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Microsoft in Business Blogs

Woman sitting on the couch working on her Surface laptopThe rapid pace of innovation in artificial intelligence has led us to the next stage of AI development, which we call “industry verticalization”: designing AI products to meet the needs of specific industries.

For financial services, this means AI designed to tackle the specific use cases for insurers, banks, and large investment banks. These products and solutions build upon existing modular AI components, such as printed and handwritten text recognition, speech transcription services, and a variety of natural language processing (NLP) skills. The trend we are seeing with our customers is a combination of these, coupled with business-specific AI components.

For example, today’s money managers must digest an inordinate volume of research reports, 10-K’s, company news reports, and other disparate financial information to make the most impactful investment decisions. We know that AI can be utilized to distill this breadth of information and find the specific variables required for a money manager’s investment making decisions. As Director of Cognitive AI for Financial Services, I have the opportunity to hear from senior business leaders at large financial services organizations on these and other challenges. The discussions have led to the innovative use of AI tools to identify and distill the breadth of information a money manager needs to succeed.

Another example is the design of an AI model to extract information from forms that are relevant to a specific industry, such as insurance. The insurance industry uses the standard Acord form to price and quote insurance policies. These are complex multi-page forms that contain numerous fields about a property requiring insurance coverage. Insurers currently spend a significant amount of time extracting information and loading it into their back-office systems so they can provide a quote.

Designing an AI-automated system that receives an Acord form, extracts the required information, and then facilitates the quote process is nirvana. It helps insurance companies decrease the turnaround time for quotes and ultimately increase customer satisfaction.

Finally, the recent developments in NLP and language models, such as the Microsoft Turning multilingual language model and OpenAI’s GPT-3 are rewriting the playbook for how AI will unlock advances in worker productivity. For all intents and purposes, GPT-3 is an AI model that’s ingested almost everything on the internet (including Wikipedia, online books, blogs, etc.) and has become great at understanding language.

GPT-3, which was built using one of the world’s largest and fastest supercomputers in the Microsoft cloud, has generated extreme interest with CIOs and senior leaders, who foresee its usefulness in data summarization and interpretation. For example, its ability to summarize pages of text into a couple of paragraphs will help employees better cope with the massive amount of information being directed at them on a daily basis.

GPT-3 is intriguing and promising, it is currently being evaluated by researchers, and GPT-3’s broader impact on the future of AI in the workplace is still unknown. GPT-3 has its flaws and may still generate text that does not make sense or is biased. However, GPT-3 has immense potential, and we are just beginning to understand how we can utilize it to help employees become more efficient in the workplace, as well as the greater good it could serve in the world.

These advances in AI have driven industry “verticalization” and led to increased adoption of AI in the workplace, providing enterprises with prebuilt business specific logic that saves time, money, and resources. The ability to go from concept to production is significantly reduced, and implementation of AI in the workplace can now take weeks instead of months or years.

These are only a few examples of how enterprises will utilize industry-specific AI to make quicker and more accurate data-driven decisions, but the opportunities are endless. At Microsoft, we understand the need to incorporate an industry lens when building our products. These new AI solutions will certainly make jobs less mundane, increase employee productivity, and vastly improve customer service.

Decision makers in financial services have considerations particular to the industry. This new wave in AI will augment user productivity with a more targeted approach, helping the industry realize the true transformational impact of AI.

To get your business ready now for the future of AI innovation, learn more about the AI business school for financial services.