the trading platforms used to execute investor mandates have become critical as time has become a crucial variable in investor action.
With the timeliness of transactions becoming just as important as the particular assets traded, trading houses have had to improve the quality of their platforms in terms of data processing, research, customer interaction and generational segmentation. This has created a sort of J-Curve pattern where service delivery quality at the point of transition or upscaling of digital trading transactions shows early signs of difficulties with service quality which dip briefly at the point of the first-stage implementation and then improve exponentially. The 2020 online ranking digital trade report suggests that trading houses are still located somewhere at the lower end of the rising J-curve (see illustration 1 below).
Illustration 1 Climbing The Digital Trading Curve
Indeed, stockbrokers have improved their adoption of digital trading platforms across stockbroking houses, however, the customer service journey remains relatively poor. The speed of transactions and response to customer enquiries have not improved significantly since the last report in 2019.
Stockbrokers may have possibly failed in providing clients with the transactional experience they expect in terms of allowing customers to have regular daily digital interaction with the market through detailed research produced in a format that is quick and easy to interpret and represents actionable data. Nigeria's capital market operators (CMOs) also appear to be lax to the quality of their trade advisory services. The lack of engaging and interactive advisory activities as experienced by investors abroad prevents local CMOs from creating broad digital interaction with clients. Analysts note that the domestic trend appears to be for stockbroking firms to project their in-house research on their custom-built websites, this limits the number of eyeballs that see the research and recommendations and hurts the opportunities that exist to widen their client base.
To improve interactiveness between CMOs and their clients CMOs will need to show greater presence in the digital media space, they would need to get their research posted on leading business and finance websites and engage in online media conversations around the different financial markets. The supply of qualitative market information in the popular business media would build investor confidence, help in ensuring knowledge-based trade action and provide opportunities for CMOs to market their bespoke niche products and services. The balance would be to assess the cost of potential media partnerships with the expected revenues that would emerge from more intensive client relationships and stronger brand positioning.
Upping The Strategic Push
Going forward, CMOs will need to break into new strategic pathways where they can adopt product/service differentiation as a basis for a competitive tussle for market share. Speed, for example, at this stage goes beyond being a feature to being a value promise. The commitment to speed evolves into a conscious discovery of ways of providing excellence within the shortest practical period. Besides speed, CMOs would review cost-to-market issues. The lower the cost of delivering service the better the ability of the CMO to squeeze profit margins per trade, one clear way of reducing cost over the medium to long-term would be the adoption of big data and artificial intelligence (AI) skills to farm information and package it within a framework that gives both asset managers and investors strategic data in usable small-sized buckets.
The last arm of the CMOs digital competitive strategy would be to create service/product niches that provide non-contested (blue ocean) market opportunities. For example, repackaging the daily stock market report in a way that removes inactive stocks and concentrates on active stocks with specific threshold market capitalizations and shares price movements on a moving-average basis for the last 30 days. In other words, the strategic imperatives for CMOs would be; differentiation, cost and niche (see illustration 2 below).
Illustration 2 Digital Competitive Strategy, From Old Models To New Objectives
Of Waterfalls and Monkeys
Two models can be used to further the digital plans of CMOs; one model is the waterfall model which allows the implementation to take place in one full sweep, with execution taking place on all fronts simultaneously.
In other words, all goals are addressed at the same time or something akin to a 'full-court press' in basketball. The alternative model is called the agile model which allows CMOs to take a step at a time, using each step as a learning ladder to be lined up against the next phase of digital implementation. This approach, bearing the agility of a monkey, reduces risk and allows for incremental reviews but may be slower than its waterfall counterpart and lead to several realignments based on changing situations (see illustration 3 below).
Illustration 3 Adopting Different Digital Strategies could Involve Tough Choices
CMOs will have to decide which approach works for them, but whichever is chosen must be done with the ultimate intention of significantly improving their client's service/product delivery experience. The struggle for the digital market of the future will go beyond just understanding J-curves and classic models of competition to understanding the idiosyncrasies of the emerging generation of traders and designing services to meet the new expectations.
Online Trading: A Peep Into Tomorrow
Online trading is gradually making a shift in global importance. The need for AI in online trading in Nigeria has become more of a pillar than a building block. Artificial intelligence help brokers in getting larger trade transactions done, ensure that the stock market works efficiently with lower volatility for a period. AI presents grand opportunities for millennials and perhaps generation Y and Z that can get a quick run on its intricacies.
A wide variety of online trading platforms around the world are taking advantage of AI. Companies such as Greenkey technologies in Chicago adopted AIfor trading uses, speech recognition, and natural language processing technology to save traders time searching through conversions, financial data, and notes. Artificial intelligence is also maximized by Auquan company in U.K. Auquan's data science competition platform democratizes trading by allowing data scientists from all backgrounds to produce algorithmic trading strategies that help solve investment challenges. Also, Kavout's "K-score" is a product of its Kai intelligence platform that processes massive diverse sets of data and runs a variety of predictive models to come up with a stock-ranking rating (see Illustration 4 below).
