Jan 11, 2019

A Strategy for Capital Markets Success in 2019 and Beyond: Embrace These Technologies and Trends

By James Jockle, Chief Marketing Officer, Numerix

In a capital markets environment that is rapidly evolving with new technologies and initiatives, it is my view that market participants have no choice but to accept the transformation and leverage innovations to improve business decisions, meet regulatory requirements, build a competitive advantage, help mitigate cost pressures, and generate significant efficiencies.

What are these innovations? There have been remarkable advances in AI and machine learning, data management and processing, cloud-based platforms, and digital transaction processing, among other capabilities. They offer firms with a visionary posture immense opportunities. My question to you is does your firm have a strategy or methodology in place for using these emerging technologies to succeed faster and more securely in today’s increasingly challenging and complicated capital markets landscape?

There is no single “best strategy” that will work for every organization, as each has its own unique business requirements. But seeing the future clearly and developing a proactive and calculated response can help set a firm apart. Here, I briefly examine the four technological forces and market priorities that I think should be top-of-mind for IT executives and the C-suite as we continue to move forward into the New Year.

1. Manage risk through artificial intelligence

AI is among the dominant topics in the financial markets today, offering potential benefits such as better risk management, improved operational and cost efficiencies, enhanced client services, improved data and analytics, and increased profit and revenue generation.

Validating the tremendous potential for AI application in the capital markets is the fact that, by the end of 2017, it is estimated that financial firms potentially spent more than $1.5 billion on AI-related technologies and, by 2021, potentially $2.8 billion, representing an increase of 75% over a four-year period.

While AI is still very much a maturing industry, it is gaining traction quickly, including in the derivatives space. AI could, in fact, be a game changer for risk management. The capital markets have been hammered with a regulatory tsunami since the financial crisis and, as a result, a more stringent and prescriptive regulatory environment is having a significant impact on front-office risk management technology. In fact, Chartis Research, in its recent report examining Front-Office Risk Management Technology, claims that banks can no longer put off upgrades to systems that were built for a different era and observes how in recent years banks have increasingly recognized the need to upgrade, standardize, consolidate and externalize their compliance and risk management processes and systems.

So, what we are seeing today is that some institutions are deciding to put artificial intelligence to work to augment their current front office risk management processes.

The ability of machine learning models to crunch enormous calculations and analyze huge amounts of data with more granularity and deeper analysis can potentially improve analytical capabilities in risk management and compliance, helping traders make more informed decisions at not only a securities level, but across their entire derivatives book of business. AI applications in risk management could include specific functions such as identifying the right counterparty with whom to trade, discovering potential counter-party risks, unveiling additional costs within a portfolio, or identifying new trading patterns that could be used to adjust trading strategies—all in more efficient and automated ways.

Using a real-world example, AI could potentially transform XVA pricing and risk calculations. Derivatives risk calculations are becoming more difficult to assess and it may become necessary to use AI as an approach. To put it simply, XVA is about computing potential risk now and in the future, and to accurately reflect the capital that a trade consumes over its lifetime and to ensure products are priced correctly to customers. But XVA measures are extremely complex, as are the calculations, and require an enormous amount of compute power to handle the data being generated. AI could be the solution for conducting XVA calculations, interpreting how to optimize XVA costs, and could provide signals to the risk and trading functions to help them better interpret data and make the most prudent trading decisions to optimize best performance.

2. Place an increasing focus on data & analytics

The same Chartis Research report highlights how regulatory pressures are also one of the factors impacting the scale and complexity involved in data management. Regulatory and risk management requirements are challenging financial services firms to capture, store, and analyze data that spans multiple years and multiple sources, at ever increasing levels of granularity.

Investment and trading decisions are becoming increasingly data-driven, particularly as electronic markets are leading to higher volumes and a greater proliferation of market data. Market participants are faced with having to crunch millions of data points regarding market performance, economic indicators, inventory information, and performance across asset classes. And they have to do so in order to make smarter and more informed decisions—and better mitigate risk.

So, what is the issue? It is not about being able to collect a lot of data. It’s about being able to effectively derive, analyze, and squeeze value from that data. Is your institution using analytics tools and techniques that are falling short in turning data into valuable business insights to wield against your competitors?

Industry wide there is an increasing focus on data quality, management and analysis with the market leaders investing more and more in data solution technologies that address accuracy, completeness, and timeliness—as well as to meet the regulatory requirements that demand much stronger data governance.

The time has come to turn data into a strategic function.

3. Accept the public cloud

As the volume of data—and the need for it—continues to explode, the industry is now seeing significant shift towards more flexible infrastructure, such as on-premise cloud, public clouds, or a hybrid of both. The public cloud, in particular, is starting to find high levels of adoption as acceptance of the cloud matures. And, according to Greenwich Associates, this is no longer just for non-core services—institutions are getting more comfortable with moving the processing of core market data to the public cloud.

In regard to the impact of data and analytics, in some cases the cloud offers the ability to quickly gain access to massive amounts of compute power without having to significantly increase technology costs. Financial services institutions with legacy systems, on the other hand, could have a hugely burdensome migration costs to contend with, leaving less budget available for capital investment into new technology, driving a vicious cycle of increased operating costs.

Cost pressures, however, are not the lone driver behind moving to the cloud. If you have a need for agility and horsepower to execute strategic business initiatives, then you want to consider getting on the cloud, but you first need a defined and disciplined plan that identifies your specific goals and analyzes any potential hidden costs.

4. Be open minded about industry standardization

There is broad belief that blockchain, or more accurately, distributed ledger technology (DLT), if implemented at scale, will change the way capital markets and Wall Street conduct business, and could fix inefficiencies and slash the costs of derivatives trading. But that’s been the thinking—or the hype—for a few years now, and we are still waiting for full, real world application in the industry.

But we may now have the catalyst for the wide scale implementation of DLT in the form of a broad industry effort to harmonize the way data is presented and reported, regardless of the platform used. It is known as the common domain model (CDM) and was proposed by the ISDA (International Swaps and Derivatives Association) in May of 2017. I think CDM will gain widespread industry support.

What is ISDA CDM? It is a common, industry standard digital blueprint for how derivatives can be traded and managed across their lifecycles, and creates a bedrock of standards upon which new technologies such as distributed ledger, cloud and smart contracts can be built. The implementation of CDM offers the potential for much greater automation and cost reduction, enhancing consistency, efficiency, and the ability to meet compliance needs, as well as boosting the potential for these capabilities to operate across firms and platforms in a common way.

The infrastructure that supports the derivatives industry today continues to be complex and disjointed, not to mention extremely costly to maintain. Standardization efforts can instigate automation and efficiency, as well as reduce complexity and costs, by laying the foundation upon which the full potential of nascent technologies—such as DLT and smart contracts—can be realized.

Keep an open mind to a new technology revolution.

JamesJockle James Jockle leads the company's global marketing efforts, spanning a diverse set of solutions and audiences. He oversees integrated marketing communications to customers in the largest global financial markets and to the Numerix partner network through the company's branding, electronic marketing, research, events, public relations, advertising and relationship marketing.

Prior to joining Numerix, he served as Managing Director of Global Marketing and Communications for Fitch Ratings. During his tenure at Fitch, Mr. Jockle built the firm’s public relations program, oversaw investor relations and led marketing and communications plans for several acquisitions. He also oversaw the brand development of a new company dedicated to the enhancement of credit derivative and structured-credit ratings, products and services. Prior to Fitch, Mr. Jockle was a member of the communications team at Moody's Investors Service.

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