Over the past 6 months, along with my team at Qolaig (www.qolaig.com), we helped companies from the financial services industry — Investment Banking, Private Equity, Asset Management and Venture Capital firms — implement AI to automate repetitive workflows.
In twenty years, the job of financial analysts had not evolved, and these companies remained skeptical about using new products and technologies to augment their productivity.
At the end of 2022, when OpenAI’s ChatGPT made its major breakthrough, all companies, even the ones that were technology-skeptic, gained interest around this new technology and the hope it could transform one’s job.
The largest corporations (alike McKinsey — see the article: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier) have been, for the majority, promoting the benefits Generative AI could add to the companies’ productivity, in optimizing the employees’ time and the potential growth it could add to them.
But one thing is still remaining an enigma for these corporate like enterprises: How to implement this new GenAI tech?
It is where actors, like Qolaig amongst others, are making a role.
The biggest challenge that financial services companies are facing with GenAI is the relevance of the use cases such companies could bring up.
In the past months, with Qolaig, after talking and iterating with many Investment Banks, Asset Management, Private Equity and Venture Capital firms, we have identified that the most useful cases of GenAI was in automating the sourcing of opportunities and the production of reports.
For example:
In Investment Banking, automating the production of company profiles;
For PE funds, automating the reporting of dealflows and the sourcing of investment opportunities;
For Venture Capital firms, who want to spend the most time possible with their portfolio companies, automating the sourcing of investment opportunities;
Eventually, for Asset Managers, updating manually the investor’s profiles after each “arbitrage”.
In conclusion, the transformative impact of Generative AI and automation on the financial services sector is evident.
Over the past six months, companies, once skeptical, have recognized the potential of these technologies to revolutionize traditional workflows.
While the benefits are widely acknowledged, the challenge lies in effectively implementing this technology.
Companies like Qolaig play a crucial role in identifying and addressing specific use cases, such as automating opportunity sourcing and report production, tailored to the unique needs of Investment Banking, Private Equity, Asset Management, and Venture Capital firms.