Copilot for Microsoft 365 is typically available as an add-on license. If you're already a Microsoft 365 user, this means it could be an extremely cost-effective choice.
More than almost any other, the financial sector runs on speed, precision, and trust. With Microsoft Copilot now embedded in tools like Outlook, Excel, and Teams, firms have a chance to transform everyday workflows with AI.
The big question is - how can AI help the financial industry work faster while staying compliant and keeping the human touch? Rolling Copilot out can be confusing, so it’s crucial to identify the right use cases from the outset.
To help you get going, we’ve put together this introduction to using Copilot AI in the finance industry - and its potential for those firms who are ready and willing to embrace the future.
What is Microsoft Copilot, and how can it help in finance?
Microsoft Copilot is a widely used AI-powered assistant. If you’re already in the Microsoft 365 ecosystem, you’ve probably already seen it inside all your other Microsoft 365 apps.
It can be deployed to your staff to help improve efficiency in their everyday work or used to develop interactive or autonomous Agents that can act like virtual team members, executing tasks as part of a business process.
As a tool, it uses large language models (LLMs) combined with your internal data (emails, documents, calendars, and more). This means it can help you write, crunch numbers, summarise long texts, and automate routine work.
If you set it up right, Copilot is basically a digital colleague. Except it never sleeps and definitely won’t miss a deadline.
Setting up Copilot in finance
At this point, AI is no longer new news. But now that the initial hype has died down, companies within the finance industry are starting to understand the practical use cases for AI. Combined with ongoing changes in the industry, it creates plenty of opportunities for action.
Every subsector, from banking and insurance to asset management and fintech, can benefit from using Copilot. Agent development automates entire processes, while Copilot, as an AI assistant, helps reduce manual work, speed up reporting, and free your team to focus on higher-value analysis.
Microsoft Copilot vs other AI tools
But why Copilot specifically? There’s no shortage of generative AI tools out there, couldn’t any one of them do the job? While they may function in similar ways, Copilot has a few key advantages over other models.
Microsoft understands the entire enterprise ecosystem. It's done more than just deploying a powerful AI tool; it's also working hard to govern and secure Copilot through a unified framework of tools and permissions across your estate.
Copilot is embedded directly into Microsoft 365. Both Agents and Chat can be accessed directly from Office tools and Teams, or via web chat, depending on licenses.
Your data stays within your Microsoft ecosystem. It’s not used to train public models, and access is governed by the permissions you already have in place.
Copilot understands your business context (internal documents, policies, conversations). This means its answers are highly relevant, rather than generic.
Copilot Studio lets you build bespoke AI-powered Agents, so you can tailor Copilot to your own internal processes and systems.
Yes, other tools like ChatGPT or Google Gemini might be more flexible in open-ended questions. But for meaningful everyday enterprise tasks, Copilot’s Microsoft integration makes it a fantastic choice for financial firms.
How is AI being used in the finance industry?
At Nasstar, we think it’s best to let AI and automation solutions handle the boring stuff. The tasks that take up time, require repeated effort, and are prone to mistakes. Yes, those tasks will still need human input - but with the right setup, AI can reduce monotonous jobs from hours to seconds.
In finance, Copilot can be used to handle tasks such as:
Client communication - You’re not about to hand every single client interaction over to a robot. But what Copilot can do is help summarise lengthy email chains, draft responses, and even tweak client updates to your tone. You’ll spend less time typing and more time actually supporting clients.
Report generation - The finance world runs on reports. From monthly performance summaries to risk and compliance reviews, creating these reports can be an exhausting process. Instead, Copilot in Word or Excel can quickly pull together drafts, highlight trends and even visualise data from your chosen connected sources.
Modelling - There’s always a cash flow projection that needs adjusting. As it’s plugged straight into your data, Copilot in Excel can run the complex calculations on your behalf and even suggest formula improvements, all based on the information you already have.
Meeting prep and follow-up - This may sound basic, but it can be a massive time-saver. Copilot in Teams can generate agendas beforehand, then summarise meetings and highlight actions after. This cuts out the prep and note-taking, meaning you walk in informed and walk out with clear next steps within seconds.
TL; DR? Copilot reduces mundane admin and lets you get to the more interesting stuff.
Agent development
Agent development in Copilot is a key use case for finance firms. The real impact can be seen when Agents are developed and deployed into solution areas like fraud detection and prevention, and customer service automation.
