GQ
GovernanceIQ
AI Governance Intelligence Platform · Credit Sesame · Model Risk, Lineage & Regulatory Readiness
AI learning from 1,940 governance outcomes
ENV: PROD · ROLE: MODEL RISK LEAD
Dashboard
TrendIQ 10
DecisionIQ 9
ActionIQ 9
EffectivenessIQ 22
OntologyIQ 12
KnowledgeIQ 8
ReasoningIQ 5
GovernanceIQ 30
AI Governance Operations
Continuous oversight of models, data lineage, and regulatory readiness across Credit Sesame's AI-powered financial wellness platform
◊ Knowledge graph: 38,614 linked artifacts
Governance Readiness
87%
↑ 4pts this month
Lineage Coverage
91%
↑ 6pts this quarter
Revalidation Closure
78%
↑ 9pts this quarter
Audit Prep Cycle Time
-31%
↓ vs. last audit cycle
Open Governance Risks
5
2 critical
Continuous Intelligence Loop
Signal → Decision → Execution → Outcome → Organizational Learning
● Active across all modules
TrendIQ
10 active signals
→
DecisionIQ
9 initiatives
→
ActionIQ
8 in execution
→
EffectivenessIQ
22 outcomes learned
Governance Readiness — 12-week trend
Composite score across lineage, revalidation, and disclosure coverage
Governance Time Recaptured
Analyst hours saved per week by automation, by activity
Lineage & Documentation Health
Share of production models with complete lineage, by model family
Signal Mix — Last 30 Days
Distribution of governance signals by domain
AI Confidence Distribution
Confidence levels across active AI recommendations
Top Governance Risks — AI-prioritized
Highest-impact items pulled from TrendIQ
AI Operational Copilot
Live workflow optimizations the system is recommending
TrendIQ — AI Governance Signal Detection
Signals surfaced continuously from the model registry, feature store, vendor risk register, and regulatory guidance feeds
● Connected to 6 enterprise systems
Active Signals
10
↑ 3 this week
Pattern Clusters
5
2 emerging
Cross-Domain Correlations
6
3 high-strength
RCAs in Progress
4
Avg conf 86%
AI Recommendations
5
Pending review
Signals 12
Patterns 5
Correlations 7
Root Cause Analysis 4
Recommendations 9
DecisionIQ — Initiative Management
Active governance initiatives created from accepted signals, with AI-suggested follow-on tasks
9 active initiatives 3 AI suggestions pending
AI Continuously Recommending
The system is learning from 1,940 historical governance outcomes to improve every recommendation below
Initiative owners
94% acceptance
Task owners
89% acceptance
Closure paths
82% accepted
Follow-on tasks
71% accepted
ActionIQ — Execution Coordination
Two-tier Kanban: initiatives at the top, task drill-down on click
Initiatives Kanban
AI Operational Copilot
Live workflow optimizations across the board
Automation Opportunities
Workflows AI can orchestrate end-to-end (with model risk lead signoff)
EffectivenessIQ — Organizational Learning
What worked, what failed, and how the system is getting better at AI governance recommendations
● Continuous learning active
Outcomes Captured
1,940
↑ 118 this month
SME Corrections
37
→ model refinement
Initiative Success Rate
84%
↑ from 71% (Q1)
AI Recommendation Accuracy
89%
↑ 6pts vs baseline
Failed Closures Studied
14
Root-caused
Recent Learning Events
Outcomes from closed initiatives feeding back into the recommendation model
Improvement Over Time
Recommendation acceptance rate by quarter
What's Working (Reinforced)
Patterns the AI is doubling down on
What's Not Working (Down-weighted)
Patterns the AI is moving away from
OntologyIQ — AI governance Knowledge Graph
A living semantic model connecting every entity and risk relationship across active AI governance work
◊ 38,614 linked entities · 84,920 relationships
Entity Types Modeled
9
Customers, Credit Profiles, AI Models, Predictions, Recommendations, Regulatory Policies, Consent, Audit Events, Business Rules
Relationship Types
12
feeds · generates · governed-by · requires · scores · supported-by · impacts…
Graph Freshness
96%
Entities updated within the last cycle
Query Accuracy (validated)
92%
Against SME-reviewed answer set
Ask the Knowledge Graph
Not sure where to start? Try a sample question below, or type your own — answers are traced back to the underlying graph nodes and edges.
◊ Grounded answers only
Knowledge Graph Schema
Core entity and relationship types behind every answer
Highest-Connectivity Entities
Nodes with the most cross-domain relationships — usually the highest-leverage risk points
KnowledgeIQ — Institutional & Tacit Knowledge Capture
Tracks where model governance know-how is captured, at risk, or missing entirely, and visualizes it as a knowledge graph
◊ Linked to the OntologyIQ knowledge graph
Knowledge Assets Captured
3
↑ 2 this month · 9 in library
Experts at Retirement/Rotation Risk
8
6 uncaptured
Capture Coverage
50%
Of active work with a linked knowledge asset
Avg. Time-to-Capture
17d
↓ from 26d last quarter
Knowledge Graph — Experts, Assets, Programs & Sites
Instance-level view of the graph: who holds the knowledge, what's been captured, and which programs and sites it feeds. Click any node.
At-Risk Expertise
Operators and specialists nearing retirement or rotation, ranked by capture status
Knowledge Asset Library
Captured video, process sheets, and annotated drawings, linked to the program and initiative they came from
ReasoningIQ — Evidence-Backed AI governance Recommendations
Executives need recommendations, not just answers — the reasoning engine evaluates multiple AI governance factors together to produce a single evidence-backed recommendation
◊ Reasoning over the OntologyIQ knowledge graph
Reasoning Chains Run
5
↑ this week
Avg. Factors Evaluated
5.0
per recommendation
Avg. Recommendation Confidence
86%
Grounded in graph evidence
Executive Recommendations Delivered
5
This month
From Systems of Record to Systems That Reason
No existing system is replaced — each becomes more valuable feeding the reasoning engine
Model Registry · Feature Store · Vendor Risk Register · Consent Platform · Data Lake
6 systems connected
→
Enterprise Ontology
9 entity types
→
Knowledge Graph
38,614 linked entities
→
Reasoning Engine
4 chains run
→
Business Users
Executive decisions
Reasoning Scenarios
Each scenario evaluates multiple factors across the enterprise before producing a recommendation — click a scenario to see the full evidence chain
Add Custom Task
AI has pre-filled this based on the initiative's closure path
AI Pre-fill — Suggestions below are editable. Owner defaults to AI's recommendation.
GovernanceIQ — Governance Artifact Registry
A single system of record for every governance artifact — model validation packages, disclosures, lineage records, audit events, vendor attestations, consent records, and institutional knowledge assets
◊ 30 artifacts tracked ◊ 5 connected systems
Total Artifacts Tracked
30
Across 7 artifact types
Filed / Complete
10
Ready for audit
In Review / Pending
18
Actively being closed out
Overdue
2
Requires immediate attention
Connected Systems
The systems of record feeding the registry — click a system to filter the registry below
Governance Registry
Every tracked artifact, filterable by type — click any row for the full evidence detail