The practical benefits of AI for capital markets
AI offers game-changing benefits to capital markets firms who are committed to unlocking its power.
But for newcomers to this field, it’s easy to get bogged down in the details and lose sight of the overall prize. We recently wrote about making AI happen, explaining why AI is so important and how it can drive transformation. Now it’s time to identify the concrete benefits of embracing AI across a range of capital markets practice areas.
AI needs to be the Alpha for the organisation, cutting across all business functions in order to usher in meaningful change and drive value for the business.
AI for data management
Capital markets firms are frequently siloed. In most cases, the migration of siloed legacy systems to modern cloud-based solutions has started, but legacy applications remain and comprehensive integration across divisions, geographies and asset classes is rare.
The key is to avoid building expensive proprietary technology and focus instead on modular platforms, engineered to reduce operating costs and improve speed-to-market of advanced AI-powered solutions. These techniques can be used to improve data quality, enabling firms to do a much better job of profiling their clients and enrichening the user experience.
AI for ESG
ESG has come on leaps and bounds in recent years. In some way, this trend has been reactive, driven by consumer demand and increased regulatory scrutiny. But we have also seen a new generation of progressive capital markets leaders proactively embrace ESG as a way to optimise brand value and future-proof their organisations.
On the product side, there is pressure from regulators to adhere to climate change objectives, increasing demand for green funds and sustainable bonds. But this isn’t simply a front office phenomenon – under the bonnet, there is a huge focus on operational risk.
AI technologies can help firms to build a treasure trove of ESG data and develop a pipeline of insights. But it’s important to note that transformation doesn’t happen overnight – the data management process is fundamentally iterative, evolving along with the broader ESG franchise.
AI for next-generation wealth management
We recently wrote about wealth management, noting that the traditional wealth model is hard to scale and susceptible to a new customer demographic demanding personalised, digital-first services. But we didn’t stop there; we suggested some ways that firms can adapt to the new market reality using exciting new technologies.
It’s not just about transforming the front-end of wealth management with robo-advisors. To enjoy the full benefits of digital transformation, firms must prioritise data management across the length and breadth of the organisation.
By leveraging AI, firms can develop a client servicing model enabled by hyper-personalisation, resulting in richer, more relevant client conversations and increased business.
AI for operations analytics
Operations isn’t an area of capital markets that tends to grab the headlines. But practitioners across the business know that it’s a crucial area; the foundation upon which the entire client experience is built. They also know that post-trade activities can be highly manual and prone to error, creating poor customer experiences, increasing risk and elevating costs.
It’s not just underlying processes that are inefficient. Analytics are equally sub-optimal. If the process by which problems are identified could be automated, it would be easier, quicker and cheaper to fix issues before they become business-critical. AI offers huge benefits here. Data-led approaches – including Natural Language Processing, Network Analytics and Process Mining – can automatically identify sources of inefficiency, fixing exceptions upstream. This optimises the operations process and transforms risk into opportunity.
AI for algorithmic trading
Capital markets firms are investing heavily in data scientists to develop new algorithmic trading strategies. But back-testing these strategies is time-consuming and prone to “false discoveries”. This makes the business hard to scale. Commercialising successful strategies remains technically tricky due to the scale problem and as a result, banks are struggling to compete in the algorithmic trading arms race.
Thankfully, there is a solution to this challenge. It involves taking the Modern Engineering and Intelligent Data Foundation capabilities of AI and adapting them specifically to the task of scaling algorithmic trading, enabling continuous rapid deployment of quantamental scaled AI investment strategies. This kind of domain expertise is rare, and only made possible through years of experience working on the ground in algo trading.
It also highlighted the importance of building human+AI relationships which is the only way to drive the industry forward.
We’ve barely scratched the surface of what’s possible for capital markets firms implementing AI.
In the years to come, market data providers will converge with exchanges to provide platforms for clients to research, trade, monitor and risk manage all in one place. M&A deal analytics are evolving rapidly and firms are developing data-led profiling assets to support winning and running deals, including due diligence and organisational assessment. Demand for enhanced data analytics is rising, and AI is stepping in to provide trade analytics solutions including surveillance, risk profiling and tracking. And alternative data from external firms is being collated and sold as a service, enabling clients to blend market data with alternative sources to obtain a trading advantage, improve their research and do a better job of risk management.
None of these advances would be possible without AI. So, it’s critical that capital markets firms engage with this burgeoning field of technology in order to remain relevant as the market evolves. We passionately believe that every capital markets business should adopt a data-first culture, with rapid and repeatable deployment of AI solutions into production.
If you would like to find out more about applying AI to your business, please get in touch.