In today’s rapidly evolving financial landscape, digital modernization is no longer optional for credit unions — it is essential for long-term competitiveness and member satisfaction. As expectations shift toward seamless digital experiences and competitors accelerate technological adoption, Canadian credit unions face mounting pressure to modernize operations, enhance digital services delivery, and improve internal efficiency.

However, the capital investment required to implement these changes can be significant — particularly for small and mid-sized credit unions. Budget constraints, legacy systems, and risk-averse environments can slow innovation, even when the business case is clear.

Recognizing the economic importance of financial institutions, the federal and provincial governments have introduced a wide range of funding programs to support innovation and digital transformation. Many of these opportunities are underutilized in the credit union sector — not due to lack of relevance, but often due to awareness gaps, application complexity, or resource limitations. 

This white paper outlines how Canadian credit unions can strategically access government funding to accelerate digital modernization. Specifically, it explores three core areas:

1. Funding pathways for digital transformation initiatives, with a focus on intelligent automation, AI technologies, and Open Banking implementation
2. Partnership opportunities to access broader digital modernization funding, particularly through academic collaborations
3. Scientific Research and Experimental Development (SR&ED) tax incentives for technology development

By taking a structured approach to funding, credit unions can stretch their budgets, support more ambitious transformation goals, and better serve their members in an increasingly digital economy. These strategies not only unlock cost savings, but also position credit unions to remain relevant, resilient, and responsive to evolving market needs.

The Canadian government has identified digital innovation in financial services as a strategic growth sector and has introduced several dedicated funding streams to support transformation initiatives. Credit unions can leverage these programs to advance digital modernization efforts while optimizing capital investments.

Government funding programs for transformative technologies

• Scale AI Supercluster: With $230 million in federal investment, Scale AI supports business-led projects that integrate AI into supply chains and business processes. Credit unions can apply for co-investment funding of up to 50% of eligible project costs, though projects must demonstrate connection to supply chains.
• AI Commercialization Program: Through the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP), this initiative offers funding to small and medium-sized businesses implementing or commercializing AI solutions. Smaller credit unions may qualify based on employee size and project scope.
• Strategic Innovation Fund (SIF): Supports transformative innovation projects typically exceeding $10 million in total costs. Credit unions undertaking large-scale digital infrastructure upgrades — such as Open Banking API ecosystems or enterprise AI platforms — may qualify for repayable or non-repayable contributions.
• Digital Technology Supercluster: This B.C. based innovation cluster funds collaborative technology projects, including those in financial services. Credit unions can participate as consortium members on projects related to digital transformation.
• Cyber Security Innovation Network (CSIN): While CSIN primarily funds broader cyber security research networks, participating in CSIN-related initiatives can give credit unions early access to next-generation security solutions and best practices.

Eligible digital projects under government programs

Credit unions may align eligible digital initiatives with government funding priorities, including:

AI-focused projects

• Intelligent process automation: Automating back-office operations such as loan processing, KYC/AML compliance, and credit decisioning using AI tools. 
• Predictive analytics models: Developing predictive systems for fraud detection, credit risk assessment, or member churn forecasting.
• Natural language processing: Deploying AI-driven chatbots, virtual assistants, or document processing systems to enhance member engagement and service efficiency.

• Computer vision application: Implementing automated ID verification, mobile cheque deposit validation, and branch analytics technologies.

Open Banking and data security projects

• Secure API infrastructure: Building standardized APIs for controlled data third-party data sharing, a critical component of Open Banking readiness.
• Consent management frameworks: Designing systems that allow members to manage financial data access permissions easily and securely.
• Third-party integration platforms: Establishing secure gateways for fintech partnerships and service integrations.
• Enhanced cyber security protocols: Advancing internal capabilities to protect sensitive member data in increasingly interconnected systems.

