Innovation in Lending
Watch: Charting the Course To Responsible AI
February 4, 2021
As AI adoption accelerates in financial services, focusing on the best strategy for AI innovation has become a top priority. A recent report indicated that organizations are having trouble implementing this advanced technology to achieve desired business goals. With AI project failure rates nearing 50%, the need for a proven roadmap is becoming more critical. So, what’s the best approach to achieve success with AI in 2021?
Real-World Insights from Financial Institutions Implementing AI
Zest CTO Jay Budzik joined Natalie Cartwright, Co-Founder and COO of Finn AI, and Emil Matsakh, former Chief Analytics Officer at Commonwealth Bank of Australia (CBA) to discuss the viable paths to AI adoption and provide insights from financial institutions who have successfully implemented machine learning into their business.
Choose Your AI Adoption Model (Buy vs. Build)
Natalie kicked the conversation off by providing an overview of AI adoption models, from buying AI-powered software to building the capability in-house and detailing the pros/cons from the following perspectives: data, talent, and ethics. You’ll walk away with a clear list of questions and considerations to help with your AI model selection.
Establish ROI, Adopt Responsibly, Implementation Flexibility
Jay focused on the building blocks to help banks and credit unions gain the most from their AI investment. He said, “It’s essential to establish a set of clear ROI goals that can be measured.” For lenders, this can be increasing approvals without increasing risk, reducing losses while holding approvals constant, or better risk-based pricing.
After aligning your AI strategy to lending objectives, Jay discussed the importance of addressing regulatory concerns, applying the right regulatory framework to your use case, and selecting the right path to production (yes, there are multiple ways to get there!).
From data considerations to explainability, Jay addresses the nuances and provides specific milestones financial institutions can apply to their AI strategy roadmap.
Conclusion: Innovation Favors the Bold
While many companies are still struggling with moving AI projects from proof of concept to production, all three panelists agreed that there are multiple steps financial institutions can take to ensure success. From selecting the right AI Model to aligning on ROI goals to adopting AI responsibly, watch this lively discussion to get your AI roadmap to success.