Fraud detection and prevention
AI agents analyse transaction patterns in real-time, flagging anomalies like unusual spending or account access. They adapt to evolving fraud tactics, reducing false positives and enhancing security. For example, banks use AI to monitor millions of transactions daily, catching a huge number of fraudulent activities with minimal human intervention.
Customer service automation
AI Agents power chatbots and virtual assistants, handling inquiries like balance checks or loan applications 24/7. They resolve a vast majority of routine queries without human involvement, as seen in systems like Bank of America’s Erica, improving efficiency and customer satisfaction.
H2: What are the benefits of using Microsoft Copilot in finance?
Now we’ve seen what tasks Copilot is capable of handling, let’s see the many potential benefits for you and your team.
Time savings
That’s right, Microsoft Copilot can save you tonnes of time. We might have already mentioned it. But it’s worth repeating as traditional finance is full of manual processes that slow teams down. So why not let Copilot automate repetitive tasks like data entry, report writing and inbox management, and claw back hours every week.
Better accuracy
Not only is AI quicker than us humans, it’s also more accurate when you’re doing things like calculating rates or checking for inconsistencies in a dataset. In this way, Copilot reduces human error and flags potential issues before they become real problems.
Improved client service
Your clients want correct information and excellent service faster than ever. So, with more time and better insights, advisors and account managers can focus on proactive support instead of pesky admin tasks.
Cost efficiency
One huge, combined benefit of all these advantages? Well, as the old saying goes, time equals money. By reducing your company’s reliance on manual work and third-party tools, you can effectively reduce costs without compromising on quality, service, or compliance.
These benefits all set you up for success now. But it’s important to remember that AI is not going anywhere - it’s only going to improve. By future-proofing your infrastructure and introducing tools like Copilot, you’ll also be better positioned to attract talent, retain clients and respond to market changes down the line.
Are there any limitations of using Microsoft Copilot for finance?
Alongside the benefits, it’s also important to consider the potential limitations of implementing AI like Copilot. The first is data security. Copilot works with the data you already have access to. But if someone within your organisation has access to something they shouldn’t, Copilot probably does too. That’s why it’s important to tidy up access policies first.
Similarly, financial firms need to prove their models’ safety. There may be regulatory requirements to prove how decisions are made and that all models meet compliance needs.
Then there’s the question of hallucinations. Like all LLMs, Copilot can occasionally get things wrong. That’s why human oversight and high-quality data are essential - especially when you’re dealing with finances and sensitive information.
However, what do all these limitations have in common? They can all be minimised through thorough preparation, quality foundations, human know-how, and ongoing improvement. That’s where working with an expert for your Copilot implementation can make all the difference.
A good bit of our time on engagements is spent ensuring the output from Agents and Chat is accurate. Sometimes it’s more effective to limit the scope of possible answers to ensure quality than to try and think of all the combinations of things an agent might reason over.
Microsoft Copilot implementation tips
Ready to get started? There are a few ways to give your Copilot rollout the best chance of success:
Take a look at your existing tech stack. Are you already using Microsoft 365? If so, what integrations could save you time? If not, how will you deploy it?
Go through your data and permissions, making sure anything sensitive is protected.
Then, look at the files and documents you’ll give Copilot access to. Could you clean or improve the data? This will help Copilot function even better.
Next, choose a simple use case to trial first. Start small. It might be one straightforward task to prove that AI can work for you. Many companies start with things like meeting summaries, for example. Once you have the confidence that it works, you can move on to bigger and better use cases.
You’ll also need to train people. Show them how the tech will improve their jobs - not replace them - and give them the power to use the tools effectively.
Finally, keep measuring and improving. AI implementation is an ongoing process, after all.
Our customers sometimes struggle to work out where to start. To support them with implementation, we have designed a series of workshops that engage with key customer stakeholders, to uncover business value scenarios we can prioritise.
How Nasstar can help
AI in finance has so much potential. The most effective use cases are often the most mundane - repetitive, time-consuming, error-prone tasks are all fantastic candidates. The key to making the most of AI? Getting the right foundations in place.
At Nasstar, we help companies across many industries assess their current tech stacks, find AI use cases, and implement effective and successful deployments.
Want to see what Copilot could do for your business? Speak to a specialist to learn more.