Project types and optimal funding sources

Project Type	Potential Funding Source	Why This Source Is Appropriate	Typical Funding Structure
AI-driven credit risk models	Scale AI	Directly aligns with AI adoption priorities, and projects must demonstrate a connection to supply chains or operations.	50% co-investment, typically up to $2M per project
API development for future data sharing	Strategic Innovation Fund	SIF supports forward-looking infrastructure investments in priority sectors	Combination of repayable and non-repayable contributions
Blockchain identity verification	Digital Technology Supercluster	Supports consortia approaches to digital identity solutions	Collaborative funding with other institutions, typically 25-50% of costs
Regional digital banking platform	Regional Development Agencies (ACOA, CED, FedDev, FedNor, PrairiesCan, PacifiCan)	Projects with geographic impact align with regional economic development mandates	Combination of repayable and non-repayable contributions
Comprehensive Data Analytics Architecture	Strategic Innovation Fund	Larger-scale projects that transform multiple business units benefit from SIF’s substantial support	Multi-year funding with milestone-based disbursements
Cyber security enhancement	NRC IRAP (for smaller credit unions)	Technical innovation in data protection aligns with program’s R&D mandate	Project-based funding with technical advisory support

Application requirements and success factors

Successful government funding applications typically demonstrate:

1. Clear business impact: Quantifiable improvements in operational efficiency, member experience, or growth potential.
2. Innovation and advancement: Moving beyond routine technology adoptions into novel applications or methods.
3. Collaborative partnerships: Inclusion of technology partners, academic collaborators, or other credit unions.
4. Alignment with strategic government priorities: Advancing financial inclusion, supporting rural service access, promoting responsible AI use, or enhancing cyber security resilience.
5. Demonstrated implementation capacity: Internal resources, project management structures, and mitigation to support successful execution.

Case studies indicate that credit unions with dedicated innovation teams and established technology governance frameworks achieve higher success rates in securing government funding.

Emerging technologies and funding pathways

Beyond AI, several emerging technologies present new modernization opportunities for credit unions, including blockchain and cyber security.

• Blockchain and distributed ledger technology (DLT): The Canadian government has allocated funding for blockchain initiatives through the Innovation, Science and Economic Development Canada’s Digital Technology Supercluster.
• Cyber security enhancements: The Cyber Security Innovation Network provides indirect support for advanced security solutions through its research networks.

Partnering with universities for access to funding

Academic partnerships unlock additional funding streams while also providing access to specialized research expertise. Credit unions can pursue university partnerships through several approaches:

1. Identify relevant research groups: Research departments focusing on fintech, cyber security, data science, or business transformation are natural partners for credit unions. Start by identifying faculty members whose research interests align with your digital modernization priorities.
2. Develop a concrete problem statement: Universities respond best to well-defined research questions rather than general technology interests. Frame your digital challenges as research problems that could interest academic partners.
3. Start small: Consider beginning with student capstone projects, internships, or limited consulting engagements before committing to larger research partnerships.
4. Leverage existing networks: Industry associations like the Canadian Credit Union Association can facilitate introductions to academic institutions with successful track records in financial sector partnerships. The Center for Cooperative Studies at the University of Saskatchewan is one example of such an institution that has done research and issued reports specific to credit unions.
5. Attend academic conferences: Participating in relevant academic conferences provides opportunities to meet researchers and learn about cutting-edge developments in relevant fields.

Structuring IP ownership in university partnerships

Intellectual property considerations are critical in university partnerships. Three common approaches include:

1. Joint ownership model: Both the credit union and university share ownership of any IP created during the project. This model works well when both parties contribute significantly to the innovation and plan to use it for different purposes (commercial vs. academic).

Example Structure: A credit union partners with a university on developing a novel fraud detection algorithm. The agreement stipulates that the credit union has exclusive commercial rights to use the technology in financial services, while the university retains rights to publish research findings and use the underlying methods in non-competing industries.

2. License-based model: The university owns the IP but grants the credit union an exclusive license for specific applications. This model often includes royalty payments or other compensation mechanisms.

