AI in Finance

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AI, Friend or Foe to Finance? | Featuring Mike Vaishnav

To know more, watch this video interview with:

Mike Vaishnav
CFO & Strategic Advisor

Moderated by:
Digital Transformation Consultant at Hyperbots

Don’t want to watch a video? Read the interview transcript below.

Emily: Hi everyone. Good morning, good afternoon, good evening, depending on where you are. I’m Emily, a digital transformation consultant at Hyperbot Systems, and I’m very pleased to have Mike Vaishnav on the call with me. Mike is a CFO, consultant, and strategic advisor to various privately-held organizations. Before we get started on our discussion on how AI can be a friend rather than a foe to companies, Mike, could you tell us a little more about yourself?

Mike Vaishnav: Of course, thank you, Emily. I’ve been working in Silicon Valley for close to 30 years in various roles, ranging from controllership to FP&A, treasury, tax, significant M&A transactions, and process improvement system implementations. I’ve worked with companies of different sizes, from $60 million to $22 billion. In my last two roles as a CFO, I also managed HR, legal, and IT functions. So, that’s my overall background. Let’s focus on our topic rather than my background.

Emily: Thank you so much for the introduction, Mike. Today’s discussion will cover three broad categories: technology evolution in finance, the perceived threats of AI, and the benefits of AI. Starting with technology evolution, Mike, as you mentioned, you’ve spearheaded different finance functions in various organizations of varying sizes. Would you like to briefly share your key experiences?

Mike Vaishnav: Of course. I’ve seen technology evolve from mainframe computers in the early ’90s to the latest cloud-based technology. The speed and analysis of data have changed significantly. Automation and process improvements have been tremendous. We’re now entering a stage where AI can further evolve technology, especially in the finance industry.

Emily: You’ve been part of different waves of technology in finance, from manual bookkeeping to advanced ERP systems. What technological evolution have you seen over the years?

Mike Vaishnav: Automation has progressed from manual processes to cloud-based systems. Adding AI and other solutions to existing ERP systems can automate processes and make finance functions more efficient and effective.

Emily: These days, there’s a lot of buzz around AI. How do you see AI affecting the finance function?

Mike Vaishnav: AI can significantly enhance the finance function. AI is essentially human intelligence on a computer, helping finance take the next step. AI can gather and analyze large amounts of data, complementing human efforts. It can provide real-time, accurate data, improving decision-making and operational efficiency. AI can help finance executives focus on detailed analysis to improve profitability and efficiency.

Emily: Thank you, Mike. In the next part, we will discuss the potential threats of AI.

Emily: Welcome back, Mike. Here, we’ll talk about the threats of AI. AI is seen as a threat by some and a friend to others. Why are the perceptions so different?

Mike Vaishnav: People see AI as a threat mainly due to fears of job losses, data security, and privacy issues. There’s also a concern about people becoming too reliant on AI and potential biases in data. Since AI is still evolving, these perceptions persist.

Emily: Is the perception of threat real? What can companies do to change this perception?

Mike Vaishnav: The threat isn’t entirely real. While some routine jobs may be impacted, AI will create opportunities for more analytical roles. Companies need to educate their employees about AI, showing that it can complement human intelligence rather than replace it. People doing routine jobs can be redeployed to learn new skills.

Emily: We just spoke about job security. How real is this threat, or do you see it as an opportunity?

Mike Vaishnav: I see it more as an opportunity. While some entry-level positions may be affected, AI will create chances for employees to learn new skills and take on more analytical roles. The perceived threat can be mitigated through proper education and redeployment of resources.

Emily: Another threat you mentioned is data security. How real is it, and what can be done to mitigate it?

Mike Vaishnav: Data security is a real concern, but it has become more manageable with sophisticated AI systems. Ensuring data privacy and security involves everyone interacting with the data, not just the data administrators. Companies need to maintain high ethics, integrity, and trust in data handling to mitigate this threat.

Emily: That’s quite concerning for companies considering AI-driven processes. Thank you for your inputs, Mike. In the next part, we will cover the benefits of AI.

Emily: Welcome back, Mike. In the previous sections, we discussed the evolution of technology in finance and the threats posed by AI. Now, let’s explore the benefits of AI. Can you share some examples where AI simplifies the life of finance professionals?

Mike Vaishnav: AI can collect data, assist in decision-making, eliminate human error, simplify complex information, and reduce costs. It provides real-time data for analysis, making the finance function more efficient. AI helps finance professionals by automating data collection and analysis, saving time, and improving accuracy.

Emily: What skills should finance professionals acquire to take advantage of AI technology?

Mike Vaishnav: Finance professionals don’t need specific new skills because they are generally system-savvy. The key is to be open-minded and understand how to interpret and use AI-generated data. Trust in AI is built on understanding how data is collected and algorithms are written.

Emily: Can AI be a trusted friend, or should you always keep a watch on it? Can you give an example where AI can be fully trusted and another where its output must be reviewed?

Mike Vaishnav: AI can be a trusted friend for finance professionals if the data collection and algorithms are accurate. For instance, AI can reliably process and analyze large datasets. However, for complex decision-making, it’s essential to review AI outputs to ensure accuracy and relevance. Trust in AI comes with proper data handling and algorithm design, but human oversight remains crucial.

Emily: Thank you so much, Mike, for the insightful discussion. I’m sure this will provide our audience with clarity on embracing AI in their finance processes while avoiding potential threats.

Mike Vaishnav: Absolutely, thank you so much. It was a great discussion.

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