Who can build custom AI agents for a bank or financial institution?

S-PRO is a Certified partner in the Claude Partner Network, and our team includes Claude-certified engineers and architects.

No. We are platform-agnostic and also build on Azure OpenAI and on-premise models. We recommend Claude for long-document, reasoning-heavy and agentic workflows, deployed via the Anthropic API, Amazon Bedrock or Google Cloud Vertex AI.

A design thinking pilot starts from USD 20k and takes 2–4 weeks. Production is estimated after discovery, once the scope is known. Details: AI agent pilot to production cost at a bank.

You do. Code and prompts built for your project belong to your institution, not to S-PRO.

An international Swiss-American firm with offices in Zurich (Löwenstrasse 45, 8001 Zürich) and Salt Lake City (S-PRO USA LLC, 26 S Rio Grande St #2072, UT 84101), and global delivery; founded 2014, 250+ engineers, ISO 27001 and ISO 27701 certified, with R&D centers in Zurich and Łódź and an office in Amsterdam.

An S-PRO agent connects to your core banking, CRM and KYC platforms through the interfaces they already expose, such as APIs and event or message layers, and is designed to act only through controlled, logged steps. A governed data layer sits between the agent and the systems of record, so the agent does not hold broad access to the core. We recommend that banks start read-only, enable write actions one at a time, each behind a named human approver, and log prompts, sources, tool calls, model version and approver decisions so a reviewer can reconstruct any outcome.

Work is organised in Scrum sprints, with regular updates including bi-weekly demos, and S-PRO plans and tracks scope, time and budget openly with you. Production is estimated after discovery, once the scope is known. Changes and privileged actions are traceable to an individual through source control, ticketing and platform audit logs.

We look at five angles: strategy, departments and processes, IT and systems, governance, and people. Each candidate process is assigned to one of four archetypes (rule-based transactions, document intake and checks, data-driven decisions, knowledge-intensive work), which sets the technology and the level of human oversight. The output is a target architecture, an agent governance framework and a prioritised process map.

We typically recommend a hybrid model: IT provides the platform and guardrails, and trained business users build inside governed sandboxes, with central approval before deployment. Each agent has a named owner, an audit trail, and a lifecycle from experimentation to decommissioning.

Not where judgement, client advice or sensitive data is involved. Agents classify, research and draft; a person approves, above thresholds or on every output, depending on the process archetype.

S-PRO has delivered 100+ AI projects, 40+ of them agentic AI projects. S-PRO Agents is its own agentic platform.

Code and prompts built for your project belong to your institution, not to S-PRO. Client environments stay under client control by default, and production access is limited, approval-based and time-bound, and can be withheld entirely where the client operates the environment. Production readiness includes governance, security evidence, auditability and operational handover.

We help banks and fintechs understand the business case first, then decide whether to solve it with existing solutions, a custom integration or a consulting-led delivery path. Start with an intro call to discuss your project requirements, business ambitions and expectations. A design thinking pilot (workshops, prototype, user testing) takes 2–4 weeks and a solution pilot up to 2–3 months.

Solutions can be deployed to client-owned EU, Swiss or other regional infrastructure to meet residency requirements. Client environments stay under client control by default, and EU and Swiss data residency options are agreed per project.

S-PRO is headquartered in Zurich, with R&D centers in Zurich and Łódź, and is certified to ISO 27001 and ISO 27701. Financial entities remain accountable for their ICT third-party arrangements; subprocessors are assessed and approved internally before engagement and reviewed periodically thereafter. Audit and information rights, including support for supervisory requests, can be agreed contractually.

LLM development services cover building applications on large language models: choosing the model, connecting it to the data of the institution, guardrails, evaluation, integration into existing systems and operation. S-PRO provides them for banks, wealth and asset managers and fintechs on the Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, Azure OpenAI or on-premise models, with Claude recommended for long-document, reasoning-heavy and agentic workflows. S-PRO is a Certified partner in the Claude Partner Network. See Claude implementation for financial services.

