Fiduciary Duty
Meets Data Science

Engineer turned financial planner, building secure technology and CE-approved programs for the advisory industry.

View CE Programs About Matteo
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Holistiplan (Alum) · AARP TaxAide — Site Lead · Garrett Planning Network · NYC Turing Fellow (2013) · Capital One · CFP® Professional · Enrolled Agent · Holistiplan (Alum) · AARP TaxAide — Site Lead · Garrett Planning Network · NYC Turing Fellow (2013) · Capital One · CFP® Professional · Enrolled Agent ·
Background
The "E-Shaped" Expert
Matteo Hoch
Credentials
CFP®, Enrolled Agent
Education
University of Illinois at Urbana-Champaign
Specialty
Unstructured Data: OCR, Computer Vision, AI, Visualization
Advocacy
Site Lead, AARP TaxAide
Fellowship
NYC Turing Fellow '13

Data Science & Engineering

With a technical foundation from the University of Illinois at Urbana-Champaign, my career has been defined by mastering unstructured data. Whether it was building computer vision models to "read" complex nutrition facts labels or having my sports data modeling work cited by the Harvard Sports Analysis Collective, I specialize in turning noise into signal. This engineering background led me to Holistiplan, where I saw firsthand how much "tax alpha" remains trapped in tax documents—waiting for the right technology to unlock it.

Data Visualization

At Capital One, the data visualizations I developed caught the attention of senior leadership—culminating with a presentation to the CIO demonstrating the power of bespoke data products to help business managers run their most critical operations. That experience crystallized a conviction: the right visual layer on top of the right data changes how leaders make decisions.

Technical Tax & Planning

When I couldn't find an hourly financial planner to help with my own software consulting business, I decided to become one. As a CFP®, EA, I experienced first hand how tough it is to be a financial planner and tax preparer.

Now I'm bringing these threads back together—building tools and training that let fiduciaries move faster, and deeper, without compromising the trust their clients depend on.
Continuing Education
Speaking & CE Programs

Highly technical, objective-based educational sessions designed for NAPFA, CFP Board, and IAR continuing education requirements.

Technical Tax Planning

Hidden Tax Alpha: Optimizing Cash Sweeps and ETF Share Classes

A deep dive into the state income tax mechanics of money market federal obligations and the capital gains implications of the Vanguard patent expiration.

Learning Objectives
  • Analyze ETF share-class structures and in-kind redemptions.
  • Calculate state tax impact of MMF federal obligations.
  • Evaluate historical sweep vehicles for HNW tax efficiency.

Not yet approved for CE.

Practice Management & Compliance

Trust, But Verify: The SEC's AI Sweep and Fiduciary Compliance

Translating LLM architecture into RIA compliance. Learn the difference between zero-retention APIs and public model training, and how to audit vendor SOC 2 reports.

Learning Objectives
  • Identify SEC Rule 204-2 violations in generative AI tools.
  • Evaluate the data flow of predictive vs. generative models.
  • Establish a Books & Records compliant vendor framework.

Not yet approved for CE.

On the Road
Speaking Events
Upcoming
Garrett Planning Network
2026 GPN Retreat
Minneapolis, MN — Jul 30 – Aug 1, 2026
FRI
Utilizing AI Panel · Host
4:00 – 5:00 PM
SAT
Make Your Own Client Deliverables with AI
3:00 – 4:00 PM
Event details & registration
Past
Immersion Conference · 2026
AI Tactics for the Transparent Advisor
Co-presented with Daniel Bishop
GPN Conference · 2025
The Early Years: Highs and Lows and Lessons Learned
Panelist
Evidence-Based Insights
Selected Publications
Industry Research
State of the Financial Planning Profession: January 2026

An analysis of ADV filings to determine what RIAs are doing from an unbiased sample. This report explores fee-models, hourly rates, and behavior in different states.

Read Report
Machine Learning
Predicting Brain Age with Convolutional Neural Networks

A novel measure utilizing CNN models to predict brain age using T2 Weighted and FLAIR MR Images. This research demonstrates the application of deep learning in interpreting complex biomedical datasets.

View Poster
Predictive Modeling
A Simple Improvement to FiveThirtyEight's NBA Elo Model

Cited by the Harvard Sports Analysis Collective, my paper created a public implementation of Nate Silver's Elo rating systems that helped HSAC researchers better account for variance in professional basketball performance metrics.

View Citation
Current Venture
Fin Pods AI

In addition to planning and speaking, I am the founder of Fin Pods AI, a Public Benefit Corporation chartered to improve the personal finance ecosystem. We build SOC-2 compliant data infrastructure for fiduciaries.

Visit Fin Pods AI