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# The New Financial Stack: AI, Agents and Trust

Finance is shifting to machine-to-machine commerce powered by autonomous AI agents. How can leadership balance these probabilistic models with the strict deterministic execution required for absolute trust?

- **Speakers:** [Annabella Bassler](https://www.wearedevelopers.com/@annabella-bassler), [Daniele Tonella](https://www.wearedevelopers.com/@daniele-tonella), [Peter Bakenecker](https://www.wearedevelopers.com/@peter-bakenecker), [Klaus Fiala](https://www.wearedevelopers.com/@klaus-fiala-2)
- **Event:** World Congress 2026 Europe
- **Published:** July 9, 2026
- **Duration:** 28:29
- **URL:** https://www.wearedevelopers.com/videos/100002-the-new-financial-stack-ai-agents-and-trust

## Summary

The financial sector is undergoing a paradigm shift from human-initiated transactions to machine-to-machine commerce powered by agentic AI. Because banking and payments are fundamentally built on trust, organizations must rigorously balance the probabilistic nature of large language models with deterministic execution. While AI offers unprecedented capabilities in coding, fraud detection, and operational efficiency, institutions remain cautious about granting autonomous agents direct access to production environments without stringent design-phase guardrails.

To prevent emerging technology from becoming an unmanageable shadow IT problem—where local agents escalate like "Excel on steroids" without verifiable data lineage—leaders are enforcing visible governance frameworks to channel organizational energy safely. Evaluating the return on investment for these AI initiatives requires moving beyond mere cost reduction to focus on generating net-new revenues and elevating the end-user experience. Actualizing these benefits also demands mitigating unconscious bias at scale. Deploying real-time LLM assistants directly into operational workflows can successfully flag stereotypes and guide human judgment without overriding operational autonomy.

Regulatory directives, such as the EU AI Act, are essential for long-term sustainability and consumer protection, despite valid industry concerns about geographic fragmentation and compliance complexity. Standardizing rules across differing national jurisdictions remains a massive hurdle to frictionless digital deployment. Ultimately, as AI assumes responsibility for increasingly complex, real-time decision-making, the future of business engineering and finance will necessitate a fundamentally more human-centric leadership approach characterized by courage, empathy, and intellectual curiosity.

**Keywords:** agentic ai, machine-to-machine commerce, financial transaction security, probabilistic ai models, technology guardrails and governance, shadow ai proliferation, technology return on investment, real-time fraud detection, llm unconscious bias mitigation, algorithmic fairness tracking, eu ai act compliance, cross-border digital regulation, data lineage visibility, real-time workflow assistants, human-centric leadership approach

## Chapters

1. **Personal use cases and data privacy boundaries** (01:42) — Where leaders draw the line when interacting with language models in their daily routines.
1. **Transitioning toward autonomous agentic commerce** (05:09) — How machine-to-machine transactions shift the focus away from human verification toward establishing security and agent intent.
1. **Balancing deterministic and probabilistic systems in banking** (07:57) — Why the financial sector keeps autonomous models out of production while leveraging them in design and coding.
1. **Calculating the business value of emerging technologies** (09:35) — A framework for evaluating initiatives based on new revenues, user experience improvements, and cost reduction.
1. **Enhancing security and real-time fraud prevention** (12:02) — Optimizing the balance between seamless consumer experiences and rigorous transaction verification.
1. **Managing end-user computing risks and shadow models** (15:20) — How clear governance mechanisms prevent unmonitored deployment and ensure initiatives result in traceable benefits.
1. **Mitigating unconscious bias with targeted workflow assistants** (18:53) — Developing specialized integrations that analyze text in real-time to alert users of potential stereotypes.
1. **Learning agility from media and governance from finance** (20:57) — Blending rapid adaptation paradigms with rigorous compliance standards to sustainably scale modern architectures.
1. **The impact of regulatory friction on innovation speed** (22:19) — Evaluating how differing interpretations of compliance frameworks introduce complexities for multinational deployment strategies.
1. **Required leadership skills for modern technology transitions** (27:22) — Prioritizing courage, human empathy, and cross-generational curiosity to navigate shifting technical paradigms.

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