The post-crisis regulatory tsunami that hit the capital markets over the past 10 years has had a major impact on the global industry’s workforce.Cognitive learning systems despite strong downward pressure on margins, financial institutions embarked on massive recruitment for their risk management, legal, and compliance teams to cope with the complexity of the new regulatory environment.Cognitive learning systems

The result was a profound shift in employee headcount, with a significant increase of 190,000 employees in the overall capital markets workforce between 2010 and 2016 (see figure 1).Cognitive learning systems this heightened regulatory pressure has mitigated the benefits of increased automation and productivity, which should have allowed a stabilization of the overall workforce and, over time, a reduction in headcount and related expenses.Cognitive learning systems

With regulatory reform now in hand, it is critical that financial institutions shift their focus to improving efficiency to weather the ongoing pressure on margins.Cognitive learning systems the massive adoption of new technologies such as artificial intelligence (AI) and data analytics by financial institutions is obviously a means to address this need.Cognitive learning systems the digital transformation of the capital markets is well underway and will accelerate over the next few years. Given this, opimas is expecting an enormous reduction in staff with more than 400,000 full-time employees lost by 2030.Cognitive learning systems

While the size of staff in the capital markets will drastically decrease, we also expect a shift in the profiles of employees. Indeed, digital transformation is not just a matter of deploying new technology, but also will require different skill sets to implement and monitor advanced systems.Cognitive learning systems as a result, there is a growing battle for digital talent across industries, with financial institutions vying to attract and retain talent with highly sophisticated skill sets more akin to a silicon valley start-up or publicly traded technology company rather than a wall street investment bank.Cognitive learning systems experts in AI, data science and cybersecurity, typically drawn to work at tech companies, are entering the financial industry at an unprecedented rate.Cognitive learning systems since january 2019, more than 35% of the job offers published by US and european sell-side institutions specifically target candidates with a technology profile.Cognitive learning systems yet hiring people with these skills is increasingly difficult, as the demand for tech experts is currently outstripping the supply. The reason: the ideal candidate for the capital markets must have double expertise in business, administration or mathematics and also in specific technologies such as python, data visualization, etc.Cognitive learning systems the new gem in recruitment is a candidate that possesses science, technology, engineering, and mathematics (STEM) specialization.

To adjust to the changing landscape, financial institutions must implement a new talent strategy not only because they have to recruit new employees with different skill sets, but also because they have to bridge a talent gap within their own organizations.Cognitive learning systems reskilling or upskilling current employees is a necessity, and financial institutions are being pushed to diversify their learning and development programs.Cognitive learning systems they also firmly rely on partnerships with universities and acquisitions of fintech companies. In their transition to the workforce of the future, financial institutions will face significant challenges and must completely rethink their internal organization.Cognitive learning systems

While technology is increasingly fulfilling a transversal function across business lines, the organizational silos that characterize financial institutions will have to evolve toward a softer horizontal operating model.Cognitive learning systems they will have to innovate in their business functions and also in their talent management. Business and talent strategies will have to be aligned from the top, requiring strong support from executives.Cognitive learning systems

Security token offering (STO) is the new buzzword in the digital asset ecosystem, and its promoters assure that, this time, they have found the killer app that will revolutionize financial asset ownership and trading.Cognitive learning systems there are clearly a number of benefits to tokenizing existing assets via STO. Beyond complying with the existing securities regulatory framework, tokenization permits fractionalization of ownership rights, transfer of paper-based property rights into the digital world, emergence of a secondary market supported by the blockchain infrastructure, and access to a more global investor base.Cognitive learning systems A closer look at the variety of assets that are currently being considered for tokenization—ranging from company shares to diamonds and fine art—reveals, however, that we again find ourselves in a “hammer-looking-for-a-nail” situation.Cognitive learning systems the challenges when trading many of these assets is not the lack of proper infrastructure, but the expertise required to operate in these markets and the resources needed to ensure proper maintenance of these assets in the physical world.Cognitive learning systems in addition, there is potentially a clear legal distinction between different types of assets. In certain cases, the token can be the asset itself (e.G., corporate securities), but for tangible assets, it can only represent a contractual right, as the asset itself cannot be digitalized.Cognitive learning systems hence, we expect numerous initiatives to fall short of their initial objective. However, stos offer some clear potential for companies going through early-stage financing and could significantly improve the efficiency of private markets.Cognitive learning systems

STOs are particularly suited to the private markets for a number of reasons. First, the asset to be tokenized is already a financial one. Secondly, tokens have the capacity to embed shareholder agreements into self-enforcing smart contracts.Cognitive learning systems thirdly, this is a market that, despite numerous attempts to revamp its infrastructure, is still very paper intensive, requiring significant manual labour in post-deal administrative and accounting tasks.Cognitive learning systems finally, the time horizon of institutional investors in private markets, which tends to be mid-term, is well suited for the type of trading velocity that can be handled by the blockchain infrastructure. 

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While adoption of the STO mechanism by issuing companies will be incremental—by our estimates, accounting only for around 4%[FOOTNOTE]icos accounted for 17% of early-stage financing deals in 2018, according to opimas’ estimate[/FOOTNOTE] of early-stage financing deals in 2019—opimas expects that by 2022 STO market value will reach US$19 billion, which is equivalent to 13% of the funds allocated by venture capital firms in 2019 alone.Cognitive learning systems post-2022, STO growth is likely to accelerate as the market matures and acceptance expands beyond early adopters.

The development of stos in private markets could eventually pose a threat to the existing capital infrastructure, notably for listed equities, as companies that have issued security tokens are unlikely to conduct a traditional IPO in their bid to become publicly traded.  while they will certainly have to register with local regulators and provide the required transparency and financial reporting, there would be no need to change their tokens into shares and transfer them from a blockchain infrastructure to a legacy one, trading them on an exchange or over-the-counter (OTC).Cognitive learning systems therefore, it is quite probable that eventually STO adoption in private markets will cause the attrition of traditional ipos and, over the longer term, pose a clear threat to investment banks that usually get 3-7% of the deal size when taking firms public and also to central securities depositories (csds).Cognitive learning systems

The development of the STO market represents a clear opportunity for service providers in the digital asset space. Our conservative estimate is that, in 2022, roughly US$250 million in revenues will be generated by token issuance providers.Cognitive learning systems in the same year, digital exchanges and broker/dealers will share close to US$4 billion from STO trading revenues. 

The size of the STO market, the threat that it could eventually represent to legacy infrastructure providers, and the significant potential upside are driving a limited number of incumbent players—mostly exchanges—to beef up their offerings and develop partnerships with fintech providers.Cognitive learning systems but the vast majority are still taking a wait-and-see approach, as numerous factors—e.G., macroeconomic, regulatory, and technological—could tamp down STO enthusiasm.Cognitive learning systems while it’s still early days, tokenization has the potential to dramatically alter the dynamic for a number of asset classes that are ill-served by the existing legacy infrastructure.