With AI often leading new workflows in financial services, we have recently looked at the best way to implement technologies on the forefront to elevate our solutions for a more integrated client experience.
In implementing AI to drive distinct value benefits for our clients, we took an agile approach as the product team and followed these four guiding tenants:
1. Identification of business issues. We harnessed the strength of the product development team in the ideation process, asking everyone to contribute ideas for AI-powered use cases. Ultimately, we chose to focus on more mature functional areas with well-defined processes and high client usage. Then, we narrowed in on use cases that would demonstrate distinct value-add with AI. The criteria was to go beyond process automation and showcase real learning without human intervention.
2. Solution Execution. There is no better way to learn than by doing. We purposely selected use cases that were focused in scope, so we could move quickly through the entire life cycle from idea generation to user adoption. Focused use cases also narrowed the field of possible technology choices. This hands-on experience gave us the foundation to determine a broader, longer-term AI strategy
3. Iteration and Assessment. As with anything new, we expected to iterate along the way. We hosted client validation sessions to show what we built to real users, gather feedback, and modify our solutions based on that feedback. We also iterated on our technology choices, testing out various machine learning models and open source libraries before settling on what worked best for each use case.
4. Operate to Scale. One year later, we have a number of AI-powered solutions available for production use, including machine learning that suggests next user actions in Advent Lumis(SM) our data governance solution, and natural language processing that auto-tags research content in Tamale RMS®, our research management system. Equally important, we gained practical knowledge and are in a much stronger position today to invest in artificial intelligence and machine learning strategically and with longer-term focus in mind.
Whether artificial intelligence, machine learning, robotics, or Blockchain technology, the key to getting started is to look for real-world applications that can be put to the test. Start small, build expertise, and be prepared to iterate along the way. Learn more about our solutions today.