How AI is transforming capital markets across the world
Capital markets have always been a tad complicated, but over the past few years, regulations, geopolitical actions, and economic uncertainties have created new challenges.
In fact, over the past few years, revenues have been dropping in the industry. Five years ago, fixed-income trading, for example, generated nearly US$103 billion in income for the top 12 investment banks. By 2016, that figure fell to less than US$76 billion — down US$27 billion.
To make matters worse, 20 of the world’s top banks were fined close to GBP264 billion (US$341 billion) between 2012 and 2016, and the non-traditional risks that investment banks face is growing exponentially every year.
Other factors such as the entry of non-traditional players in the capital markets and the diminishing role of US and EU based financial intermediaries in emerging markets make the future seem quite bleak.
However, artificial intelligence (AI) might be the light at the end of the tunnel that the capital market needs.
What AI brings to capital markets
According to a recent report by the World Economic Forum (WEF), AI has the potential to democratize access to capital across the global economy by unlocking greater efficiency, safety, and performance in capital markets.
The rise of AI is expected to help create specialized digital tools that will rapidly transform the deal-making value chain by automating deal matching and investor matching processes and improving the accuracy of financial models.
AI can also help create new capital and risk management functions that will serve as key differentiators in the industry.
In essence, in the capital markets industry, AI has the power to:
- Simplify the deal-making process using predictive analytics and automation
- Improve investment performance through smarter, contextual, AI-driven insights
- Deploy advanced capital and risk management solutions by leveraging AI-powered solution
How AI can improve capital market operations
There’s a lot that AI can do to improve capital market operations, especially when it comes to automating repetitive tasks such as number crunching and reporting.
The WEF’s study found that AI can perform administrative tasks faster and better than humans, enabling the latter to focus on higher-value activities.
AI simplifies processes
In today’s world, capital markets intermediaries need to perform a large number of manual and low-value tasks throughout pre-deal analysis, which are often completed by highly trained investment professionals.
From due diligence, prospectus preparation, and roadshows, to pricing and other processes, investment executives handle labour-intensive and repetitive tasks that don’t necessarily make the best use of their skills.
Many rote tasks in these processes, such as analyzing documentation and legal requirements, can be automated, freeing up banker capacity to focus on higher-value interactions.
Highly trained professionals are also roped in to provide investors with information about how a particular deal is panning out and the changing metrics around each transaction. However, it’s a laborious and challenging task, one that often creates room for ‘human-error’.
However, automating these tasks using AI can not only save hundreds of thousands of man hours and millions in costs but also ensure that investors are more satisfied, being able to query and pool together information about the transactions and deals that matter to them the most — by themselves, in real time.
AI creates advanced research insights
Market and deal analytics for growing companies is a slow and laborious task. There is scanty data and venture capital firms need to make the most of it by analyzing target companies and comparing them to more developed organizations.
However, in today’s disruptive world of commerce, investments happen in frontier industries where rules and trends are often unpredictable.
Even for later-stage companies with predictable financials, scaling analytics is a challenging feat when key data is missing.
Historically, the capital-raising process has been highly intermediated, driven by referrals and face-to-face networking, making it labor-intensive and inefficient. As a result, firms are reliant on, and limited to, the knowledge of brokers, resulting in sub-optimal pairing of investors and investments.
This reduces the overall efficiency of capital markets and performance, both for investors and growing companies.
However, with AI in the picture, capital market intermediaries can mine datasets, form useful connections, and analyze data quickly and efficiently, all in order to produce insights that set the firm apart, help it gain an edge in the market, and differentiate itself.
AI offers better risk management
Inefficient calculation of initial margins ties up capital and increases costs, particularly when regulatory frameworks are increasingly focused on risk mitigation and de-leveraging Initial margin-optimization processes are a function of several variables, such as counterparties and underlying assets.
Standard optimization algorithms are limited in their ability to take a complex mixture of parameters into account without significant effort.
AI can help create intuitive algorithms using machine learning that quickly and take care of changes in data and how it is presented quickly and efficiently.
Further, capital market intermediaries require excess capital to be kept in order to meet liquidity requirements due to risk-model inaccuracies from limited use of data.
AI-powered risk measurement that is based on strong data used and accurate risk models can provide quite some relief – and make the business significantly more cost effective, driving up profits exponentially.