Innovation is Fusion: You got your chocolate in my peanut butter!

Partnerships have become a driving force of innovation because firms can achieve things by pooling their capabilities that they can't achieve alone. Few firms are experiencing this more acutely than financial data providers as they seek to meet their customers where they are, integrate their data into workflows and move up the value chain from providing data to helping users produce insights.

This trend is starting to gain momentum in the Wealth Management industry. As tech becomes more central to the advice process, Wealth Management firms (and the vendors that serve them) are pushing the envelope on their tech capabilities to help Advisors differentiate their advice and scale their practices.?

AI has been a catalyst for this process, but it has also raised new challenges:

• The technology is new and is evolving so quickly that firms can't keep up with what it can and can't do;
• AI is only as good as the data it's used on; you really can't evaluate it effectively without a high-quality dataset that you understand well;
• The stakes are higher than ever as firms are pressured to take advantage of AI while also being conscious that it introduces myriad risks.

This context was the catalyst for a unique collaboration between 微软 and 晨星 . We've watched large firms with mature strategy, product and program management organizations mobilize to build GenAI use cases. Even in the best circumstances it takes months to get an idea off the ground. Mid-sized firms have great ideas and a bias for action, but without these coordinating resources, they're having a tougher time getting started.?

So we asked ourselves a question: If we pool our respective firms’ tools, data and skills at a single place and time around a structured design process, can we help our joint customers innovate more quickly? The result was truly inspiring!

The Setup

The concept was to bring together Microsoft tools and Morningstar data to help the audience visualize and prioritize innovative use cases to build for their users. Based on our collective client experience we created a list of use cases that firms would likely want to explore. Microsoft selected products from its toolkit that would be helpful in bringing those use cases to life; Morningstar selected data sets that would be needed to hydrate the use cases. Because investing is both art and science, we included data sets that contained both structured (tables with investment returns) and unstructured data (narrative research reports) in the exercise.

We brought it all together in Microsoft's Soho innovation space (The Garage) and took the participants through a structured Design Thinking exercise: they elaborated on user problems, brainstormed “how might we?” questions to envision opportunities, and then ideated on potential solutions. The exercise culminated in solution prototyping in a sandbox, pre-loaded with Morningstar data. Special thanks to our partners at Protiviti who set up this environment and provided SMEs to guide participants through this part of the process.

The Result

Participants explored a wide array of use cases, mostly aimed at helping Advisors become more efficient and enhance the quality of advice. Some highlights included:

• Helping Advisors explain portfolio performance by using LLMs to generate narrative descriptions of portfolio performance and market trends. The concept included tailoring the narrative to each client’s interests and knowledge level by mining meeting transcripts.
• Helping Advisors structure more diversified and personalized portfolios by using LLMs to compare the details of complex products like Alternatives and ESG funds.
• Helping Advisors keep client assets through wealth transfer events by cultivating deeper relationships with family members. This team went deep on how meeting transcripts and other relationship data could be used to measure attrition risk, recommend engagement opportunities and combat Advisor biases.

The entire group spent a lot of time talking about data - what data they have, what data they would need, where it might be acquired and myriad considerations around privacy, consent, security and of course, regulation. Attendees also explored other risks and pitfalls with Microsoft, Morningstar and Protiviti experts with first-hand AI product development experience.

Participants finished the day with a better understanding of the problems they wanted to solve for their target user, a strawman of the solution and a deeper understanding of the role technology will play in the future of advice.

The Path Forward

This event was born out of a hypothesis that together, Microsoft and Morningstar would be able to help our mutual customers innovate more effectively than we could individually. The event itself was a prototype of how three customer-obsessed organizations could come together to create a uniquely valuable experience. While the outcomes and customer feedback definitely validated our hypothesis, we also identified several ways to improve. We invite Wealth Management firms who are committed to innovating with data and AI to join us and our partners at Protiviti on this journey.

Lawrence Johnson , Steven Berger , Marc DeMoss , Benjamin Barrett , Rick Schmehl , Vimal Vel , Gino Rodriguez , Brandon Swinton , J.P. (Jody) DeCuire , James Ensminger , Christine Livingston , Jonathan Rapchak , Yifei Yun