COMMON SENSE AI

The Common Sense AI Financial Services agenda has been developed with input from engineers, data scientists and digital transformation leaders in financial services as well as FinTech companies building the future of AI.

How Companies Build Useful Chatbots and Keep Them Smart

• Chatbots are the entry point for many companies into the universe of “AI”.
• They are also often dismissed as annoyingly limited and not at all intelligent.
• We’ll discuss how companies build useful, not-annoying chatbots, and evolve them to stay that way.

Evaluating Human-in-the-Loop AI Systems

• Many of the most exciting applications of AI are those that serve as a “force multiplier” for your human subject matter experts.
• How are companies developing AI systems designed from the start to work with a human as an integral component of a complex workflow instead of an afterthought?
• We’ll discuss some ways you can evaluate how well an AI system is built to be effective with a human in the loop.

Insurance Use Cases for AI in 2020

• AI is already beginning to transform insurance from quotes to underwriting to claims.
• We’ll explore the opportunities and the pitfalls of AI initiatives in the insurance industry.

Balancing Ethics and Efficiency in AI Adoption

• AI is inherently powerful, and power corrupts. AI is also notoriously susceptible to the bias of model builders.
• How are companies working to ensure AI systems don’t trample individual rights including expectations of privacy?

Will Developers Become Irrelevant?

• As low code development platforms proliferate, will coders be replaced by data scientists and subject matter experts?
• How will the developer role likely shift in the next 5 years, and what should you be doing to prepare for it?

Building the AI-Augmented Workforce

• Recruiting, training and retaining the people who work with and alongside AI systems will require new management strategies.
• Some of these strategies will themselves be made possible by AI systems. We’ll discuss how companies are preparing to win in the AI-augmented future.

No More Black Boxes: What The Shift to Explainable AI Means

• How much should you trust AI systems that hide their decision making process in a “black box”?
• A new generation of AI systems allow users to understand how results were produced, making them more accountable, auditable and trustworthy.
• We’ll walk through several examples of explainable AI systems and discuss the implications for financial services businesses.

Preparing Your Organization for Strategic Adoption of AI

• Companies should explore hypothesis-driven scenarios to understand where and when disruption is likely to occur and which business lines will be impacted.
• How can you design AI pilots and POCs that test how successful you may be operating in a particular role within a data- or IoT-based ecosystem.

How AI and automation impact loan delinquency treatment.

Getting Leadership Buy In: How we got our Executive Management Committee to understand:

1. What is digital transformation
2. Why it’s important
3. How it touches all employees & areas of our business
4. Why we need to invest in it.

Remove friction from your data science workflows:

Machine learning opens up many opportunities. However, actually operationalizing Machine Learning applications remains a challenge. In this session, we will review common causes of friction and best practices to overcome them.

AI-Powered Data Privacy

How can AI be applied to protect sensitive data and ease compliance burdens that are increasing every year?