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Program Highlights »
Fri Dec 07 05:00 AM -- 03:30 PM (PST) @ Room 511 CF
Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy
Manuela Veloso · Nathan Kallus · Sameena Shah · Senthil Kumar · Isabelle Moulinier · Jiahao Chen · John Paisley

The adoption of artificial intelligence in the financial service industry, particularly the adoption of machine learning, presents challenges and opportunities. Challenges include algorithmic fairness, explainability, privacy, and requirements of a very high degree of accuracy. For example, there are ethical and regulatory needs to prove that models used for activities such as credit decisioning and lending are fair and unbiased, or that machine reliance doesn’t cause humans to miss critical pieces of data. For some use cases, the operating standards require nothing short of perfect accuracy.

Privacy issues around collection and use of consumer and proprietary data require high levels of scrutiny. Many machine learning models are deemed unusable if they are not supported by appropriate levels of explainability. Some challenges like entity resolution are exacerbated because of scale, highly nuanced data points and missing information. On top of these fundamental requirements, the financial industry is ripe with adversaries who purport fraud and other types of risks.

The aim of this workshop is to bring together researchers and practitioners to discuss challenges for AI in financial services, and the opportunities such challenges represent to the community. The workshop will consist of a series of sessions, including invited talks, panel discussions and short paper presentations, which will showcase ongoing research and novel algorithms.

Opening Remarks (Talk)
Invited Talk 1: Fairness and Causality with Missing Data (Invited Talk)
Invited Talk 2: Building Augmented Intelligence for a Global Credit Rating Agency (Invited Talk)
Panel: Explainability, Fairness and Human Aspects in Financial Services (Panel Discussion)
Coffee Break and Socialization (Break)
Invited Talk 3: Fairness in Allocation Problems (Invited Talk)
Paper Presentations (see below for paper titles) (Talks)
Lunch (Break)
Invited Talk 4: When Algorithms Trade: Modeling AI in Financial Markets (Invited Talk)
Invited Talk 5: ML-Based Evidence that High Frequency Trading Has Made the Market More Efficient (Invited Talk)
Paper Presentations (see below for paper titles) (Talks)
Announcement: FICO XAI Challenge Winners (Announcement)
Coffee Break (Break)
Invited Talk 6: Is it possible to have interpretable models for AI in Finance? (Invited Talk)
Paper Presentations (see below for paper titles) (Talks)
Posters and Open Discussions (see below for poster titles) (Poster Session)
Closing Remarks (Talk)