BankTech Day 2026: From exploration to execution, the five key issues redefining the banking sector
1. From exploration to execution: industrializing AI Why Alteryx—and why this choice has defined us since 2018 Our presence in three formats
The dominant topic of discussion is no longer "should we invest in AI," but "how do we industrialize the identified AI use cases." This includes model robustness, continuous monitoring, operational governance, integration into business processes, and controlled inference costs.
This shift changes the required skill sets: fewer prompt specialists, more AI architects, ML engineers, and MLOps experts.
It also changes internal governance: executive committees are demanding hard numbers—TCO, ROI per use case, adoption rates, and drift.
The “so what” for your organization
Your 2026 priorities are no longer about "launching a new AI PoC." They are about "choosing 2 to 5 use cases to scale sustainably, with a solid MLOps framework."
2. Data: the foundation and the pain point The partnership in numbersOur takeaways — four strong signals
Three requirements dominate:
Sovereignty — Sovereign LLMs (Mistral) and SecNumCloud hosting to avoid dependency on American hyperscalers.
Governance — Purview, Unity Catalog, and Collibra are becoming standards. The CDO is often reporting directly to the Executive Committee.
Security — DORA, GDPR, and SecNumCloud are reinforcing each other. Running an LLM within a workflow is now a security issue.
The "so what" Sovereignty is becoming a technological exit criterion. Test your LLM providers for SecNumCloud/DORA compliance as early as possible.
3. Compliance by design: integrating compliance from the start Our 5-pillar Alteryx deployment methodologyOur conviction
- The "compliance by design" approach: integrating regulatory requirements by design. Industrialized, end-to-end auditable reporting chains capable of absorbing new regulatory definitions without needing to be rebuilt.
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- The regulator is becoming a stakeholder in the design process—just as GDPR was for personal data.
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- The "so what" Do not wait for the “compliance” phase to integrate requirements. The marginal cost is 15-20% from the start, compared to 200-300% after an audit.
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4. Transformation is also human and organizational Prime Elevate: Alteryx training at scaleThank you
- Reconnect IT and business units — moving past the intermediate layer of “Digital Officers” to empower business teams as direct stakeholders.
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- Restoring an end-to-end vision — a management controller must understand the ERP, the data warehouse, the dashboard, and the AI model.
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- The “so what” Fund business time. A successful project requires 40-60% of business time throughout its duration.
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5. Training as a critical lever A flagship case study: 5 years at a major French bank
Data and AI skills must permeate business functions, rather than remaining siloed among a few experts.
Three recurring themes:
- Acculturating business units to AI
- Upskilling IT teams in Finance (Finance Prime Analytics program with 300+ trained at a major French bank)
- Industrialization of continuous learning paths that are Qualiopi-certified and eligible for OPCO funding
Our perspective at Prime AnalyticsOur commitment to the Alteryx ecosystem
- Our four-step method:
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- 1. Start with business challenges
- 2. Structure your data
- 3. Train your teams
- 4. Activate the right technological levers
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- The challenges facing the banking sector are as much technological as they are human. Combining both is how we build the sovereign bank of tomorrow. Let's talk about it. Let's talk about it.
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