AI Maturity & Readiness – Financial Organization

Answer each scenario based on how your financial organization behaves today. Each option (A–E) maps to a maturity level from Ad‑hoc to Transformational.

Response Scale: A = Very Low / Ad‑hoc (1) B = Low / Emerging (2) C = Moderate / Developing (3) D = High / Operational (4) E = Very High / Transformational (5)

1. Leadership Commitment – AI for Credit Risk Forecasting

Your analytics team proposes an AI model to improve credit risk forecasting. Leadership listens but expresses concern about regulatory scrutiny and model explainability. How would leadership most likely respond?

A. Avoid the project entirely due to perceived regulatory risk. B. Ask for a high-level summary but take no action. C. Approve a small pilot with minimal resources. D. Sponsor a structured pilot with compliance and risk teams involved. E. Champion the initiative, allocate budget, and align it to long-term risk strategy.

2. Data & Technology Foundations – Fraud Detection Data Integration

A new fraud detection model requires transaction data from retail banking, card services, and digital channels. Each team stores data differently and uses inconsistent definitions. What happens next?

A. You cannot obtain the data due to siloed systems and access barriers. B. You receive partial or low-quality data that requires heavy cleanup. C. You manually merge datasets with moderate effort and workarounds. D. You use existing governed pipelines and metadata tools to standardize data. E. Data is already unified in a governed, secure platform with lineage and access controls.

3. Existing Capabilities & Talent – Automating KYC

A business unit wants to automate parts of the KYC review process using AI to reduce manual workload and improve accuracy. How does your organization respond?

A. No one has the skills or capacity, and the project stalls. B. One analyst experiments informally without a structured approach. C. A small data team supports the project but is overloaded. D. A cross-functional team (data engineering, data science, compliance, KYC ops) is available. E. A mature AI enablement function guides the team with standardized workflows and governance.

4. Cultural Readiness – AI-Assisted Customer Service

You introduce an AI assistant that drafts responses for customer inquiries about account issues, loan status, or card disputes. How do employees respond?

A. Most refuse to use it due to fear of errors or compliance violations. B. A few try it but stop due to lack of trust. C. Adoption is mixed; some teams use it, others avoid it. D. Most teams adopt it after seeing accuracy and time savings. E. Employees actively request more AI tools and share best practices.

5. Governance, Risk & Ethics – Model Drift in Credit Decisioning

A credit decisioning model begins producing inconsistent approvals. A manager raises concerns about fairness, bias, and regulatory exposure. What happens next?

A. No one knows who owns the model or how to escalate the issue. B. The issue is acknowledged but not formally investigated. C. A technical team reviews the model informally. D. A governance process triggers a structured review with risk, compliance, and model validation. E. Continuous monitoring detects the issue before it impacts customers, and automated alerts trigger remediation.

6. Use Case Strategy & Integration – Duplicate AI Projects in Wealth Management

Two wealth-management teams independently build AI tools for portfolio risk scoring. Leadership discovers the duplication during a quarterly review. How does the organization respond?

A. Duplication continues because no one coordinates AI work. B. Teams are told to collaborate, but nothing changes. C. A central team attempts to align efforts reactively. D. A portfolio review consolidates the work into a shared, scalable solution. E. A unified AI roadmap prevents duplication and ensures enterprise-wide reuse.

AI Maturity & Readiness Survey
Financial Organization – Scenario Based

AI Maturity Result

AI Maturity & Readiness SurveyFinancial Organization – Scenario Based

AI Maturity Result

AI Maturity & Readiness Survey
Financial Organization – Scenario Based