FINRA

•

5 min

Over 812B market events/day: shifting FINRA from feature delivery to threat response

Data-Driven Decision Frameworks • AI Governance

Role:

Director, Product Design & Research

Team:

7

900

%

Per team cost to develop behavioral analytics

900

%

Per team cost to develop behavioral analytics

250

%

Length of org. approval cycles (avg. 8 → 6 weeks).

250

%

Length of org. approval cycles (avg. 8 → 6 weeks).

30

x

Avg. featuer adoption (~10% → 30%) org-wide after CoE rollout.

30

x

Avg. featuer adoption (~10% → 30%) org-wide after CoE rollout.

600

%

Org-wide AI adoption 8 months after AI goverance

600

%

Org-wide AI adoption 8 months after AI goverance

Confidentiality Notice

My work at FINRA was focused on highly sensitive market surveillance and privacy initiatives. To comply with strict non-disclosure agreements, all proprietary data, live interfaces, and specific workflows have been omitted. This case study focuses exclusively on high-level strategy, organizational architecture, and publicly communicable outcomes.

Challenge

Without a dedicated user experience discipline, product design and strategy were inconsistent and siloed. Teams operated independently, and there was no consistent source for research, measurement, or design quality.

strategy

I built a cross-functional design organization from scratch and instrumented FINRA's portfolio with behavioral analytics (Pendo) and AI, giving teams a shared evidence layer to make decisions from.

Results

Teams began making decisions from observable behavior instead of assumptions, reducing approval cycles by 25%. Analytics adoption costs dropped by 90%, and feature adoption increased from an average of <10% to +30%.

Challenge

No design function

When I joined FINRA, design was largely an engineering responsibility with no shared standards, centralized practice, or operational alignment. Most teams had never worked with dedicated UX partners.

The problem was not resistance to design. It was fragmentation and funding. Every team had evolved its own workflows, patterns, research habits, and delivery assumptions over time.

Challenge

No design function

When I joined FINRA, design was largely an engineering responsibility with no shared standards, centralized practice, or operational alignment. Most teams had never worked with dedicated UX partners.

The problem was not resistance to design. It was fragmentation and funding. Every team had evolved its own workflows, patterns, research habits, and delivery assumptions over time.

Example of the hybrid-format discussion guides used to collect insights

strategy

My 6-pillar framework for product-led growth at FINRA

As the organization matured, the challenge shifted from introducing UX to building durable systems that teams could operate independently.

strategy

My 6-pillar framework for product-led growth at FINRA

As the organization matured, the challenge shifted from introducing UX to building durable systems that teams could operate independently.

Low fidelity mock of the product analytics

Example fishbone root-cause diagram used to demonstrate the cascade effect of frictions sources

Strategy
What I Did

Lean alignment first

I avoided introducing heavyweight process too early. Small working sessions and lightweight artifacts created faster adoption and reduced organizational resistance.

Build the operating system

Co-built RACI models and approval frameworks with product and engineering to create shared accountability.

Make data the deciding voice

Piloted then scaled behavioral analytics across 65 products and built a CoE to turn data access into org-wide fluency.

Foundation before velocity

Established the first research practice, centralized insights repository, and design system across all 65 products.

Build the org to flex

Deployed a hybrid model: embedded teams for continuity, flexible resourcing for spikes, generalists before specialists.

Govern the AI

Built the governance framework that took FINRA from a no-AI policy to enterprise-standard LLM adoption.

results

Selected highlights

I'm immensely proud of the things I achieved at FINRA in the short span of 3 years, and even more excited for the inertia my teams have continued. Here are some highlights:

results

Selected highlights

I'm immensely proud of the things I achieved at FINRA in the short span of 3 years, and even more excited for the inertia my teams have continued. Here are some highlights:

Enterprise Adoption
30

x

Exposed hidden adoption barriers across 12 enterprise products, increasing feature adoption from ~10% to ~30% and cutting operational waste.

Enterprise Adoption
30

x

Exposed hidden adoption barriers across 12 enterprise products, increasing feature adoption from ~10% to ~30% and cutting operational waste.

Analytics Cost
900

%

Deployed behavioral analytics across 15 teams in 3 months, reducing implementation costs from $500K to < $50K per team and reducing team friction

Analytics Cost
900

%

Deployed behavioral analytics across 15 teams in 3 months, reducing implementation costs from $500K to < $50K per team and reducing team friction

Operational Drag
250

%

Reduced enterprise approval timelines from 8 → 6 weeks by making approval dependencies, ownership, and operational risks visible earlier in the process.

Operational Drag
250

%

Reduced enterprise approval timelines from 8 → 6 weeks by making approval dependencies, ownership, and operational risks visible earlier in the process.

Enterprise AI adoption
600

%

Shifted org from no-AI policy to governed rollout in 60 days, creating 350 SMEs and scaling org LLM adoption to 60% in 8 mo.

Enterprise AI adoption
600

%

Shifted org from no-AI policy to governed rollout in 60 days, creating 350 SMEs and scaling org LLM adoption to 60% in 8 mo.

Review

What I would have done differently

In hindsight, I should have started with a lightweight behavioral analytics pilot in year one using our internal non-scalable event tracker instead of waiting until year two to prove the value through a mature analytics platform.

That decision probably cost 6 months.

An earlier pilot would have shown teams almost immediately how differently product decisions looked with even limited user insights while also exposing the limitations of our internal tooling through direct experience.

Instead, I spent almost 6 months convincing leaders using projected savings, executive meetups, and wading through legal, privacy, and architecture committees before teams had enough firsthand exposure to feel the operational problems themselves.

Review

What I would have done differently

In hindsight, I should have started with a lightweight behavioral analytics pilot in year one using our internal non-scalable event tracker instead of waiting until year two to prove the value through a mature analytics platform.

That decision probably cost 6 months.

An earlier pilot would have shown teams almost immediately how differently product decisions looked with even limited user insights while also exposing the limitations of our internal tooling through direct experience.

Instead, I spent almost 6 months convincing leaders using projected savings, executive meetups, and wading through legal, privacy, and architecture committees before teams had enough firsthand exposure to feel the operational problems themselves.

Founding the world's largest B2B marketplace

Amazon

•

5 min

Founding the world's largest B2B marketplace

Amazon

•

5 min

Safeguarding 162M investors by revealing risks.

FINRA

•

6 min

Safeguarding 162M investors by revealing risks.

FINRA

•

6 min

Safeguarding 162M investors by revealing risks.

FINRA

•

6 min

Accelerating global COVID-19 research with AI

IQVIA

•

7 min

Accelerating global COVID-19 research with AI

IQVIA

•

7 min

© 2026 James Ricks
© 2026 James Ricks