Services
Three stages. One continuous engagement.
Maclear organizes its work around where your institution is in its data and AI journey. Each stage builds on the last — and you can engage at whichever point fits your current needs.
Stage 1
Assess & Prioritize
Before building anything, you need to understand where you stand. Maclear’s assessment work cuts through complexity to surface what actually matters for your institution — and what to do about it first.
Data & AI Self-Assessment
Structured evaluation of your current data and AI maturity. Covers infrastructure, governance, talent, and use-case readiness. Produces a clear picture of where you are and what’s holding you back.
AI Readiness Review
Deep dive into organizational readiness for AI adoption. Examines technical prerequisites, governance gaps, risk exposure, and capability constraints relevant to your operating environment.
Data Strategy Development
A practical data strategy built for your institution’s scale and constraints. Defines priorities, target capabilities, and a realistic path forward — not a theoretical framework that gathers dust.
AI Use Case Prioritization
Evaluate potential AI initiatives against value, feasibility, risk, and data requirements. Produces a prioritized use-case roadmap that reflects your real capabilities and business objectives.
Vendor & Technology Assessment
Independent evaluation of AI and data vendors, platforms, and tools. Assess fit, risk, and total cost of ownership — without vendor pressure or pre-existing commercial relationships.
Stage 2
Build & Implement
Turning strategy into working solutions. Maclear designs and builds data infrastructure, analytics systems, and AI capabilities that are production-ready and compliant from the first deployment.
Data Engineering & Infrastructure
Build and modernize data pipelines, warehouses, and integration layers. Reliable, maintainable infrastructure that supports downstream analytics and AI without creating technical debt.
Machine Learning & AI Development
End-to-end model development from problem definition through production deployment. Covers feature engineering, model selection, validation, and handoff — with documentation suitable for audit and regulatory review.
Analytics & Reporting Systems
Design and build reporting platforms, dashboards, and self-service analytics tools that give decision-makers reliable insight without depending on data-team availability for every query.
Generative AI System Design
Design enterprise-grade GenAI systems with retrieval-augmented generation, prompt engineering, and integration architecture. Built with appropriate controls for regulated environments.
AML & Compliance Analytics
Specialized analytics for financial crime detection and compliance monitoring. Transaction pattern analysis, network analytics, and control effectiveness assessment for AML, fraud, and regulatory programs.
Stage 3
Govern & Sustain
Deployment is not the finish line. Maclear’s governance and sustainment work keeps solutions reliable, controlled, and useful over the long term — while reducing institutional risk and satisfying regulator expectations.
Model Risk Management
Implement model risk management practices aligned with SR 11-7 and OSFI expectations. Covers model inventory, risk tiering, ongoing monitoring, and documentation for regulatory examination.
Independent Model Validation
Third-party validation of models and AI systems. Covers conceptual soundness, data quality, implementation correctness, and ongoing monitoring — delivered with audit-ready documentation.
AI Governance Framework Design
Design and implement AI governance frameworks that align with your risk appetite, regulatory obligations, and organizational structure. Covers policies, accountability, oversight mechanisms, and escalation paths.
Ongoing Monitoring & Support
Structured programs for model and system monitoring, performance review, and proactive maintenance. Catch drift, degradation, and emerging risks before they become operational problems.
Regulatory Examination Support
Preparation and support for regulatory reviews of data and AI systems. Documentation organization, examiner-ready responses, gap remediation, and post-examination follow-through.
Maclear Academy
Build internal capability, not just external dependency
Maclear Academy delivers tailored training programs that help your teams understand, use, and govern data and AI systems — so the value doesn’t walk out the door when the engagement ends.
Data Literacy for Financial Institutions
Foundation-level training in data concepts, interpretation, and critical thinking. Designed for risk, compliance, finance, and operations teams who work with data but don’t build models.
AI Risk & Governance for Board and Executive Teams
Strategic-level briefings on AI risk, regulatory expectations, and governance responsibilities. Helps leadership ask the right questions and exercise meaningful oversight of AI programs.
Practitioner Training & Upskilling
Hands-on technical training for data analysts, model validators, and risk professionals. Covers applied ML, model risk, governance tooling, and domain-specific use cases.
Private Client Service
Dedicated, confidential support for institutions that need it most
For institutions facing sensitive challenges — an examination finding, a model failure, a board-level concern, or a strategic decision with high regulatory stakes — Maclear offers a private, retainer-based advisory relationship. Founder-led, discreet, and focused exclusively on your outcomes.
Get Started
Not sure which stage fits your situation?
A short conversation is usually enough to identify the right entry point. Maclear offers a complimentary 30-minute discovery call to any institution exploring its options.