Example Structure: University researchers develop a new data analytics framework with credit union funding. The university retains IP ownership but grants the credit union an exclusive, perpetual license for implementation in financial services applications, with predefined royalty rates for commercial deployment.

3. Sponsor-owned Model: The credit union fully funds the research and owns all resulting IP, with the university receiving compensation for its research services and retaining limited rights for academic purposes.

Example Structure: A credit union fully funds a specific research project on secure API development for Open Banking. The agreement specifies that the credit union owns all commercial IP, while the university can publish generalized findings (with sensitive details removed) and use the knowledge for teaching purposes.

Key considerations for IP agreements include:

• Clearly defining background IP that each party brings to the collaboration
• Specifying rights for future improvements or derivatives of the technology
• Establishing publication protocols that balance academic interests with commercial confidentiality
• Addressing student IP rights when students participate in the research

University funding programs

• Mitacs accelerate program: Provides matching funds for research internships, where graduate students and postdoctoral fellows work on credit union digital projects. For every $7,500 a credit union contributes, Mitacs provides matching funds to support a four-to-six-month research internship.
• NSERC Alliance Grants: Fund collaborative R&D projects between businesses and academic researchers, covering up to 66 percent of project costs. For small and medium enterprises, NSERC may contribute up to $1 million over five years, though universities must lead the application process.

Successful partnership approaches

When pursuing university partnerships, credit unions should look for opportunities that align with existing research programs at Canadian universities with strong financial technology or data science programs. To explore potential partnerships, credit unions could contact university research offices directly or work through organizations like Mitacs that facilitate industry-academic collaborations.

The negotiation of IP rights and research parameters should be clearly established at the outset of any partnership through formal research agreements reviewed by legal counsel familiar with academic collaboration structures.

Programs that could be leveraged

Program	Focus Area	Partnership Type	Funding Amount	IP Ownership Consideration
Mitacs accelerate	Applied research with business impact	University researchers	$15,000+ per internship unit	Student IP typically shared between university, company, and student
NSERC Alliance	Collaborative R&D	Academic institutions	$20,000 to $1 million	Negotiable, typically joint ownership with defined field-of-use rights
ACOA’s Regional economic growth through innovation	Innovation in Atlantic provinces	Regional partners including universities	$100,000 to $3 million	Proportional to investment, with government maintaining march-in rights
Regional Innovation Programs through PrairiesCan and PacifiCan	Technology adoption in Western provinces	Industry consortia and academic institutions	Varies by project	Consortium agreement typically required, with rights proportional to contribution

The Scientific Research and Experimental Development (SR&ED) program remains one of Canada’s most significant innovation incentives. Credit unions pursuing digital transformation initiatives — particularly those involving custom development, novel problem-solving, or experimental technology deployment — may qualify for SR&ED credits.

Identifying credit union digital projects that qualify for SR&ED

Three mandatory criteria must be met for SR&ED eligibility:

1. Scientific or technological uncertainty: The project must address challenges that cannot be resolved through standard practice or routine methods. This uncertainty must be fundamental — solvable through structured experimentation or systematic investigation.
2. Scientific or technological advancement: Activities must seek to generate new knowledge or capabilities beyond what is readily available or documented in the industry.
3. Scientific or technological content: Evidence of systematic investigation through experimentation or analysis, including formulation of hypotheses, testing, and analysis of results.

The possibility of failure requirement

A critical but often overlooked requirement for SR&ED eligibility is the genuine possibility of failure. The Canada Revenue Agency (CRA) specifically looks for projects where:

• The solution to the technical problem is not obvious to a competent professional in the field
• There is genuine uncertainty about whether a proposed approach will work
• Experimentation and systematic testing are required to overcome the uncertainty
• The project involves multiple iterative attempts to solve the problem

This requirement distinguishes SR&ED-eligible activities from routine development work. For credit unions, this means that simply implementing a commercial solution or developing according to established methodologies would not qualify. The project must involve genuine experimentation with uncertain outcomes.

