"We're pioneering deployment of machine learning on massive, highly complex financial datasets, a huge investment that touches all parts of JP Morgan Chase’s business, from hedging strategies to trading to the critical area of detecting fraud."

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What was the opportunity you sought to address with AI?
Model risk control is a critical function in the investment bank. Stricter regulations have led to an abundance of restrictions, model reviews, testing, and monitoring on models used in trading. Model risk data and and workflows need to be efficiently handled thru automation and accurate analysis, identifying the correct actions to apply once an event is identified. AI can have a significant role in enabling pattern discovery (fraud, issues), issue classification and categorization, data quality identification and remediation, and overall reduction of the cost of doing business. That involves a complete end-to-end solution, from development to deployment ofmachine learning models.

What advice would you share with others who are considering using AI?
Find a problem to solve first — talk to your stakeholders and understand theirpain points. Then evaluate all possible solutions, including non-AI. Consider the total cost of ownership of an AI solution and make sure it’s sustainable and that results are trustworthy and explainable to stakeholders.

What do you believe is most critical to making an AI project successful in driving business results?
Understand the use cases and get agreement with the users on the measures for success. AI can be a part of the complete solution. Understand the end-to-end strategy and design flexibility without over-engineering. Get lots of immediate feedback, and develop in an agile way.

What’s the best advice you’ve ever received?
Make opportunities for yourself – don’t wait to get them handed to you. How?Talk to people, get feedback, ask for help, don’t accept the status quo, ask questions, challenge, don’t expect to solve everything yourself — and look for the best in your network.

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