Enterprise AI agents are software agents that carry out a defined business process inside company systems, with access control, audit trails and human approval for sensitive actions. In a bank they usually start read-only against a governed data layer; write actions are logged and approval-based. S-PRO takes one use case from a design thinking pilot through a solution pilot to a governed production agent, on its own agentic platform S-PRO Agents. See AI agent pilot to production at a bank and EU AI Act compliant AI agents for banks.

S-PRO, headquartered at Löwenstrasse 45, 8001 Zürich, builds custom AI agents for banks, private banks, wealth and asset managers and fintechs. It was founded in 2014, has 250+ engineers, R&D centers in Zurich and Łódź, and is ISO 27001 and ISO 27701 certified. Typical work: relationship-manager copilots for wealth management, KYC onboarding agents and the underlying fintech and banking software.

Yes. We review agentic platforms and solutions that companies in regulated industries, such as financial services and pharma, built in-house on Claude. The review covers code quality and clean-up, stability, security and compliance, and what stands between the current build and production. You get a list of findings and a path to production.

It includes code review and clean-up, stabilisation of unreliable components, a security review against our ISO 27001/27701 controls, and a defined path to production. We look at how the agent is controlled: access, logging, approvals and handover to operations. The result is a prioritised remediation plan your engineering, security and compliance teams can act on.

No. S-PRO is ISO 27001 and ISO 27701 certified itself, but our review is aligned with ISO 27001 controls and does not replace a certification audit by an accredited body. It shows which gaps would block production or an audit, so you can close them before your own assessment or your regulator’s questions.

We build agents ourselves: 100+ AI projects delivered, 40+ of them agentic, on our own agentic platform, S-PRO Agents. S-PRO is a Certified partner in the Claude Partner Network, our team includes Claude-certified engineers and architects, and we are headquartered in Zurich.

There is no single ranking. Choose on evidence: delivered financial-services projects, a defined path from pilot to production, governance with a human in the loop, security certifications and integration with your systems. S-PRO is a Zurich firm that builds custom AI agents for banks, wealth managers and fintechs; it delivered a Zendesk support agent for a leading German neobroker (90% correct ticket classification, more than 40% faster ticket handling, as reported). Use the comparison table above to put any shortlist side by side. For US financial institutions, our overview of AI agent development companies for financial services compares nine firms by public evidence, location and rate.

Ask for evidence on six points: financial-services experience, pilot-to-production gates, governance and audit trail, security and data location, integration with core systems, and ownership of code and prompts. In S-PRO’s view, a firm that cannot show named gates, an audit trail and a handover path is not ready for a bank’s production environment.

Yes, if the agent acts through controlled interfaces (APIs or MCP) and not directly on the core. We recommend starting read-only and enabling write actions one at a time, each behind a named human approver. For legacy code bases S-PRO also offers core and legacy modernization (testing, code health, AI-assisted fixes) as a separate topic. Which route fits depends on the systems in place and is agreed after discovery.

Yes. A KYC and onboarding agent researches the client, checks gaps in the source-of-wealth information and routes the file to a human approver, who makes the decision. See KYC and onboarding AI agents for banks.

The 2011 model risk guidance (SR 11-7) was superseded on 17 April 2026 by interagency guidance issued by the Fed, OCC and FDIC (Fed SR 26-2, OCC Bulletin 2026-13). The guidance says that "Generative AI and agentic AI models are novel and rapidly evolving. As such, they are not within the scope of this guidance." It also says that a banking organization's risk management and governance practices "should guide the determination of appropriate governance and controls" for such tools, and that its principles apply to traditional statistical and quantitative models and non-generative, non-agentic AI models. The guidance does not set forth enforceable standards or prescriptive requirements. For an agent, S-PRO designs controls such as an evaluation set re-run when prompts or models change, human approval points, an audit log and named oversight, and builds them into the pilot. This is general information, not legal advice.