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ABA Data Maturity Evaluation
Section
1
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6
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Email
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Banker Name
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First
Last
Title
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Select One
President/CEO
SVP/EVP
VP/MD
AVP/Officer
Head of Retail
Head of Lending
Head of Deposits
Head of Digital
Head of Operations
CIO
CTO
COO
CMO
CFO
CISO
CCO
Email (To receive results)
(Required)
Functional Area
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Select One
Operations
Innovation Office
Project Management
Product Management
Deposit Operations
Finance & Accounting
Banking Operations
Payments
Credit Risk Management
Marketing
Risk Management
Business Development
Lending
Branch Banking
Digital Banking
Audit
Legal/Counsel
Compliance
Information Technology
Other
Bank Name
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Asset Size
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Select One
Under $100M
$100M - $250M
$250M - $500M
$500M - $1B
$1B - $5B
$5B - $10B
$10B - $50B
Over $50B
Leadership and Organization
Leadership:
1. Is there a designated data executive or leader in the organization?
(Required)
No designated leader
Middle management leads data
C-level data executive
2. At what level does the data leader sit in the organization?
(Required)
Middle management
Reports to C-Suite
C-Suite level
3. How engaged is the C-suite in supporting data initiatives?
(Required)
Tepid support
Acknowledges value but doesn't prioritize
Actively engaged and supportive
4. Is there a formal data governance committee or council in place?
(Required)
No
Informal group
Formal committee with regular meetings
Organizational Structure:
5. Where does the data organization reside within the company structure?
(Required)
Scattered across departments
Part of IT or a business function
Stand-alone data organization
6. Are there data analysts/subject matter experts embedded in business units?
(Required)
No
Some in key areas
Yes, across all major business units
Staffing:
7. How would you rate the alignment of work with skill levels and expertise?
(Required)
Poor alignment, often over- or underqualified
Some misalignment
Good alignment
8. Is there a process for capturing and leveraging the knowledge of subject matter experts regarding data?
(Required)
No process
Informal knowledge sharing
Formal knowledge management system
Strategy and Execution
Strategic Alignment:
9. Is there a defined data strategy aligned with the business strategy?
(Required)
No data strategy
Data strategy exists but not aligned
Aligned data strategy
10. Are there defined use cases in the data strategy?
(Required)
No defined use cases
Some use cases defined
Comprehensive use cases aligned with business priorities
Funding:
11. Is there a distinct budget for data-related initiatives?
(Required)
No distinct budget
Some data initiatives have dedicated funding
Comprehensive data budget
12. Is funding aligned with specific use cases or more general?
(Required)
General IT budget
Some use-case specific funding
Primarily use-case driven funding
13. Is there a method for measuring the return on investment (ROI) for data initiatives?
(Required)
No ROI measurement
Basic cost-benefit analysis
Comprehensive ROI framework
Work Prioritization and Management:
14. Are there standardized processes for work intake, prioritization, and delivery?
(Required)
Ad hoc processes
Some standardization
Fully standardized and documented
15. Are there defined service-level agreements (SLAs) for data work, and how consistently are they met?
(Required)
No SLAs
SLAs exist but inconsistently met
SLAs consistently met
16. Are Agile methodologies used for data work management?
(Required)
Traditional waterfall
Hybrid approach
Fully Agile
Data Governance
Data Governance Practices:
17. Is there an established data governance program?
(Required)
No program
Informal or limited governance
Comprehensive governance program
18. Are there designated business data owners and data stewards?
(Required)
No designated owners
Some key areas have owners
Comprehensive ownership model
19. Is there a comprehensive data catalog with business definitions?
(Required)
No catalog
Partial catalog
Comprehensive, up-to-date catalog
Regulatory and Compliance:
20. Is there clear accountability for regulatory compliance related to data?
(Required)
Unclear accountability
Shared responsibility
Clear accountability assigned
21. How automated is regulatory reporting?
(Required)
Mostly manual
Partially automated
Highly automated
Data Safeguarding:
22. Has all data been classified for sensitivity/privacy?
(Required)
No classification
Partial classification
Comprehensive classification
23. What level of encryption is used for data at rest and in motion?
(Required)
Limited/no encryption
Some encryption
Pervasive encryption
24. How granular is the data access control?
(Required)
Broad access
Role-based access
Attribute-based access control
Data Fitness
Quality and Veracity:
25. How much time is spent reconciling data between systems?
(Required)
Significant time
Some reconciliation needed
Minimal reconciliation required
26. Are there processes to address data quality issues at the source rather than downstream?
(Required)
Mostly downstream fixes
Mix of source and downstream
Primarily addressed at source
27. Is there a formal data-quality measurement and improvement process?
(Required)
No formal process
Some quality measures
Comprehensive quality framework
Granularity and Timeliness:
28. Is detailed transactional data retained and available for analysis?
(Required)
Limited retention
Some detailed data retained
Comprehensive retention of detailed data
29. How quickly is data available in analytical systems after transactions occur?
(Required)
Days/weeks lag
Next day
In real or near-real time
30. Are real-time data pipelines or streaming analytics in use?
(Required)
No real-time capabilities
Some real-time data
Extensive use of real-time data
31. How are historical changes to data (e.g., policy changes, claim status changes) tracked and made available?
(Required)
Overwritten/lost
Some history retained
Comprehensive historical tracking
32. How far back is historical data easily accessible for analysis?
(Required)
Less than one year
One to five years
More than five years
33. Is there a formal data archiving and retention policy?
(Required)
No policy
Basic policy
Comprehensive policy aligned with business needs
Preparedness:
34. How much data wrangling is required for typical analyses?
(Required)
Significant wrangling for most analyses
Some wrangling required
Minimal wrangling needed
35. How well defined is the data flow between core systems and analytical environments?
(Required)
Poorly defined
Partially documented
Well-defined and optimized
Architecture and Technology Management
Data Architecture:
36. Are there documented data architectures, guiding principles, and standards?
(Required)
Minimal documentation
Some documentation
Comprehensive documentation
37. Is there architectural governance over data initiatives?
(Required)
No governance
Some oversight
Comprehensive governance process
38. Is there a data lake or central repository for all bank data?
(Required)
No central repository
Partial implementation
Comprehensive data lake/repository
39. How mature is the organization's API management for data access?
(Required)
Limited API use
Some API management
Comprehensive API strategy and management
