Customer Stories: AI in Financial Services (Cloud Next '19)
Science & Technology
Introduction
Introduction
Welcome to Day Three of Cloud Next '19! In this session, we delve into the application of Artificial Intelligence (AI) in financial services. We explore how various organizations are leveraging AI to enhance client engagement, improve operational efficiency, and navigate the complexities of managing large-scale data.
The Importance of AI
Artificial Intelligence is becoming increasingly crucial for financial institutions looking to remain competitive and innovate. As companies like the National Bank of Canada illustrate, adopting AI requires significant cultural shifts alongside technical development. During the session, speakers shared their journeys, including the challenges and successes they experienced while implementing AI solutions.
Speaker Highlights
National Bank of Canada
Dave Forlong, Senior Vice President of Innovation at the National Bank of Canada, discussed how a 160-year-old bank is transforming its operations through AI. He outlined a strategy centered on three key priorities:
- Enhancing revenue opportunities.
- Improving client and employee experiences.
- Increasing operational efficiency by reducing costs.
Dave shared some valuable lessons learned over two years, including the importance of hiring the right talent, funding end-to-end software development, and transitioning to scalable, open-source solutions. He emphasized that AI can accelerate objectives but requires a significant change management approach involving clients and staff.
Rabobank's Digital Transformation
Dan Kooning, currently a freelance consultant at Rabobank, introduced their innovative Google Assistant project, which allows users to interact with the bank through voice. This initiative aims to adapt to the changing landscape of customer interactions, where traditional banking methods are losing ground to digital and conversational channels.
Dan shared the mission behind the Google Assistant integration and emphasized the importance of staying focused, forming agile teams dubbed "speed boats," and having executive support to navigate compliance issues effectively.
Pluto 7's AI Implementation
Jonathan Jiang and Dhruva Reddy from Pluto 7 presented their approach to building scalable predictive models for loan delinquency. They leveraged Google Cloud's tools, including BigQuery for data exploration and ML Engine for deploying machine learning models.
Their solution involved extensive data preparation, feature engineering, and the comparison of multiple models, including AutoML, TensorFlow, and XGBoost. The outcome demonstrated the power of Google Cloud in solving complex financial problems.
Conclusion
The stories shared at Cloud Next '19 highlight that successful AI implementation in financial services is not just about technology but also about building a culture that encourages innovation and agility. As these organizations move forward, they remain committed to harnessing AI's capabilities to transform their operations and better serve their clients.
Keywords
- Artificial Intelligence
- National Bank of Canada
- Rabobank
- Google Assistant
- Customer Engagement
- Operational Efficiency
- Pluto 7
- Financial Services
FAQ
Q: What was the main focus of the session on AI in financial services?
A: The session focused on how financial organizations are leveraging AI to improve client engagement, operational efficiency, and data management.
Q: Who were the main speakers in the session?
A: The main speakers included Dave Forlong from the National Bank of Canada, Dan Kooning from Rabobank, and Jonathan Jiang and Dhruva Reddy from Pluto 7.
Q: What strategies did the National Bank of Canada employ for AI implementation?
A: The National Bank focused on enhancing revenue, improving client and employee experiences, and increasing operational efficiency.
Q: What innovative project did Rabobank introduce?
A: Rabobank introduced a voice banking solution integrated with Google Assistant, allowing clients to manage their accounts through voice commands.
Q: How did Pluto 7 utilize Google Cloud for loan delinquency predictions?
A: Pluto 7 used Google Cloud tools like BigQuery and ML Engine to prepare data and deploy machine learning models to predict loan delinquency effectively.