Commercial value requirement

SR&ED projects must create or improve materials, devices, products, or processes that have potential commercial value. For credit unions, this means the R&D effort must produce:

• A tangible business asset with potential commercial application
• Technology that addresses a specific business need or market opportunity
• Innovations that could reasonably generate revenue or reduce costs if successful

Importantly, the asset does not need to be successfully commercialized to qualify for SR&ED. The key requirement is that the R&D was undertaken with commercial intent. Even failed projects can qualify if they meet the other criteria.

For credit unions, potential SR&ED-eligible projects include:

• Core banking system development: Custom development or significant customization of core banking platforms represents a prime SR&ED opportunity. The technical challenge often lies in reconciling modern functionality with legacy data structures while maintaining system reliability. Novel IP could emerge from creating proprietary middleware that bridges these systems or developing custom algorithms for transaction processing optimization. The risk element manifests in the uncertainty of whether new architectural approaches can maintain the required performance metrics under real-world transaction volumes. Credit unions that document their systematic testing of different architectural approaches, performance optimization techniques, and integration methods can build strong SR&ED claims.
• API development: Creating proprietary interfaces for third-party integration presents technical uncertainties in ensuring secure, efficient data exchange while maintaining compliance with evolving standards like open banking. Novel IP opportunities exist in developing unique authentication methods, consent management frameworks, or data transformation tools specific to credit union data models. The scientific and technological risk emerges when attempting to solve complex problems like real-time synchronization across disparate systems or maintaining data integrity across multiple integration points. Credit unions could document challenges in areas like handling edge cases, scaling test findings to production environments, and iterative improvements to API security models.
• Data analytics infrastructure: Building custom data lakes, warehouses, and analytics platforms involves significant technical uncertainty in handling diverse financial data sources with varying quality and formats. Novel IP may arise from developing specialized extract, transform, and load (ETL) processes for credit union-specific data models, creating custom data governance frameworks, or designing unique data visualization approaches for financial risk analysis. The risk element centers on whether theoretical data architecture approaches will function effectively with the credit union’s specific data characteristics and volume. Methodical experimentation with data transformation techniques, storage optimization approaches, and query performance enhancements provides strong evidence of systematic investigation required for SR&ED claims.
• Security solutions: Developing novel cyber security approaches for financial data protection involves addressing technology gaps in existing security frameworks. Credit unions can create valuable IP through custom fraud detection algorithms that incorporate member behavioral profiles, unique encryption methods for sensitive financial data, or proprietary authentication systems tailored to multi-channel banking environments. The technological risk stems from uncertainty about whether theoretical security models will effectively counter evolving threat vectors while maintaining member experience and system performance. Document systematic testing of different threat detection approaches, false positive reduction methods, and performance optimization techniques to strengthen SR&ED claims.
• Mobile banking innovations: Creating new mobile banking functionalities or services often involves technical uncertainty in developing features that function reliably across diverse devices while maintaining security and performance. Novel IP may emerge from creating unique user authentication methods (such as custom biometric implementations), developing proprietary transaction verification workflows, or designing specialized algorithms for on-device data processing that enhances security. The technological risk centers on whether theoretical approaches to mobile security, offline functionality, or device-specific optimizations will function as intended at scale. Credit unions could document their experimental approach to testing different implementation methods, performance optimization techniques, and security models to support SR&ED eligibility.

