July 24, 2024
Investment

2024, the year generative AI rockets to wide use for investment accounting operations teams


In this new year, where are you on the generative AI innovation curve?

In 2023, discussions about how technology is revolutionizing investment functions have intensified. Everyone from the CIO to the investment accounting team can enjoy innovations like enhanced analytics, cloud transformation, sophisticated tech for portfolio management and reporting, risk and compliance, and more have all had significant impacts on the investment landscape.

Now, gen AI and Large Language Model tools have taken center stage and are having paradigm-shifting benefits for adopters in what is emerging as the battleground in financial services today — end user experience and the ability to deliver unparalleled growth.   

There are universal end user must-haves for investors and their accounting teams, items like transparency, accuracy, personalization and speed. In a few short months, gen AI has made it possible for these teams to gain significant efficiency across these areas.

Now that more financial institutions are test-driving gen AI across the investment lifecycle, 2024 will be the year when the investment industry aims to take this up another level — pushing for faster knowledge, driving new functionality, and using the technology for more ambitious use cases.

Here are several trends that are set to shape the investment accounting space and the end-to-end investment process in 2024.

Gen AI has potential for expanding the existing investment accounting knowledge base

For investment managers using gen AI today, few if any investment teams are tackling more menial tasks such as content generation, summarization and synthesis with ease. The future of gen AI lies in enabling back-office users to ask questions about their portfolios, such as, are they exposed to too much risk due to changing market conditions or can they get a breakdown of their peers’ portfolio returns? This is only the tip of the iceberg, though, for the investment industry.

In our industry, LLMs can correlate enormous amounts of data and investment performance. Those who use it well can gain an information advantage over the market and create a vast knowledge base from which to make more advanced decisions. We’re going to start to see more autonomous AI coming down the pike, getting productized to automate time-consuming tasks that will free accountants up for high-value duties. In fact, investment professionals should be focused on making confident decisions about their portfolio allocations and have the intelligence to shift to higher-returning asset classes, without the burden of data processing, analysis and reconciliation.  

Deloitte posits that for our industry, gen AI tools can perform “customized stock picking, writing performance reports, writing proxy letter[s], enhancing advisor platforms and enhancing digital assistants to have more natural language capabilities.” The use cases are virtually endless and investment accountants are yearning for this enhanced functionality to be included in their tool kits in the year ahead.

LLMs go from workflow “novelty” to a refined workflow efficiency engine

As users swiftly get accustomed to using gen AI tools, they’re thrilled about being able to accomplish broad goals, like adding quick-responding gen AI chatbots, creating custom images in a click, and getting a variety of other content outputs generated. But having broken the initial barrier of the unknown, users across financial services functions are now looking for more customized and sophisticated outcomes from their LLM tools.

We have been dazzled this year with increased productivity and operational efficiencies, and numerous LLM startups are emerging. Accounting, insurance and other financial services organizations are integrating or moving to launch their own customized solutions, like BloombergGPT, ChatPwC and McKinsey’s Lilli.

This year will see LLM tools move beyond performing as autocomplete on steroids. The platforms will gradually improve, moving the needle on gen AI’s precision and ferret out hallucinations. For example, LLM administrators can supplement the tool with logic, and rely on retrieval-augmented generation, which improves the quality of the LLMs by using data from external knowledge bases, resulting in improved data outputs.

Gen AI is being deployed across economies, governments, businesses and our personal lives. We will begin to see it in every application in which we work. Like the internet and Web 2.0’s early days, we will gradually interact with the technology, and thus get better with it, changing the way we communicate, learn and do business.

AI efficacy will ripple upward

Alongside gen AI performance benefits and enhancements, the investment accounting industry will have an equally keen eye on integrating it into other areas of its workflow, namely in regard to compliance. A massive compliance workforce in financial services stands to benefit from this technology, accelerating time for the validation and verification process. We will see such use cases compounding on a month-to-month basis. Gen AI’s productivity effects will cascade from knowledge base, customer experience and onboarding investment policy statements, to compliance and other higher-value functions.

This is all good news, since investment accounting in insurance, asset and investment management will face thorny challenges in 2024, like T+1 faster settlement times (May 2024), the SEC’s ESG disclosure rule (pending for years), and omnibus regulations on these AI tools themselves that could impact nearly all industries as their use expands.

Obsolescence looms for the skeptics

Economic uncertainty, increased regulatory scrutiny and geopolitical crises spell another competitive year in financial services. Firms are seeking every opportunity to add value and pry open margins. Firms that leverage gen AI solutions will start to outperform competitors in a significant way; they will become faster, better, cheaper. Those skeptics in the laggard or late stage of the innovation curve will not only begin to feel like they are missing out, but are likely to find they are teetering on the edge of obsolescence.



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