AI governance. Financial services.
We mean to be pedantic. *
We examine the details behind your AI’s decisions.
For small and mid-sized financial-services firms, we turn questions about AI into a practical governance playbook: know your systems, assign responsibility and keep the evidence.
THE PEDANTIC PERSPECTIVE [ 01 ]
An AI system is more than its model.
01 PurposeWhat decision is it here to support?
02 DataWhere does its information come from?
03 BehaviorWhere can it fail, drift or cause harm?
04 AccountabilityWho can question it—and override it?
* We want to understand how it all works together.
Built for the realities of financial services
Banks Credit unions Fintechs Financial-services teams
01 / What we do
From “we use AI” to “we can account for it.” Start where you are. Build the controls you need. Keep them working as your systems change.
01 / Understand
AI governance diagnostic Establish what AI is in use, where the risks sit and what needs attention first.
AI inventory and use-case discovery Initial risk classification and gap assessment A prioritized, practical action plan Typical engagement · 2–3 weeks
Discuss a diagnostic ↗
02 / Establish
Governance implementation Turn the findings into clear ownership, repeatable controls and evidence your teams can use.
System cards, policies and decision records Vendor review and human oversight definitions Monitoring and incident escalation procedures Typical engagement · 8–10 weeks
Discuss implementation ↗
03 / Maintain
Ongoing governance Keep your governance current after launch, through new use cases, vendor changes and emerging issues.
Scheduled reviews and evidence updates Support for exceptions and governance decisions Follow-up on monitoring findings and actions Monthly advisory engagement
Discuss ongoing support ↗
Engagement scope and timing are agreed around your systems, priorities and team capacity.
02 / How we think
Detail is not a distraction. It’s the work. A policy alone cannot tell you whether an AI system is behaving as intended. You need to understand the data, the decisions and the people around it.
Pedantic brings data-management discipline and responsible-AI thinking into a step-by-step consulting approach, proportionate to your organization.
[ a ] Look at the whole system. Models, source data, vendor-embedded AI, staff use and human handoffs all belong in the conversation.
[ b ] Make accountability explicit. Define who owns the risk, who reviews the outcome and who has authority to stop or override a decision.
[ c ] Make the reasoning traceable. Record decisions, limitations, unresolved tensions and the evidence that supports the next action.
Informed by established disciplines
DAMA · EDM Association · The Alan Turing Institute
Independent consulting. No affiliation, endorsement or certification implied.
03 / What you take away
Governance you can put your hands on. We help your team develop and maintain the core records behind responsible AI use—not just another presentation.
01 AI inventory02 Risk classification03 Model / system cards04 Decision log05 Vendor assessments06 Incident escalation process07 Human oversight definitions08 Monitoring cadence09 Approved use policy
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