R/LRyan Law

Ryan Law

Turning complex data into intelligent decisions.

Vice President, Client Intelligence · RBC Capital Markets

Capital MarketsData & AnalyticsAI Innovation

Explore my work Discover L//IOS
Live demosynthetic series · 64 pts
Trend
-0.2%
Outlier
z = 4.8
Next step
Review #45
less manual reporting
95%by automating and moving Excel reports into Tableau
fewer KYC errors
97%with bots for client outreach and document uploads
clients
20,000+kept accurate through a global KYC refresh
validation rules
300+in a data quality framework supporting control processes
About

I’ve spent my career where markets meet data.

I'm Ryan Law, Vice President of Client Intelligence at RBC Capital Markets, where I've spent eleven years turning markets data into decisions. I build analytical systems, automate complex workflows, and explore how AI can change the way we understand information.

Banking taught me how markets businesses actually run: the questions leaders ask, the pressure on the numbers, and how much depends on data being right.

From my first role I looked for the repetitive work that could be automated. Today I design reporting and analytical systems for Capital Markets, automate what doesn’t need a person, and build the validation that makes the output trustworthy.

After years of building reporting, dashboards and validation frameworks, I kept coming back to one question:

What if software could do more than display information?
What if it could understand the data, surface what matters, and help people decide? L//IOS is my exploration of that. See L//IOS
Experience

Where the business meets the build.

I bridge business requirements and technical execution: understanding what a markets team needs, then building and validating the systems that deliver it.

Dec 2025 – Present

Vice President, Client Intelligence

RBC Capital Markets

Leads reporting, data quality and business intelligence for Capital Markets, turning complex business requirements into practical solutions.

  • Manage an offshore analytics and reporting team: work allocation, deliverables and capability building
  • Oversee validation frameworks, data integrity controls and reconciliations
  • Drive automation, and align priorities with business leaders, technology partners and teams across regions
Impact

Reliable data, less manual work, clearer answers.

Selected work from Capital Markets, described in general terms. No client, trade or proprietary detail is shown.

A validation framework people can trust

Checked before it reaches a report, across roughly 100–150K trade records.
Problem
Large trade datasets fed downstream reporting, and errors were found late, by the people reading the reports.
My contribution
Designed and built a rules-based validation framework that checks the data before it reaches reporting.
Approach
Python-driven rules with clear exception handling, so each break is visible, owned and resolved.
Impact
300+ rules applied across roughly 100–150K trade records, supporting the control process.
PythonValidationControls
The pattern behind it · general, not employer-specific
  1. Ingestsource feeds
  2. Reconcilematch & align
  3. Validaterules engine
  4. Resolveexceptions
  5. Reportcertified output
Expertise

Markets knowledge, data discipline, and the tools to build.

Markets & Business

  • Capital MarketsEstablished
  • Client IntelligenceEstablished
  • Business IntelligenceEstablished
  • Stakeholder CollaborationEstablished
  • Operational EfficiencyEstablished

Analytics & Data

  • TableauEstablished
  • PythonEstablished
  • ExcelEstablished
  • SQLEstablished
  • Data Quality & ValidationEstablished
  • Data VisualizationEstablished

Engineering & Automation

  • Workflow AutomationEstablished
  • Data IntegrationEstablished
  • Process OptimizationEstablished
  • Application DevelopmentBuilding
  • Analytical SystemsBuilding

Artificial Intelligence

  • AI-Assisted DevelopmentBuilding
  • LLM ApplicationsBuilding
  • Intelligent AnalyticsBuilding
  • Natural-Language InterfacesExploring
  • Agentic WorkflowsExploring
EstablishedProfessional depthBuildingActively applyingExploringLearning and experimenting
Independent project · Flagship

L//IOS: An Operating System for Insight.

An Operating System for Insight.

Three applications built on one idea: software that understands the data, says what matters, and shows its working.

The future of analytics isn’t more dashboards. It’s systems that understand the data and tell us what matters.
The idea behind L//IOS
01 · Data intelligence · autonomous analysisWorking

L//IOS Analyst

Give it files it has never seen. It works out the structure, connects the datasets safely, checks quality, builds the dashboard and investigates what changed. Every number traces back to source rows.

Drop data → Initialize → Understand → Dashboard → Insights → Investigate

  • 166,286 synthetic trades, 5 files, 9 data regions understood in under 25 seconds
  • Engine totals checked against an independent recomputation from the raw workbook
  • Measured on a 72 MB workbook: 831,430 rows ready to explore in about 87 s
See it in depth Try it in miniature
L//IOS Analyst dashboard showing KPIs, revenue by month, and a ranked list of findings
Real screenshot · L//IOS Analyst on its synthetic “Global Markets” sample (fictional firms)
02 · MarketsWorking

L//IOS MarketsMarkets and research intelligence

L//IOS semiconductors workspace: year-to-date performance, leaders and laggards, with DEMO DATA badges
Real screenshot · L//IOS in demo mode (the app labels every value DEMO DATA)

Ask a question and the question builds the workspace: market data, deterministic analytics, coverage, internet-attention signals, evidence with labels, and research that remembers what changed.

Explore Markets
03 · HealthIn development

L//IOS HealthPersonal health and training intelligence

L//IOS Mobile Today screen with readiness rings and the next session, labelled demo data
Real screen · rendered by the app’s own UI tests with sample data

A native Android app that reads Health Connect, interprets messy workout notes, tracks strength, running and body composition, and tells you what changed and what to do next, labelling every value as measured, calculated or interpreted.

Explore Health
L//IOSAnalystCollectValidateUnderstandExplainAct
//One loop, three domains · concept

Each app runs the same five steps on a different kind of data.

Open the L//IOS project page Try the Intelligence Lab

L//IOS is an independent personal technology project and is not affiliated with or endorsed by RBC Capital Markets.

Intelligence Lab

Beyond the dashboard, in miniature.

A hands-on version of L//IOS Analyst. Give it three files, press “Watch it run”, or try your own CSV, and see it work out the data, check it, build the dashboard and investigate what changed. Every number goes back to a row.

Loading the Intelligence Lab…
How I work

Five principles.

  • Clarity over complexity.Technology should make complex information easier to understand.
  • Intelligence over information.Good analytics explains what matters instead of simply displaying data.
  • Automation over repetition.Repetitive work should be redesigned wherever practical.
  • Trust through validation.Reliable data and transparent calculations come first.
  • Continuous evolution.New technology is a chance to rethink how the work gets done.
Projects

The work, and the path to it.

L//IOS leads. The earlier builds stay as a record of how I learned: the first apps, charts and sites I made.

Contact

Let’s build something meaningful.

Whether it’s markets data, analytics, automation or applied AI, I’m always glad to compare notes.

LinkedInRyan Law GitHublawryan Emailryanlaw@live.com