POLYGON RESEARCH ACADEMY

DATA AND AI
IN HOUSING FINANCE

Master the intersection of data, industry knowledge and AI advancements. Designed for the housing finance professionals and data-driven thinkers, this program goes beyond theory and gives you hard, practical skills and a deep understanding of the market forces shaping the housing finance industry today. By the end, you'll understand the critical data flows and AI's transformative role in housing finance and you'll be ready to turn insights into action, making smarter, data-backed decisions that drive impact.

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Data and AI in Housing Finance is built upon the foundation of Leading With Data Science (LWDS) course, authored by Polygon Research and delivered via the Future Housing Leaders Program at Fannie Mae since 2020. It provides students with the knowledge and skills to ethically and efficiently use industry data and SaaS technologies to understand the housing finance markets, products, customers, and lenders. The course consists of live instruction, on-demand videos, guest speakers, exercises, and hands-on data analysis using interactive apps. The course is continuously updated to channel the latest AI developments as well as to reflect changes in the data describing the housing finance domain.

Upon completion of this course, students will:

Acquire deep knowledge of the housing finance industry through its data

Understand the links among Data, Industry Knowledge, and AI

Become proficient in applying data and tools with real-life scenarios

Develop hard, practical data science skills in housing finance

The course consists of 7 live sessions

Week 1

Orientation

Introduction to the course goals and plan.

Review the course timeframe and logistics

Overview of class tools

Introduction to the main themes of the class

Week 2

Housing Finance

Weekly AI Recap - current new trends in AI

Demographic Drivers of Housing Demand

The Housing Finance Domain

How HMDA describes:
-> Loan Originations
-> Secondary Market
-> Loan Servicing

Projects and Assignments

Week 3

Data Science: Data, AI, and Machine Learning

Weekly AI Recap - current new trends in AI

Core Lesson: Terminology, concepts, techniques. The current state of the art in AI - technology, application, and regulation.

Statistical techniques for data quality - part 1

Projects and Assignments

Appendix (additional reading)

Week 4

Microdata & the Geographic Context for Housing Finance

Weekly AI Recap - current new trends in AI

What is microdata? Why Understanding Geography is Important?

How is Geography Expressed in HMDA LAR? How does it change and how do we measure it over time

Statistical techniques for data quality - part 2

Projects and Assignments

Week 5

Market Efficiency and Competitive Analysis

Weekly AI Recap - current new trends in AI

Market Efficiency in Mortgage Banking

Competitive Analysis
->Vectors for Competitive Analysis
->Discussing Methods of Identifying Peers
->Exploring HMDA LAR data fields defining lenders

Statistical techniques for data quality - part 3

Projects and Assignments

Week 6

Fair Lending in the Era of Gen AI

Weekly AI Recap - current new trends in AI

What is Fair Lending?

Fair Lending Basics

The Role of Descriptive Data Science in Fair Lending

Automated Valuation Models

Projects and Assignments

Week 7

Loan Servicing

Weekly AI Recap - current new trends in AI

RAG Servicing Example

Servicing Basics and the Biggest Risk in Servicing

Modeling Loan-Level Performance Data

Live walkthrough in Snowflake and Polygon Research tools

Projects and Assignments

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DATA AND AI IN HOUSING FINANCE

Upon completion of this course, students will:

The course consists of 7 live sessions

Data and AI in Housing Finance

DATA AND AI
IN HOUSING FINANCE