Banks are going through a crucial time right now because they have to find creative ways to manage the increased risk that comes with operating in a market that depends more on fiscal than monetary policy and managing a changing regulatory environment.
As the world’s banking institutions continue to struggle to recover from the global financial panic that occurred ten years ago, a new problem has emerged. Even while banks’ overall profitability was increasing, some continued to fall behind. Prior to the market turmoil caused by the coronavirus, about one-third of investment banks had unsustainable cost structures. These banks were operating at a significant loss and were suffering greatly as a result of their tardy restructuring.
Additionally, technology is changing financial markets. Blockchain, mobility, artificial intelligence, and the cloud have brought up new possibilities as well as new limitations and demands for changing legacy IT environments. Fintech is posing a threat to established companies in both big and small markets. Additionally, the sector can mutualize and standardize procedures with utilities for regulatory reporting, clearing, collateral, and affirmation thanks to technology.
Capital Markets Technology: What Is It?
The capital markets sector is vital to the global economy because it provides the money that people, businesses, and governments need.
To satisfy the technological demands of the sector, capital markets technology encompasses a range of services and technologies. Its goal is to provide cloud-based and digital solutions that increase productivity, simplify procedures, and provide top-notch customer support. The main aim is to guarantee adherence to evolving rules while augmenting efficacy and providing superior customer service.
Emergence of FinTech Startups
Utilizing state-of-the-art capital markets technologies, a new wave of fintech firms is upending the established value chains in the financial sector. These agile startups are offering innovative solutions for trading, investment management, research, fundraising, and more. Established players are also innovating, but fintechs are leading the charge.
Key areas fintech is transforming include:
1. Payments & Remittance. Digital payments and cross-border money transfers using cryptographic technologies and machine learning, such as Stripe and Revolut.
2. Lending & Credit Underwriting. New data sources and ML models to determine credit risk more accurately and instantly.
3. Algorithmic Trading & Quant Funds. Automated high-frequency trading strategies and data-driven funds relying on machine learning algorithms.
4. Wealth Management. Automated advisory services powered by robo-advisors and cognitive engines to deliver personalized investment advice.
As they capture value in lucrative segments, fintechs are forcing financial institutions to rethink innovation strategies.
Core Drivers of the Technology Revolution
Several interconnected technological innovations and trends are catalyzing the revolution in capital markets:
APIs and Open Banking
Open banking regulations combined with modular platform architectures are enabling fintech startups to build innovative services faster via APIs. Incumbents are also launching developer portals with APIs to foster partnerships. As more enriched data becomes available via APIs, expect creative mashups.
Cloud Computing
Allied Market Research research projects that the global fintech cloud market will expand at a compound annual growth rate (CAGR) of 16.4% between 2022 and 2031, from an estimated $44.4 billion in 2021 to $196.2 billion by 2031. Financial institutions are able to explore new business models without making significant infrastructure investments thanks to the scalability and flexibility of cloud-based systems.
Cloud computing has made it possible to deliver risk simulations, algorithmic trading, and automated reporting more quickly. With costs coming down and more workloads moving to the cloud, smaller businesses can now take advantage of cutting-edge technologies.
Big Data and Alternative Data
Harnessing new data sources like satellite imagery, social media feeds, and IoT data to feed complex analytical models is leading to better predictive insights and alpha. As data generation explodes exponentially, big data techniques like data lakes and streaming analytics help extract value. However, understanding the differences between data lake and data warehouse is essential for efficiently storing and processing vast amounts of data. Lack of talent is currently a key bottleneck, and regulatory uncertainty around alternative data also exists.
Artificial Intelligence and Machine Learning
Sophisticated predictive models powered by AI and ML are allowing deeper data-driven insights and powering robo-advisors. Firms are using AI across functions – from client profiling to fraud analytics. As models become more accurate with more data, they are being embedded into core systems.
Blockchain
Shared immutable ledgers allow peer-to-peer asset transfers by eliminating intermediaries. Blockchain-based smart contracts have the potential to disrupt many current capital market functions massively. Cross-border payments, trade finance, and proxy voting are early use cases. Interoperability across different blockchains remains a concern.
Key Impacts on Financial Institutions
The growing wave of technology innovation across capital markets is triggering deep business model changes across various financial institutions. Both long-established Wall Street banks and firms, as well as emerging fintech challengers, are undergoing technology-driven transformation.
While the nature of technology’s impact varies, virtually no financial institution is immune. The key implications on major industry segments are as follows:
Exchanges
With increasing electronic trading and new entrants offering innovative trading venues, traditional exchanges are upgrading core systems to achieve lower latency, higher throughput, and shorter settlement times via technologies like in-memory computing and blockchain. Some exchanges are also launching cryptocurrency trading platforms to address growing interest.
Investment Banks
Migrating trading platforms to the cloud, building low-latency networks powered by AI, and leveraging alternative data and ML for more accurate modeling are enabling banks to improve trade execution while reducing costs and risks. Technologies like intelligent document search and analysis are expected to raise investment bankers’ productivity.
Asset Managers
New robo-advisory services built on automated portfolio construction and rebalancing algorithms are reaching retail investors. For institutional investors, AI and big data are powering the shift from purely fundamental analysis to data-driven systematic strategies. With increasing access to alternative datasets, asset managers are launching more quantitative funds.
Insurance Firms
Insurers are using IoT devices and AI-based visual analytics to understand risk profiles better. Blockchain-based parametric insurance smart contracts allow instant payouts. Insurtech startups are also innovating rapidly, threatening incumbents.
Commercial Banks
From digitizing channels to modernizing credit risk models with ML to building blockchain-based trade finance platforms, commercial banks are leveraging technology to improve customer experience while reducing fraud. Regulatory requirements are also driving technology spending.
Key Challenges in Adopting New Technologies
While the business case for embracing new innovations is compelling, financial institutions face significant barriers to leveraging cutting-edge technologies. Integrating complex legacy systems with modern cloud-native stacks is riddled with challenges. Talent shortages, organizational silos, bureaucratic approval processes, and cultural resistance exacerbate technology adoption woes.
Specifically, the key challenges include:
— Difficulty integrating with legacy systems: most established firms have decades-old IT systems that are complex, brittle, and secure. Retraining models, rewriting legacy code, and re-architecting data flows are non-trivial.
— Talent shortages: demand for engineers and data scientists with expertise in AI/ML, blockchain, big data stack, and cloud technologies far outstrips supply. Fierce competition from tech firms makes attracting and retaining talent harder.
— Organizational silos: different teams within firms often operate in silos with business, technology, and operations not aligned. This affects oversight, budgeting, and adoption of new solutions.
— Cultural resistance: employees accustomed to old ways of doing business often resist learning new tools and workflows. Leadership support and change management are vital to drive adoption.
While the business case for innovation is strong, addressing these real-world organizational challenges requires a multi-pronged strategy combining technology modernization programs with cultural transformation initiatives sponsored by senior leadership.
The Road Ahead
With emerging technologies like 5G, augmented reality, and quantum computing, the scope and speed of innovation in the financial markets are only going to increase. Traditional company structures may be disrupted if smart contracts and decentralized autonomous organizations based on blockchain and crypto-assets gain traction.
Even when large internet companies like Google and Amazon join the game, nimble fintech entrants will pose a threat to established players like investment banks and exchanges. It will become necessary for financial institutions to be on the cutting edge of technological innovation for them to prosper in the middle of this upheaval.
