Knowledge graph applications for AI-driven financial services

A talk by Wanying Ding
VP, Applied AI/ML Lead, JPMorgan Chase

Register to watch this content

By submitting your email you agree to the Terms of Service and Privacy Statement
Watch this content now

Stages covered by this talk

About this talk

Knowledge graphs are at the core of many AI systems by supporting quick data preparation and complex computation. Knowledge Graphs can help find meaningful connections amongst disparate datasets, providing comprehensive and contextual analysis for many AI-driven financial services. This includes Risk and Fraud management, Algorithmic Trading, Loan/Insurance Underwriting, Chatbots, Document Analysis etc. In this regard, Knowledge Graphs are reshaping the business landscape and nature of modern financial services. In this presentation, we will present several use cases to illustrate why knowledge graphs are building blocks for modern financial services. Then we will discuss the critical techniques for building a Knowledge Graph, which includes defining an ontology, conducting information extraction, unifying given datasets. We will also demonstrate how a Knowledge Graph facilitates AI-driven financial services around Natural Language Understanding, Question and Answering, Recommendation, Reasoning, etc.

Have you got yours yet?

Our All-Access Passes are a must if you want to get the most out of this event.

Check them out

Proudly supported by

Want to sponsor this event? contact us.