Documentation and evidence requirements for SR&ED claims

To support SR&ED claims, credit unions must maintain comprehensive documentation that demonstrates:

1. Problem definition: Clear articulation of the technical problem and why existing solutions were inadequate
2. Hypothesis development: Documentation of the proposed technical approach and the underlying scientific or technical questions
3. Systematic investigation: Records of the experimental process, including:
   • Test methodologies
   • Control procedures
   • Parameters being tested
   • Measurement criteria
4. Results analysis: Documentation of outcomes, including:
   • Failed approaches and why they didn’t work
   • Successful approaches and their technical significance
   • Knowledge gained through the process
5. Evidence of advancement: Documentation showing how the project advanced knowledge or capabilities beyond what was previously available

The CRA emphasizes concurrent documentation — records created during the project rather than after the fact. This includes technical specifications, design documents, test results, meeting minutes, decision logs, and project management records.

Examples of potential eligibility of technology development activities

Example activity	Potential SR&ED eligibility	Example documentation requirements	Example Novel IP potential	Example risk elements	Example commercial value
Developing custom algorithms for credit scoring	High eligibility	Technical uncertainty documentation, hypothesis testing, iterative development records	Proprietary predictive models incorporating unique member relationship data and local economic factors	Uncertainty whether theoretical mathematical models will achieve sufficient predictive accuracy across diverse member segments	Improved loan decisioning accuracy translating to measurable risk reduction
Adapting open banking APIs for legacy systems	Moderate eligibility	Integration challenges, custom adaptations, test results	Custom middleware for translating between modern API standards and legacy data structures	Technical uncertainty in maintaining data integrity across systems with fundamentally different architectures	Creation of reusable integration framework enabling new service offerings
Building in-house data analytics platform	High eligibility	Architecture designs, technical challenges, development logs	Specialized ETL processes for credit union financial data, custom reporting frameworks	Risk in whether proposed architecture can scale to handle growing data volumes while maintaining query performance	Platform enabling data-driven decision making and personalized member services
Customizing vendor software	Low eligibility (unless substantial modification)	Evidence of modifications beyond configuration	Extensions to core functionality that address credit union-specific workflows	Technological uncertainty in modifying closed systems without compromising stability or vendor support	Enhanced capabilities addressing specific business requirements not met by off-the-shelf solutions
Testing commercial solutions	Not eligible	N/A	Limited IP potential	No technological uncertainty from SR&ED perspective	No SR&ED-eligible commercial value created

The implication of risk and unique IP for eligibility

SR&ED initiatives explicitly target activities with technical risk — projects where the outcome cannot be guaranteed through the application of standard techniques. For credit unions, this means:

• Document technical uncertainty: Maintain detailed records of technical challenges and approaches considered.
• Emphasize experimentation: Track iterations, failures, and pivots in the development process.
• Identify novel elements: Clearly articulate how the project extends beyond implementing existing solutions.

While creating unique intellectual property strengthens SR&ED claims, it is not strictly required. Credit unions can claim SR&ED for adapting existing technologies in novel ways or integrating technologies in previously untested combinations—provided there is genuine technological uncertainty and systematic investigation.

SR&ED Financial benefits and calculation examples

Financial benefits of SR&ED include:

• Canadian-controlled private corporations (CCPCs) can receive up to 35% of eligible expenditures as refundable federal tax credits.
• Other corporations, such as non-CCPCs, may be eligible to receive a 15% non-refundable federal tax credit.
• Provincial incentives, additional tax credits may be available at the provincial level. However, rates and refundability vary by jurisdiction.
• Eligible expenditures typically include salaries, contractor fees, materials, and overhead related to R&D activities.

Need help calculating your SR&ED opportunity? Connect with our team for a tailored assessment based on your specific activities, structure, and location.

Federal programs

• Strategic Innovation Fund (SIF): Supports large-scale, transformative projects across five streams:
  • Stream 1: Research, development and commercialization
  • Stream 2: Business growth and expansion
  • Stream 3: Investment attraction and reinvestment
  • Stream 4: Collaborative technology development and demonstration
  • Stream 5: National innovation ecosystems
• Provincial digital programs: Several provinces have established digital adoption initiatives to fill the gap left by federal programs:
  • Digital Nova Scotia Productivity and Innovation Voucher Program: Offering vouchers for technology consulting and implementation
  • Ontario Digital Main Street Program: Supporting digital transformation for small businesses
  • Alberta Digital Economy Program: Providing grants for digital adoption and workforce development
• Business Development Bank of Canada (BDC) financing: Offers specialized loans for technology adoption and digital transformation projects.

