Amid constant macroeconomic uncertainties, many financial services companies are hoping to do more with less this year. Many are reallocating resources, making staffing cuts, and finding new ways to boost productivity.
In such a climate, generative AI, specifically LLMs (large language models), has been a hot topic, with many questioning if its potential to generate content and analyse information quickly could provide much-needed support.
While AI has the potential to drive greater efficiency and innovation, it’s not a silver bullet for financial services. To maximise returns and drive business-wide progress, businesses must view AI as just one piece of the puzzle and explore other innovative technologies to integrate alongside it, like automation.
Early success with AI
There are high hopes for AI to alleviate the mounting workload strains on financial professionals. UpSlide’s research shows that investment bankers currently spend anywhere between 10 to 40 hours per week in Microsoft applications on manual tasks such as presentation formatting and updating data points.
Over the last year, we’ve seen many financial services companies, like Goldman Sachs, KPMG and PwC, exploring whether generative AI could reduce the time their workforce spends on administrative tasks in Microsoft 365. And so far results have been positive.
Since Microsoft launched their AI-powered assistant, Copilot, back in February 2023, 70 per cent of Copilot users reported they have been more productive, and 68 per cent said it has improved the quality of their work.
The most promising use cases include drastically reducing repetitive workflows like data entry, form processing, and customer service inquiries. It can also deliver enhanced data analytics to access strategic insights faster, with over half of financial institutions already achieving cost efficiencies in this area.
However, AI is not a miracle solution - it won’t be able to solve every issue, especially for highly regulated industries like finance.
Where AI falls short
AI tools can certainly achieve a lot, but in isolation, they cannot fulfil strategic objectives for financial institutions.
LLMs like Microsoft Copilot and Google’s Gemini are generative models; they’re helpful when producing standard text and image outputs. However, more specialised situations, like building a pitchbook, require a complex, time-consuming integration between the model and your data and workflows.
Similarly, ensuring brand compliance can be difficult; at present, most LLMs aren’t mature enough to be able to guarantee that every output produced will comply with your company’s brand guidelines.
We might be able to overcome these obstacles in the future, as it is already possible to train an LLM to be more industry or company-specific in terms of the content they generate. But until then, AI’s effectiveness in the financial sector is undoubtedly restricted.
To drive enterprise-wide impact, financial leaders should adopt a cohesive strategy that integrates AI alongside automation.
Automation will take output to the next level
Integrating finance-specific automation tools, like UpSlide, helps address AI limitations by providing crucial missing capabilities of these models, such as automatic data updates, finance-specific content generation and brand compliance.
Rather than manually doing these mundane tasks, automation can do the legwork of populating slide templates with the most current figures or tombstones, continuously pulling real-time data.
Armed with automation, finance professionals can also efficiently manage all corporate content within a centralised hub. They can add, update and remove templates and other materials before distributing the changes to global teams, ensuring they always use the latest content in the right format. This attention to brand identity is where automation shines, and AI falls short.
Teams can subsequently produce accurate reports in shorter amounts of time, minimising the risk of human error and freeing up precious time to focus on more strategic areas of business, like nurturing client relationships.
When implemented effectively, automation will ensure financial professionals deliver personalised, trustworthy and accurate documents every time, strengthening their brand reputation and client relationships.
To truly future-proof for the years ahead and revolutionise their teams’ workflows in Microsoft 365, financial institutions must implement AI in tandem with automation.
Providing your employees with both these tools will ultimately make your employees more efficient and fulfilled, and your business more successful.
In the finance industry, where quality, accuracy, and client-centricity are paramount, these innovations will be the driving force behind a more agile, competitive, and client-focused landscape in 2024.