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The FATE of Financial Crime PreventionPedro Saleiro

Money2020 - Las Vegas, October 2019

Pedro SaleiroData Science Manager

The FATE ofFinancial Crime Prevention:Fairness, Accountability,Transparency and Ethics in AI

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The 3 main ethical problems of AI today(not adequately addressed by regulation, yet)

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1. Bias and Fairness

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What about the online payments industry?

The fictional example of Tyler and Xmusic:The False Positive Rate for Tyler’s zip code is

5X higher than average

Xmusic is not aware of the biases ofits fraud prevention AI solution

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2. Transparency

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State-of-the-Art in Explainable AI

Transaction: 23132Score: 875

Fraud Non-fraud

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3. Accountability

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Companies must use AI that is compliantand tied to their values!

But...

Increasing complexity (e.g., deep learning) and automation (e.g., AutoML) makes it hard

to understand AI and its impact.

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FATE to the rescue!(let’s talk about a few research projects)

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1. Bias and Fairness Audits

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What do you need to audit an AI system?

1. Fraud predictions 2. The true outcome

(fraud/not fraud)3. Protected attributes

you care about4. Select bias metrics5. Bias audit toolkit (e.g. Aequitas)

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The Awareness Effect

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2. Human-Interpretable Explanations(and adequate evaluation)

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How a great explanation looks like

Transaction: 23132Model Score: 875

Explanation:Suspicious because it's an

high-speed ordering from a bot

Fraud Non-fraud

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Semantic Layer for Explanations

Linking low-level model-based explanations with semantic

concepts from a fraud ontology

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Systematic Evaluation of Explanations

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3. Robust and Multi-Objective Model Selection

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The Awareness Effect (again!)

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Multi-Objective Model Selection

From all the compliant models optimize:

1. Overall performance (e.g., Recall)2. Fairness (e.g., FPR disparity nationality)3. Performance Stability4. Quality of Explanations5. Energy consumption (!!)

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OutlookFairness, Transparency and Accountability arecurrent ethical issues in AI

FATE research at Feedzai is working on:1. Fairness Awareness through audits2. Human-Interpretable and useful explanations3. Robust and multi-objective model selection

We are empowering our clients with control to develop AI that is compliant, tied to their values and function as intended!

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THANK YOU