Regional development agency programs

Agency	Regions covered	Notable programs	Funding range
Atlantic Canada Opportunities Agency (ACOA)	Newfoundland and Labrador, New Brunswick, Nova Scotia, PEI	Business Development Program, Atlantic Innovation Fund	$500,000 to $3 million
Canada Economic Development for Quebec Regions (CED)	Quebec	Regional Economic Growth through Innovation	Up to $5 million
Federal Economic Development Agency for Southern Ontario (FedDev Ontario)	Southern Ontario	Business Scale-up and Productivity Program	$500,000 to $10 million
Federal Economic Development Agency for Northern Ontario (FedNor)	Northern Ontario	Regional Growth Through Innovation Fund	$250,000 to $5 million
Western Economic Diversification Canada (WD)	Manitoba, Saskatchewan, Alberta, British Columbia	Business Scale-up and Productivity Program	$250,000 to $5 million
Canadian Northern Economic Development Agency (CanNor)	Yukon, Northwest Territories, Nunavut	Inclusive Diversification and Economic Advancement in the North (IDEANorth)	Up to $3 million

Provincial/Territorial programs

Each province and territory offers additional funding programs that can supplement federal initiatives:

• Ontario: Various innovation programs through Ontario Centre of Innovation
• Quebec: ESSOR Program (though primarily manufacturing-focused)
• British Columbia: Innovate BC programs for tech sector growth
• Alberta: Alberta Innovates programs for technology development
• Other provinces: Various regional innovation programs

Credit unions could consider their geographic footprint when developing a funding strategy, as regional programs often offer more favorable terms for locally-based institutions.

By strategically leveraging these government funding sources, Canadian credit unions can accelerate their digital transformation journey while optimizing their capital allocation. The key to success lies in aligning modernization initiatives with program criteria, building strong partnerships, and developing compelling applications that demonstrate both innovation and economic impact.

Exploring government funding opportunities for digital modernization is an important first step — but turning opportunities into outcomes requires experience, strategy, and a strong application approach.

MNP’s Credit Union team is dedicated to helping credit unions identify funding pathways, assess project eligibility, and maximize innovation investments. Whether your goals involve advancing AI initiatives, strengthening cyber security infrastructure, preparing for Open Banking, or expanding digital member services, our advisors are ready to help.

For more information, visit Credit Unions Involvement or reach out to our team directly. Together, we can help your credit union take the next step toward a stronger digital future.

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AI and Digital transformation

• Scale AI Supercluster
• AI Commercialization Program (NRC IRAP)
• Strategic Innovation Fund (SIF)
• Digital Technology Supercluster
• Cyber Security Innovation Network (CSIN)

Research Partnerships

• Mitacs Accelerate Program
• NSERC Alliance Grants

SR&ED and Tax Incentives

• Scientific Research and Experimental Development (SR&ED)

Regional Development Agencies

• Atlantic Canada Opportunities Agency (ACOA)
• Canada Economic Development for Quebec Regions (CED)
• Federal Economic Development Agency for Southern Ontario (FedDev Ontario)
• Federal Economic Development Agency for Northern Ontario (FedNor)
• Prairies Economic Development Canada (PrairiesCan)
• Pacific Economic Development Canada (PacifiCan)
• Canadian Northern Economic Development Agency (CanNor)

Provincial Innovation Organizations

• Ontario Centre of Innovation
• Quebec ESSOR Program
• Innovate BC
• Alberta Innovates

Case Study Research Resources

• Mitacs Success Stories
• NSERC Alliance Grant Information
• Canadian Credit Union Association Research