Patent-Pending Explainable AI for Financial Institutions

Transparent AI Tools for Banking Decisions Under Constraint

CompAIance is developing a family of patent-pending fintech solutions for regulated financial institutions across pricing optimization, liquidity analytics, regulatory automation, and stress/scenario analysis.

We are currently conducting structured discovery conversations and private simulated-data demonstrations with banking, fintech, risk, compliance, treasury, and pricing professionals.

Validation in Progress

CompAIance is currently moving from invention to market validation.

We are seeking expert feedback from professionals who understand real-world banking workflows, including pricing, liquidity, regulatory reporting, compliance, treasury, risk management, stress testing, fintech product, and financial-services innovation.

We are not seeking confidential information or immediate commercial commitments. Our goal is to understand where current workflows create the most friction, where existing tools fall short, and which problem areas should become the initial commercialization focus.

Help Validate or Share Expert Feedback on Explainable AI for Banking Workflows

About CompAIance

CompAIance is an early-stage fintech venture developing patent-pending explainable AI tools for regulated financial institutions.

Our work focuses on financial decision workflows where transparency, auditability, and economic rigor are essential: pricing optimization, liquidity analytics, regulatory automation, and stress/scenario analysis.

Founded in 2024, CompAIance combines experience in regulated technology environments, finance, machine learning research, and fintech venture development.

CompAIance is developing a patent-pending fintech solution family supported by four filed U.S. patent applications covering explainable AI methodologies for financial reporting, rate optimization, liquidity analytics, and stress/scenario analysis.

One of our solutions, RegAutomate™, was selected as a 2025 UW CoMotion × Curinos FinTech Incubator finalist — formally, a finalist for the 2025–2026 Curinos FinTech Incubator powered by UW CoMotion — providing early external validation and reinforcing the importance of market traction, workflow feedback, and institutional trust.

Patent-Pending Fintech Solution Family

CompAIance is developing a patent-pending fintech solution family — four filed U.S. patent applications — spanning four explainable AI solutions for regulated financial institutions. Each solution addresses a distinct banking decision workflow while sharing a common emphasis on transparency, auditability, and defensible outputs.

RateOptix™ — Pricing Optimization and Decision Intelligence

RateOptix is designed to help financial institutions evaluate pricing decisions using competitive market inputs, internal profitability constraints, fairness considerations, and explainable recommendation outputs.

Relevant for: pricing, deposit strategy, product management, treasury, retail banking, analytics.

Current validation focus: pricing decision workflows, competitive response, explainability, and adoption barriers.

RegAutomate™ — Explainable AI for Banking Regulatory Filings

RegAutomate is designed to transform financial institution data into regulator-ready reporting outputs with traceable audit logs and explainable mappings.

Relevant for: regulatory reporting, compliance, finance, audit, data governance, RegTech.

Current validation focus: reporting workflow friction, auditability, explainability, and data-readiness requirements.

Early prototype work using simulated data is being used to evaluate potential improvements in workflow efficiency, mapping consistency, explainability, and audit-trail generation. Production performance would require additional validation using institution-specific workflows, data environments, and governance requirements.

LiquidityPulse™ — Dynamic Liquidity Risk Analytics

LiquidityPulse is designed to support liquidity monitoring, deposit-flow analysis, funding-source visibility, and early-warning decision support.

Relevant for: treasury, liquidity risk, ALM, bank CFO teams, risk management.

Current validation focus: liquidity visibility, early-warning indicators, data availability, and actionability.

StressSense™ — Stress Testing and Scenario Analysis

StressSense is designed to support transparent stress-testing workflows, scenario provenance, risk narratives, and explainable outputs for internal and external stakeholders.

Relevant for: risk management, stress testing, scenario planning, board reporting, regulatory review.

Current validation focus: scenario realism, assumption transparency, reporting burden, and decision usefulness.

What We Are Learning

Financial institutions face increasing pressure to adopt AI-enabled tools while maintaining transparency, governance, and trust.

Our current validation work is focused on answering four questions:

Which banking workflows create the greatest friction today?
Where do current tools fail to provide sufficient transparency or actionability?
Which use cases can be demonstrated safely using simulated or non-sensitive data?
Which CompAIance solution should become the initial lead solution for commercialization focus?

Feedback from banking and fintech professionals will help determine product prioritization, workflow design, and future pilot readiness.

Why Explainability Matters

AI adoption in financial institutions requires more than model performance. Outputs must be understandable, traceable, and defensible.

CompAIance is designed around five principles:

Transparency: Recommendations should explain the data, assumptions, and constraints behind the output.

Auditability: Workflows should preserve traceable evidence for governance, review, and oversight.

Decision Support: AI should augment human judgment rather than replace accountable decision-making.

Regulatory Readiness: Systems should be designed with financial-institution expectations for model governance, auditability, documentation, and human oversight in mind, rather than toward any single named mandate.

Modular Deployment: Institutions should be able to evaluate focused use cases before broader adoption.

Leadership Team

Douglas Jamieson — Founder / Co-Founder

Douglas brings over 30 years of experience in regulated technology environments, management, engineering, business transformation, and finance. His background includes leadership and project execution across Fortune 500 technology organizations and an MBA in finance.

Jack Jamieson — Co-Founder / Student Founder

Jack is an incoming University of Washington student interested in mathematical economics, entrepreneurship, and data-driven financial decision systems. He contributes to machine learning research, prototype development, patent portfolio support, and market validation across CompAIance’s fintech solution portfolio.

Jack is currently helping lead structured discovery conversations and simulated-data prototype demonstrations with banking and fintech professionals.

Request a Demo or Discovery Conversation

We are currently conducting structured validation conversations with banking, fintech, risk, compliance, treasury, pricing, and financial-services professionals.

Please use the contact form if you are open to providing expert feedback, participating in a short discovery conversation, helping validate, or reviewing a private simulated-data demonstration.

We do not request confidential information. Demonstrations use simulated or non-sensitive data.