In virtually every client conversation I have these days, I am inspired by the innovation that generative AI has unleashed in the financial services industry. There is no shortage of creative ideas and impactful use cases for business transformation, with exciting new features to reduce costs, increase efficiency, improve productivity and deliver better customer support.
What’s equally, if not more important, is AI’s ability to help solve some of the world’s toughest social problems. This echoes the work we do with Microsoft Cloud for Financial Serviceswhere we strive to not only empower our customers, but also help improve the world at large through responsible AI and cloud computing.
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It is clear that generative AI opens new doors to create greater value for customers, the benefits of which are already visible. drama in all sectors. In the unique case of financial services, generative AI also opens up the possibility of solving global problems that have long posed a challenge to almost every segment of society.
Three areas of impact on financial services
In January, I had the opportunity to attend the annual meeting of the World Economic Forum in Davos, Switzerland. Naturally, AI was a big topic of conversation, and what encouraged me the most were the discussions and examples of its potential to impact major social challenges. In the context of social good, I see three key areas where this can happen:
1. Equity and inclusion
I see that advanced, generative AI holds enormous potential to create more inclusive and personalized financial products and experiences for a broader population. This could include the latest natural language features of chatbots, integrating screen reading and storytelling features such as See AI in your banking products for the blind and visually impaired community, and providing text-to-speech functionality for those with hearing impairments. A striking example of the transformative potential of AI in coding is the story of Anton Mirhorodchenko, a Ukrainian software developer with cerebral palsy. By using GitHub Copilot, he has significantly simplified his workflow and improved his productivity and outlook.
2. Poverty and stability
Financial inclusion is also critical to stability, as technological innovations open new opportunities for data-driven financial tools that can enable a broader range of underserved communities to achieve financial independence. There are a lot of exciting fintech innovations in this area. For example, CWallet, a financial technology company specializing in digital wallet services, is empowering migrant workers in Qatar to access financial services with Microsoft Azure. There are other significant fintech initiatives underway in places like Latin America And Kenya using AI and digital innovations to improve lives, reduce poverty, expand access to financial services and credit, and narrow the financial inclusion gap.
And it’s exciting to see how other organizations across industries are already innovating with Azure OpenAI Service to enable inclusive growth through technology. For example, as part of our new ADVANTA(I)GE INDIA Initiative and AI skills development efforts, Indian social impact organization, Karya, is using Azure OpenAI to help make technology accessible in underfunded languages and more inclusive data – with work that also provides rural citizens with training, fair wages, and education on financial tools to make the best use of their income.
3. Environment
We all recognize the critical importance of tackling climate change, and it is already an important topic in financial services. But I think we’re only scratching the surface of AI’s potential to address common risks and opportunities in environmental, social, and governance (ESG) and sustainability efforts in the ISF space in due to slow manual processes, siled data, data quality issues, lack of information, and reporting. Advances in generative AI can help synthesize structured and unstructured data, create ESG insights and recommendations, and communicate to stakeholders. I’m also excited to see examples of financial leaders like United Arab Emirates transform sustainability measurement capabilities with Microsoft Sustainability Manager.
When it comes to achieving these ambitions – and countless others where AI can make a major difference – success requires more than just cutting-edge technology. Microsoft believes that meaningful innovation can only occur when organizations also adopt a set of core principles focused on ethics and human factors.
The crucial role of responsible AI
The excitement about this next wave of AI is undeniable, but we must use it responsibly to avoid perpetuating bias or excluding segments of society. At Microsoft, we are committed to helping our customers use our AI products responsibly, sharing our learnings, and building partnerships built on trust.
To help financial services organizations realize the potential of AI, Microsoft has released the Responsible AI Standarddeveloped a Impact evaluations template and created transparency documents for clients using our Azure OpenAI Service and products like new Bing to share what we have learned. Microsoft open source Equitable learning The toolkit can also help financial services organizations ensure their AI systems are fair by identifying biases in data. When our partner EY put it to the test using real mortgage underwriting data, it improved the fairness of lending decisions, reducing gender disparities from 7% to less than 0.5%. From Davos you can also look at my round table on the responsible deployment of AI in financial services.
How inclusive design and diversity unlocks potential
Inclusive design draws on the broad spectrum of human diversity and gleans insights from varied perspectives. Microsoft champions design principles that recognize exclusion, learn from diversity, and create universally beneficial solutions. Technology designed this way means greater access, less friction, and greater emotional connection with more people.
Our commitment to helping others adopt inclusive solutions is reflected in our Microsoft Inclusive Design Toolkit. The tools create solutions at scale, such as more responsive, less biased digital experiences and more accessible cities. In the financial sector, this translates into products and services designed to meet the needs of as many people as possible, regardless of their abilities or circumstances.
Likewise, diversity is a proven catalyst for innovation within technology teams. Studies show that greater diversity can help teams focus more on facts, process those facts more carefully, and generate more creativity and innovation.1 Ethnic and gender diverse leadership teams are more likely to outperform financially in their industry, and companies with more women in leadership positions tend to be more profitable.2 So, for technology to be truly inclusive, it must be built by teams that reflect the diversity of its users.
A mission of empowerment thanks to AI
My transition from banking to Microsoft was driven by the potential for meaningful technological innovation that could create positive change. Despite the challenges we face, my outlook remains optimistic. I hope this blog has given you some ideas and I invite everyone to get involved in efforts to use AI in a way that benefits society as a whole.
Microsoft’s mission is to empower every person and organization on the planet to achieve more, and we do that by creating technology that we believe will change the world. To achieve this, we know that we must assume a set of important responsibilities. Trust, reliability, safety, privacy, security, inclusiveness, transparency and accountability: these are the fundamental principles that have guided our leadership in AI over the past decade. Alongside our partners and many other global stakeholders, we invite you to join us on the important journey ahead.
To learn more about our commitment to trustworthy AI and to find other resources, please visit our Fostering responsible AI practices website.
1Diversity wins. The importance of inclusion. McKinsey & Company, May 2020.
2Why diverse teams are smarter. David Rock and Heidi Grant, Harvard Business Review, November 4, 2016.
