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Artificial Intelligence (AI) is not just a technological advancement; it’s a paradigm shift that’s reshaping our world. Recent research and studies have underscored the transformative potential of AI, particularly in the realm of financial services. According to a report by the World Economic Forum, AI is set to create a financial revolution by bringing about unprecedented changes in the way financial institutions operate and serve their customers.1 This revolution is not just about improving efficiency or profitability; it’s about democratizing financial services and fostering greater financial inclusion.

Marking a significant step toward adopting AI to transform the finance sector, Franklin Templeton has recently partnered with Microsoft to build an advanced financial AI platform. The platform will use composable business applications to help Franklin Templeton rapidly embed AI in its processes and enable digital transformation at scale. The two firms—leaders in their respective industries—are aligning capabilities to facilitate continuous innovation within financial services.

With the exponential rise of AI in recent years, such as the above example, how can businesses, especially in the finance sector, embrace AI to enhance diversity, equity and inclusion (DEI), while also mitigating its potential risks?

I recently had the opportunity to talk with my colleague Deep Ratna Srivastav, Head of AI & Digital Transformation at Franklin Templeton, about the ways AI has been and will continue to transform the finance sector through broadening inclusion. Below is our conversation:

Regina: How can AI effectively address traditional barriers and foster more diversity and inclusion within the finance sector?

Deep: The biggest value that AI brings is scale. You can do things better, faster and cheaper. So almost by definition, it can allow for more inclusion. Especially in the financial industry, which traditionally has been able to focus more on certain communities and certain levels of wealth, AI can certainly broaden that base. You can bring costs down and you can start having an impact with people who never got access to financial advice and didn’t get the right education and information in the past. So, AI, in my mind, plays a huge role in how you can take something that has been accessible to certain elements of society and really broaden the base. If you do it right, it does. But the onus is on us, in the financial industry, to make it happen.

Additionally, almost every aspect of a financial services company can be improved through the use of AI. This includes recruiting more diverse talent, creating more customized products, having more efficient operations, and helping sales and marketing teams distribute products more successfully.

Regina: Going into specific examples, Franklin Templeton’s collaboration with Microsoft will seek to combine structured data and contextual financial information to deliver personalized experiences to differentiated financial services clients. This is different from many other AI initiatives that merely focus on limited capabilities, such as summarization and basic conversations.

Deep: Yes, Franklin Templeton envisions being able to give more sophisticated, personalized support to a broader set of clients. To do that, we need reasoning capabilities that really understand our clients, not just summarize a few data points. And if we can do these things for our clients, we can start doing them for the entire enterprise also.

Regina: Considering recent advancements and debates in the AI field, how do you envision the evolving relationship between AI and DEI in the future?

Deep: Like anything new, some people are worried about AI, and it is vulnerable to threats. AI is vulnerable to bad actors teaching it bad things. Added to this, as AI usage increases and becomes more powerful, it can start becoming the voice of every organization, of every industry. In my mind, AI needs DEI support to become part of the solution. We, as the technology builders, will have to be careful to make sure that we are bringing in the right culture when developing the applications. If we do that, AI will become highly inclusive, highly diverse and it will really help in driving equity. And so, these two really go hand-in-hand.

Also, as I mentioned earlier, AI can bring information and education to different sections of society who can then make the right decisions—allowing for more equity and inclusion. But this will only be the case if systems are trained, not only on those it has dealt with in the past, but also with other sections of society as well.

Regina: How can AI be leveraged to drive more equitable outcomes for underrepresented communities?

Deep: I think that goes straight to the heart of what AI does. For any AI application, if you leave it to a couple of engineers to create solutions, then they may end up inadvertently bringing in a lot of bias. How do you deal with that bias? The only way you deal with bias is by having a lot more diversity in the process from the start.

So right out of the gates, diversity becomes almost the driver to reduce biases—because you can train the systems on anything. The only way you can get it correct at the start is if you are using a lot of diversity in how you build it. This means bringing in a lot more diversity in how the system is being supervised and in how the system is being tested and monitored—the full feedback loop. In our world of AI, I would say that diversity almost becomes the foundational level that you need if you really want to get this process right.

Regina: Thank you Deep for your insights.

As we embrace the AI-driven transformation in finance, we have a critical opportunity to enhance inclusivity and equity. AI can democratize financial services, but achieving this requires integrating DEI principles right from the start. As leaders in financial services, we must ensure AI is developed ethically—with diverse teams and unbiased algorithms—for the benefit of all segments of society.



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