Top five ways generative AI can drive value in capital markets
Global VP, AI & Business Solutions, Google Cloud
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From broker-dealers and hedge funds to wealth managers and trust companies, capital markets ecosystem participants are increasingly looking to scale and grow by transforming their extensive knowledge into value-added experiences. Traditional banks acquired brokerage firms years ago to meet the need to connect with investors, and now, they find themselves competing with robo-advisors and digital-first trading platforms. At the foundation of every investor touchpoint is accessible and useful investment insights.
Generative AI is a disruption — and potential catalyst — within this environment, which is why financial services institutions are looking to incorporate generative AI into their toolkits. How will generative AI add value as capital markets firms look to differentiate, scale, and accelerate the speed of business? We see five main areas taking hold.
1. Enhancing the customer onboarding experience
Today’s institutional investors, corporate customers, and high-net worth individuals expect a fast and smooth onboarding experience. It’s not just about filling out and signing documents—although that is a necessary yet still painful process for both financial institutions and their customers. It’s also about the really hard part: understanding all the assets that an investor has, parsing it all together in an efficient manner, and managing it over time to surface the best opportunities for the client.
Alternative investments and private equity firms are making significant inroads into the investment landscape and client portfolios. Extracting information, understanding all the investments and accounts, and viewing them in a unified way is becoming more challenging as the universe of more complex asset classes expands.
Every investment and asset class starts with a document. Generative AI is highly proficient at understanding assets across a deeper level, whether it’s a share of stock that begins with an S1 or a bond that starts with an agreement. Generative AI can help financial advisors and portfolio managers understand the unique situations, risk profiles, and goals of their new clients in seconds versus the six to nine months it would typically take in the past.
2. Unleashing next-level investment research
Many capital markets organizations have massive investment knowledge bases and want to leverage generative AI for fast, effective Q&A with their data.
People who manage money and build funds know all too well how the investment world is becoming increasingly connected and multi-dimensional. Professionals must be able to understand risk and supply chains at the global level. That means sifting through information from an array of company filings, transcripts, and reports, as well as data on interest rate changes and different types of risk in all different formats. Based on our conversations, most providers offering evaluated pricing services already have AI components, not generative AI, that help piece together disparate data to estimate the market price of a given bond, as an example.
So how can generative AI help transform the investment research experience by making complex data more accessible and useful?
Bringing together foundation models and the power of Vertex AI Search and Conversational AI, generative AI can provide a natural language research assistant that can be relied on to synthesize and search millions of earnings call transcripts, 10Ks and 10Qs, consensus estimates, macroeconomic reports, regulatory filings, and other sources to quickly and intelligently understand semantic queries, offer summarized responses, and provide answers to follow-up questions.
Generative AI can simplify how valuable information is extracted and summarized from complex documents. Check out our demo illustrating how it can help investment analysts accelerate research and discovery.
3. Delivering seamless asset servicing
When it comes to asset servicing, corporate actions in the wealth management and trust space immediately come to mind. Corporate actions are typically manual and paper-intensive, with millions issued each year in the form of an 8-K, a press release, or some other method. Globally, an estimated 46% of event data is published and received manually, driving unnecessary risk and expense to organizations that process corporate action events for their clients and downstream organizations.
Generative AI can help firms process information faster and make decisions around asset servicing, from corporate actions and clearing and settlement, to margin and tax positions and collateral agreements, and apply the right tax protocol and distributions when necessary. And in a T+1 settlement environment, speed and accuracy will matter more than ever.
4. Revolutionizing client engagement
One of financial institutions’ biggest concerns is ensuring a productive client communications and customer service operation. Whether via a live customer service agent, a virtual assistant, or an online investor, people want to be able to ask questions about portfolios, get answers fast, and solve problems quickly with the correct information.
Conversational responses and summarizations using generative AI are changing the customer communications paradigm in financial services. As a result, leaders can be more creative in looking for new ways to engage their clients with their products and services. Greenwich research shows that 50% of U.S.-based financial advisors are investing in customer relationship management technology upgrades in 2023.
Generative AI provides enhanced virtual assistants to help customers get the answers they need with less human intervention by summarizing conversations and automating tasks. Clients can also get conversational and hyper-personalized financial recommendations tailored to their needs. A recent Coalition Greenwich study shows that high-powered analytics are already the key to creating personalized investment and service strategies at scale across a portfolio of clients. Going forward, generative AI is poised to have an even bigger impact, making wealth managers vastly more effective at serving their clients by helping them provide tailored recommendations for financial products and services based on customer profiles.
Stanford Digital Economy Lab scholars studied the impact of generative AI deployed at scale in the customer service sector at a call center. They found that access to AI assistance increased agent productivity by 14%, with the biggest impact on less experienced workers. In addition, agents with two months of tenure who used the tool were able to perform as well as agents with six months of tenure who didn’t have access to the AI.
5. Transforming regulatory compliance
Compliance can be more ambient with generative AI. What does that mean, exactly? In a literal sense, it means that compliance exists or is present on all sides, all-encompassing like temperature or light.
But in the capital markets world, collecting all this information is still very manual. Generative AI can create a more ambient compliance environment, providing a better and faster way to monitor advisors’ and traders’ client communications to ensure they’re not doing or saying things they shouldn’t be. It can also generate sales and marketing content that’s compliant. As well as create and change assets and technology controls to evaluate missing encryption controls, help automate and document code updates when regulations change, and monitor and manage controls easier and at scale.
A significant amount of the marketing, onboarding, customer service, and regulatory reporting involves repetitive content creation. In financial services, a vast amount of work is done to document and ensure compliance. By processing vast content, creating insights and answers via text, images, and user-friendly formats, generative AI can assist with repetitive tasks like localizing marketing content in different languages and checking customer contracts for compliance.
A recent MIT study revealed that individuals using generative AI tools were 37% faster at completing tasks, and as the workers repeated their tasks for improvement, their quality went up significantly faster. In addition, 68% of generative AI users submitted results from only one query, indicating that the tools dramatically reduced effort.
The future of generative AI in financial services
Fast, dynamic sensemaking is increasingly critical to financial services institutions. In capital markets where an expanding universe of investable assets is happening across alternatives, derivatives, and securitization, the ability to cover more asset classes at a deeper level is critical. In the wealth management space, there is a huge push to make finance and investing more digestible and to be able to serve more clients at scale.
Firms will need better and faster ways to monitor portfolios and customer needs, make predictions, and invest assets at a hyper-personalized level. That means investment professionals will need to be able to synthesize more information and provide clients with more service and comparisons across a wide range of complex asset classes. And complying with regulations around the world while detecting and preventing fraud needs to be faster and easier.
With generative AI, financial institutions can future-proof their businesses by accelerating research and discovery, generating new insights, and rapidly scaling the speed and quality of decision-making.
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