Open Source in Finance Forum Toronto 2026

This panel aims to strengthen the case for open source contribution from financial services by moving the conversation from belief to evidence.

By grounding open source contribution in concrete ROI data and real-world financial services experience, the panel equips organizations to make more confident, sustainable decisions about how—and why—they engage with open source. Attendees will gain shared language and metrics they can use internally to justify contribution, align stakeholders across engineering, risk, and leadership, and shift effort away from costly private forks toward healthier collaboration models.

For the ecosystem as a whole, this means:

- More upstream contributions instead of fragmented private forks
- Faster feedback loops between users and maintainers, especially on security and stability
- Stronger, better-resourced projects with long-term institutional support
- Increased participation from regulated industries that historically struggle to justify contribution

By demystifying ROI and showing how contribution directly benefits both firms and communities, this session helps remove one of the biggest barriers to enterprise open source sustainability.

This session gives the ecosystem a concrete, shared reference for what secure, interoperable FDC3 looks like in practice.

By combining live demos with real-world use cases from BlackRock and RBC, the talk moves beyond specification theory to show how FDC3 Security & Identity can be implemented and used today. Vendors, platform teams, and end-user firms will leave with a clearer understanding of expected patterns, integration points, and interoperability guarantees as the spec reaches release-candidate maturity.

This accelerates adoption, reduces fragmentation, and increases confidence that open desktop standards can meet enterprise security requirements.

Canada ranks fifth globally in AI investment, boasts 3X the number of patent filings vs the rest of the G7, features an abundance of world-class talent, and best-in-class AI research institutes such as Mila in Montreal and the Vector Institute in Toronto. Yet, Canada lags in its ability to commercialize AI opportunities in this domain, and lags global counterparts in AI and open source collaboration. How can Canadian companies better leverage global AI and open source ecosystems to turn their early R&D investments into competitive solutions that compete on the international stage? And what can Canada learn from other countries about open source opportunities and ROI in the face of trade uncertainties? This session reveals new research led by the LF Research and Meta, exploring Canada's open source AI opportunities - and current challenges.

The gap between AI research and production deployment in financial services is not primarily a technical problem - it is a structural one. Drawing on Vector Institute's co-development experience across 500+ use cases and more than 200 organizations, this session explores how a collaborative approach can compress that gap, under what conditions transparency becomes a competitive asset, and where risks lie, from cybersecurity exposure to the governance challenges that open models surface rather than create.

Provisioning compute capacity in the cloud should be as straightforward as defining what you need, not where and how to get it. Yet HPC engineers face inconsistent, provider-specific APIs, incompatible provisioning models, and duplicated integration logic across schedulers and clouds. Open Resource Broker (ORB) solves this with a unified, open-source API and abstraction layer for provisioning cloud capacity anywhere.

ORB integrates seamlessly with IBM Spectrum Symphony HostFactory to standardize capacity requests, tracking, and release. Its modular design supports additional schedulers and multiple cloud providers beyond the initial AWS implementation. ORB supports CLI, REST, SDK and MCP APIs for consistent scaling across diverse HPC environments.

We'll demonstrate ORB's architecture, end-to-end provisioning, and resiliency patterns including retries, idempotent operations, and failure recovery. We'll also cover extensibility for new schedulers and cloud APIs.

Built for large-scale financial HPC grids, ORB is now donated to FINOS under Apache 2.0 for open governance. Attendees will learn proven strategies to make HPC capacity management more portable, automated, and sustainable.

FINOS AIGF provides a practical, use-case-led way to identify the risk profile of GenAI/agentic systems and select mitigations that are defensible for financial services. In parallel, the FINOS AI Reference Architecture Library is explicitly building threat-modelled architectures whose risks and mitigations are drawn from the AIGF catalogue, so teams can design, deploy, and operate within agreed risk tolerances.

This session proposes (and demos) an AIGF-aligned reference implementation: a composable, GitOps-delivered blueprint that turns FINOS AI reference architecture diagrams into deployable, secure platform patterns. Using k0rdent AI for consistent multi-cluster AI platform provisioning and Flux CD for policy-driven delivery and drift control, we operationalize the FINOS Multi-Agent Reference Architecture threat model (threats mapped to controls across layers such as gateway, MCP, evaluation, and observability). The result is a reusable stack that can be instantiated across cloud and bare metal, and that produces measurable assurance evidence aligned to Use Case → Risks → Metrics.

(1) Intro to Fluxnova
- How does it fit and what business problems can it solve?
- 2-3 Financial Services examples
- What tooling is available?
- Monitoring
- Tasklist
- Admin
- Briefly: Engine & installation/architectural options
(2) Demo w/ AI Governance Framework & guardrails using a common Financial Services use case
- General overview of thought process: https://www.linkedin.com/posts/ryan-johnston-823124_one-thing-became-very-clear-in-last-week-activity-7424543321907302401-RgG4
(3) Performance
- Brief overview of performance with numbers from a demo environment
- We've run tests with the Camunda 7 codebase that have demonstrated performance that is blazingly fast. We're going to run a specific test with the most current version of Fluxnova prior to OSFF Toronto and will share those results.
- High-level numbers from a previous performance test that we ran on the code base with a production-ready architecture at AWS: https://summit58.com/camunda-platform-performance-at-scale/
- General comparison of performance to other architectural approaches & generic alternatives
- We're *not* trying to compare performance to any other platform.

CALM, the Common Architecture Language Model, is a way for architects to define system architectures as code, allowing true integration and controls within the SDLC. In this session, learn more about the core principles of CALM, and how multiple financial institutions are coming together to adopt and define its future.

Introduction to the Common Domain Model (CDM), the open source, standardized, machine-executable model for the financial industry. CDM promotes transparency, efficiency, and interoperability between market participants. This overview session will touch on the basics, scope, history, live use cases (e.g. collateral, regulatory reporting), and how it could benefit your organization.

Data is foundational to digital businesses and critical for training accurate AI models; poor quality or copyrighted data introduces major risks and liabilities. Beyond IT, reliable, enriched business data—including company information, legal entities, and ownership structures—is essential for competitive advantage and managing risk in sectors like financial services. Currently, this vital data is fragmented, inconsistently defined, and costly to reconcile. This expert panel will explore the rapidly changing open data opportunity and what it means for financial services and other industries. The discussion will center on the benefits of an open data consortium, which employs shared governance and open standards to collaboratively maintain datasets for the benefit of all users and AI models. Success requires a structured global entity graph, sourced from verified public records, to underpin critical workflows like KYB/KYC, AML, risk management, and AI. Panelists will detail how to build and sustain this asset, addressing data definitions, governance, and the balance between openness, privacy, and commercial involvement. This is an opportunity for financial institutions and open source leaders to engage in shaping shared data infrastructure.