Executive leaders at hedge funds, private equity, and other financial firms are exploring how professional-grade generative AI (GenAI) tools can improve their internal workflows and business results. Industry experts are raising important concerns about risks concerning accuracy, data privacy, and governance as a result. These concerns extend even to emerging business-grade GenAI solutions—such as Copilot, Microsoft’s GenAI solution for its 365 software and beyond.
Fortunately, Copilot uses Microsoft Azure OpenAI services for processing—no external AI or large-language model (LLM) services come into play. As we will find—and unlike other, generalized GenAI solutions—Copilot delivers on many of the efficiency, accuracy, and data privacy needs financial firms already have in place today.
In this article, we explore the potential of Microsoft Copilot for investment firms. We consider its capabilities and how those functions can translate into better processes and outcomes for both employees and stakeholders, as well as specific use cases that can drive these results.
What is Microsoft Copilot?
Copilot is Microsoft’s GenAI solution which integrates with its core Microsoft 365 products—including Word, Excel, PowerPoint, Outlook, Graph, and Teams, among others. In the financial services industry, Microsoft Copilot can connect its LLMs to firms’ organizational data, fetching content and context (e.g., from Microsoft Graph).
The tool is designed to drive productivity, creativity, and collaboration across individuals and teams using these functions. Specifically, Copilot can generate responses to user queries based on a combination of available documents, emails, chats, meetings, and other formal and informal data repositories.
It’s in this role that Copilot can leverage data, securely and in a governed way. Copilot can become a practical extension of a firm’s data resources, enabling employees and stakeholders to automate processes, drive efficiencies, reduce errors, and drive better business results.
In fact, Microsoft Copilot is already driving results in finance. In Microsoft’s September 2023 article, the company describes its partnership with the London Stock Exchange Group (LSEG): “Using Microsoft 365 Copilot in Microsoft productivity apps to access LSEG financial markets data… can make data and analytics much easier to discover and use.” They add, “Customers will be able to… enhance their workflow and bring greater efficiency and productivity to their organizations.”
How Does Microsoft Copilot Impact Data Privacy?
There are natural concerns about accuracy and data privacy when it comes to GenAI software. But unlike general tools like ChatGPT, Copilot is not an unmitigated technology. It is a tool that functions within Microsoft’s existing applications and parameters; it accesses data and provides output based on a financial firm’s allotted permissions as well.
For example, Copilot’s processes and output stay within a given user’s tenant as the user leverages its functionality; it doesn’t access other user’s tenants as that user proceeds. That means Copilot will only surface information that the user operating Copilot has permission to view. In terms of encrypted data, Copilot aligns with Microsoft’s Purview Information Protection—it will not return encrypted data to a given user in any way unless that user already has the permission and means they need to access it.
Building upon Microsoft’s secure data model for privacy and controls, Copilot provides several additional layers of protection as well—including logical isolation, encryption strategies, and physical security. Collectively, all prompts, retrieved data, and Copilot responses stay within the Microsoft 365 boundary.
9 Ways Microsoft Copilot Can Drive Value for Investment Firms
Since Copilot is purpose-built for sensitive data environments, it allows for a wide variety of use cases within the business contexts of financial firms. Here we share several potential use cases for Microsoft Copilot among these companies. Consider how these approaches could work for your organization, taking all potential benefits and risks into account.
- Improve code quality: As users generate code, Copilot can propose optimized algorithms to improve runtime and performance; it can help users ensure code adheres to best practices and standards as well. By utilizing AI-powered assistance, employees can complete tasks faster and more accurately, freeing up time for higher-value work.
- Streamlining financial processes: Users can leverage Copilot as they create code for budgeting, variance calculations, and forecasting, and access recommendations for tools that can automate data imports from any variety of sources.
- Accelerate data analysis: Copilot can help users create pivot tables and visualizations, or suggest efficient ways for them to filter and process data; it can help users analyze financial ratios, such as ROI and debt-to-equity as well.
- Provide predictive insights. “It’s crucial now more than ever for organizations to accurately predict demand and quickly adapt to demand shifts in a timely, sustainable, and cost-effective manner,” as Microsoft describes. “[Copilot’s] AI-powered forecast model automatically selects the best algorithms and parameters for every product, and planners can fine-tune the parameters based on their bespoke business needs.”
- Automate financial reporting: Copilot can suggest code for creating financial statements, provide modeling for varied forecasting scenarios, and enhance models for more efficient implementation.
- Enhance financial reporting: Copilot can provide users with recommendations for custom report templates and formats based on the data they will present; it can help users enhance the visual appeal of their reports by suggesting interactive features as well. Critically, users can use Copilot to automate key aspects of report creation to reduce the risk of human error.
- Personalized capabilities. Copilot uses contextual cues from each user’s past interactions with the tool to personalize experiences more effectively. This could be especially valuable for finance teams that need to access specific client information and preferences quickly and accurately.
- Improve Collaboration. Microsoft’s products have already evolved over recent years to become more collaborative; Copilot is designed to perform superbly in these contexts. By allowing for real-time collaboration, employees can utilize the efficiencies of Copilot more seamlessly and quickly generate practical information for the entire team—even for customers.
- Maintaining data privacy. Microsoft has built-in features to help protect sensitive data and ensure regulatory compliance. Investment firms can leverage these capabilities to maintain the trust of their clients while still utilizing the benefits of Copilot.
The Hatch is Open—It’s Time to Step In
It’s certain: companies like Microsoft will only improve their GenAI solutions over time. Financial leaders should be prepared for growing client expectations that they begin using GenAI effectively as well. As we have demonstrated, Copilot has clear benefits for financial firms considering GenAI solutions.
Fortunately, financial leaders can take initial steps with Copilot before they jump right in. They must be willing to test Copilot on new use cases, measure the accuracy and compliance of their output, and establish whether they improve outcomes for users and stakeholders. With a timely, careful approach, those early adopters are sure to see returns on their GenAI investment before their direct competitors.
Option One Technologies is Your Partner for GenAI Initiatives
Option One Technologies is a leading IT services provider and consultant for financial firms. Our experts continually review and test new tools to ensure our clients have the best options available. We can also help companies develop their GenAI adoption strategies, whether they are looking to leverage Copilot or other, similar solutions.
Contact us today to learn more about how we can help you navigate the ever-evolving landscape of GenAI in financial services.
