Artificial intelligence (AI) ─ the ability of software to perform tasks that traditionally require human intelligence ─ and generative AI ─ the power to create content autonomously ─ are top of mind for institutional investors today.

By enabling large-scale data synthesis and manipulation at speed, generative AI has the potential to fundamentally reshape the investment industry.

At State Street, we’re uniquely positioned to help institutional investors deploy AI across the investment process and embed efficiencies throughout their firm’s entire operations. As an essential partner to the world’s leading institutions, State Street has the skills, resources and scale to architect the financial infrastructure of the future ─ and we’re already getting started.

Explore some of our latest AI thinking to help you navigate your own transformation.

AI adds a layer of intelligence to analyze, interpret and guide decision-making on a wide cross-section of data, ranging from front-to-back-end services and market data, to pricing, reference data and ESG data.

While AI holds considerable promise for unlocking new insights and improving productivity, data is the foundational element of that opportunity. Ensuring the massive volume of data is fit for purpose requires a solid data management platform capable of capturing, curating, validating, enriching and delivering data sets to AI and machine learning (ML) modeling engines.

Institutional investors of all types understand that data is a vital resource. Data remains not only the cost of entry, but also, critically, the means of differentiation and competitive advantage. Effectively leveraging data to make timelier, better-informed investment decisions is the essence of being a data-driven organization.

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While AI is powerful, its potential is multiplied when combined with human insight and other technologies:

• The cloud has made it possible to harness massive computational resources on-demand.
• A new generation of cloud-native data management platforms eliminate time-consuming data movement and make it possible to assemble the massive and complex data sets required by AI algorithms in a matter of minutes.
• Generative AI is poised to radically transform how our clients interact with all of our services, enabling conversational access to knowledge, documentation, trade status, portfolio data and news.

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AI is no longer unique to a sector, industry or product — it is a global change agent. Its ability to transform financial services and the investment process has significant implications for investors.

A beneficial way to gain exposure to AI is to take a broad view of its impact by owning the “full stack” of building blocks that underpin the broader technological opportunities as opposed to individual applications. (An AI full stack includes component makers, cloud services, research and labs, and applications).

However, integrating AI into the financial system requires thoughtfulness, as finance does not neatly meet the criteria of categories that are compatible with AI.

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AI applications can transform a firm’s operations and can be grouped into six major categories:

• Generative AI chatbots provide customer-facing service teams and financial advisors with curated knowledge for more productive customer interactions and help middle-office operations specialists automate routine trade reconciliations.
• Data governance applications include detecting and escalating anomalies in mission-critical financial data, escalating suspicious records to human analysts to validate and remediate potential errors.
• The ability to parse documents, spreadsheets and other unstructured sources helps inform portfolio construction, flag suspicious AML/KYC transactions and perform valuation and cash flow analysis of private equity and other alternative asset classes.
• Software developers are harnessing applications that generate code, freeing them to focus on algorithm development.
• Hedge funds are using image analysis to generate buy and sell signals based on chart pattern recognition.
• AI algorithms are creating visualizations of investment performance, risk exposures and other portfolio analytics.

At the same time, operational resiliency and security will be key for all AI-driven operational transformations.

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