Today, 3 Arc Advisory was at the AI in Financial Services conference at Loyola University Chicago’s Quinlan School of Business. Here are our top 5 takeaways from a great day:
- Data access and data quality continue to be top challenges for using AI, particularly operating at scale and with appropriate governance throughout. We’ve seen this across industries and maturity levels too.
- The need for interpretability and explainability of AI solutions highlights the importance of traceability and tracking of models, features, and the data underlying them. We’d add that to do this well, it needs thoughtful planning and implementation to capture key information.
- Graph networks and databases are becoming more important, especially in fraud detection and 360 customer views. We’ve also seen this in other relationship mapping, such as for business development in professional services and employee engagement in HR functions.
- To understand your customer’s pain points, sit in on calls with your customer service team. We’d add that it’s incredibly valuable to shadow key roles in your organization who produce the data you want to use in your AI models – in our experience it always creates learnings of how (and how not) to interpret the data.
- There was broad agreement that better standards and ethical AI frameworks are needed around AI. We look forward to partnering with organizations as they develop their best practices.