Illustration 4 AI and The Future: Surfing The Rise
Based on the current state of artificial intelligence applications in stock brokerage by use-cases from companies operating in the space, artificial intelligence applications in stockbroking can be classified into three major segments:
In trade executions using artificial intelligence, the trade execution algorithms are programmed. When a trader executes a buy request, stock exchanges need to match these buy orders or bids, with sell orders to execute securities trades. Artificial intelligence uses statistical techniques to break up trades into smaller orders to minimize the impact on the stock prices after the trade is executed.
Also, AI can be used for the identification of arbitrage. This is a case where investment managers can potentially take advantage of differing prices for the same assets in different markets. It can search for such arbitrage opportunities and list them out to the investor in their dashboard (see Illustration 5 below).
Illustration 5 AI King of The Arbitrage Game
The second segment in which AI can be applied is discretionary trading. Artificial intelligence can prompt traders and stockbrokers with trading strategies for individual stocks e.g. AI can recommend the best stocks to trade based on the highest probability of returns the next day. This will be a certain win-win for CMOs that build business models on the customer's transaction journey (see Illustration 6 below).
Illustration 6 When AI Takes Discretion
The third segment in which AI can be applied is advisory services. Artificial intelligence can analyze financial data such as SEC filings, technical indicators, price patterns, and sentiment analysis based on news, blogs, analyst, reports and social media feeds relevant to a particular broker's marker interest. CMOs need to lock this part of their activities down to guarantee superior client services (see Illustration 7 below).
Illustration 7 AI and The Beauty of Analysis
When Online Platforms Give a Boost, a Pat and a Kick
The world is becoming increasingly digitized, automated, and advanced in technology adoption. There is a gradual shift towards the application of AI in massive online transactions. Some online trading platforms around the globe have adopted this methodology, hence the call for Nigerian online trading platforms to tilt towards this direction. The speed at which such technological advancement is adopted by an online trading platform will determine its competitive level and its survival in the nearest future.
An online trading platform quick to adopt this technology would record an increase in its user's satisfaction, an increase in the level of sophistication of its platform, an increase in the number of users, and also a significant rise in its brokerage revenue. A modest approach to the adoption would mean that the online trading platform would record a fair increase in user's satisfaction, continue operation in the short run to medium period, its level of sophistication would be intermediate, there would be the need for room for growth and improvement and a modest rise in brokerage revenues.
The two undesirable actions for any online trading platform would be to be slow in the adoption of AI and not adopting AI at all. Online trading platforms slow to adopt artificial intelligence in the nearest future would record a significant decline in the number of users, low level of user-satisfaction, low level of sophistication, and significant decline in brokerage revenue. While an online trading platform that fails to adopt artificial intelligence would lose a majority of its users, significant decline in brokerage revenue, a decline in user's satisfaction as they are likely to migrate to more sophisticated online platforms and would be forced to upgrade its services a sophistication to ensure its survival (see Illustration 8 below).
Illustration 8 The Online Digital Trade, Boost, Pat and Kick
Artificial Intelligence and the Nigerian Stock Market, Navigating A Black Box
Integrating and adopting artificial intelligence on online trading platforms present numerous benefits, opportunities as well as risks and challenges. Artificial intelligence suggests that the number of humans involved in trading and investment decisions decreases and this may affect markets and price actions.
Analysts have said that application of AI to asset trading could create efficiency with lower market volatility. Stocktraders, in turn, have argued that greater efficiency could come from a reduction in subjective market decisions based on human sentiment, thereby, cutting down on what investors call, 'white noise'. Furthermore, AI also reduces trading cost, it provides dynamic automated modelling and rapidly and efficiently collects and analyzes far more information than considered previously possible.
Despite the benefits of AI, there are still challenges associated with integrating it as a tool to facilitate online trading. Unsupervised, self-taught AI presents the challenge that its decision-making and financial trading processes take place in a 'black box' and they may be incomprehensible to both users and regulators. Also, implementing AI is not easy as it is expensive, requires sophisticated expertise. Furthermore, some of the commercial benefits of AI are constrained by the current regulatory framework governing financial markets, there is the potential threat of a compliance arms race as individuals and organizations try to game the system.
There are also risks associated with AI in online trading. AI programs used in trading and investing rely on third-party data sources that are susceptible to manipulation. Also, models used in financial markets stress testing may provide misleading results if they are given insufficient training. Furthermore, if many traders use similar AI strategies, they may pose a risk to market stability as different actors unwittingly act in concert (see Illustration 9 below).
Illustration 9 Inside A Black AI Box
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For: Proshare Editorial Board
Teslim Shitta-Bey Saheed Kiaribe
Managing Editor Director, Research
Downloadable Versions of 2020 Report (PDF)
Related Links - Previous Years' Reports