Use Case Bank: Where the Journey Begins

Every digital innovation journey starts with a simple but powerful question: Has someone already solved this problem? The Use Case Bank (UCB) is Calibo's answer to that question. It acts as the launchpad for innovation within the Digital Business Innovation Methodology (DBIM), ensuring that organizations don't reinvent the wheel. Instead of starting from scratch, teams can search, evaluate, and build on proven ideas—saving time, reducing redundancy, and accelerating value delivery. Whether it’s a business leader seeking to improve customer experience or a compliance officer exploring automation opportunities, the UCB provides a structured, searchable space to explore what’s already working and what’s possible.

When and Why to Search the Use Case Bank

Stakeholders search the Use Case Bank with intent, based on business needs, strategic priorities, and operational goals. Here are a few common scenarios that motivate stakeholders like the CDO, CPO, Portfolio Owner, Engineering Leads, and others to initiate a keyword-based search in the Use Case Bank:

Use Case Search Driver	Scenario	Search Trigger	Why
Strategic Alignment with Organizational Goals	The product manager wants to launch initiatives that support a new corporate strategy around customer-centricity or data-driven personalization.	CPO searches for keywords like: “customer feedback analytics” “personalized recommendations” “sentiment analysis”	To avoid duplicating efforts and build upon already aligned use cases.
Meeting Regulatory or Compliance Requirements	A Compliance Lead or CDO is responding to new regulations (for example, ESG, GDPR updates).	They search for keywords like: “audit trail” “compliance automation” “data lineage”	To identify whether similar use cases exist and can be reused or need enrichment.
Industry Benchmarking	Leadership observes competitors using AI for fraud detection or analytics.	Engineering Lead or Portfolio Owner searches for terms like: “fraud” “machine learning” “real-time analytics”	To stay competitive and discover reuse opportunities.
Resource Optimization / Budget Efficiency	The PMO or Portfolio Owner seeks to reduce rework by reusing existing assets.	They search for use cases with reusable assets like: “data pipelines” “API integrations” “frontend components”	To assess reusability and save effort and cost.
New Business Opportunities or Initiatives	A CDO explores alternative credit scoring models for financial inclusion.	The CDO searches for keywords like: “credit scoring” “alternative data” “unbanked”	To check if any existing groundwork can accelerate the new initiative.

By grounding searches in strategic, operational, and technical objectives, stakeholders can use the Use Case Bank as a true accelerator—avoiding duplication, enabling reuse, and advancing only those ideas that promise real value.

How Advance Bank Stakeholders Tapped into the Use Case Bank

With Advance Bank’s leadership fully aligned around the vision of becoming a digital-first institution, each functional lead began their innovation journey by diving into the Use Case Bank (UCB).

Let’s follow how different team members from Advance Bank explored and interacted with the UCB.

Stakeholder: Martha Grace (Chief Product Officer)

Search Term: “Sentiment Analysis”
System Response:
- No exact match found in the UCB for her precise requirement related to product-level sentiment analysis tied to specific feedback and KPIs.
- Some semantically similar entries were discovered (like “Social Media Sentiment Trends”), but they focused on brand-level social data rather than direct product feedback and lacked integration with internal customer experience dashboards.

Action Taken: Martha initiated a new use case submission via the UCB form, ensuring it addressed the exact problem Advance Bank aimed to solve.

Sentiment Analysis of Customer Product Reviews

Field	Description
Use Case Title	Sentiment Analysis of Customer Product Reviews
Business Function / Domain	Retail Banking – Customer Experience
Problem Statement	Lack of real-time visibility into customer sentiment, leading to delayed response and missed improvement opportunities
Objective / Value Proposition	Automate analysis of customer feedback to detect sentiment trends, improve product quality, and enhance customer loyalty.
Key KPIs	Customer Satisfaction (CSAT), Net Promoter Score (NPS), Negative Review Reduction%, Review Processing Time
Team Size	6 (Product Owner, Data Scientist, Data Engineer, Frontend Developer, Backend Developer, Business Analyst)
Expected Timeline	6 weeks
Functional Scope	Ingest reviews from app and web Apply NLP models Visualize trends on the dashboard Alert product teams on sentiment dips
Status (Production/ Under Development/ Under Review)	New Entry Created

Stakeholder: Esther Jackson (Chief Digital Officer)

Search Term: “AI in Compliance”

System Response:

No exact match for her precise requirement.

Identified a relevant in-progress use case: AI-Powered Regulatory Compliance Tracker, which uses NLP to map regulations and trigger alerts.

AI-Powered Regulatory Compliance Tracker

Field	Description
Use Case Title	AI-Powered Regulatory Compliance Tracker
Business Function / Domain	Compliance & Risk
Problem Statement	Manual review of compliance documents leads to delayed alerts and potential non-conformance.
Objective / Value Proposition	Automate monitoring of compliance clauses using NLP.
Key KPIs	Audit Readiness %, Response Time to Non-Compliance, Alert Accuracy
Team Size	5
Expected Timeline	8 weeks
Functional Scope	Scan policies, map to regulatory changes, and trigger alerts.
Status (Production/ Under Development/ Under Review)	Under Development

Action Taken

Esther reviewed the existing entry and proposed feature enhancements for broader document coverage and integration with internal risk systems.

Stakeholder: Joseph George (Portfolio Owner)

Search Term: “Credit Evaluation”

System Response:

Two use cases surfaced as strong matches:

Intelligent Credit Scoring Engine – in Production.

Early Warning System for High-Risk Borrowers – Under Review.

Intelligent Credit Scoring Engine

Field	Description
Use Case Title	Intelligent Credit Scoring Engine
Business Function / Domain	Retail Lending
Problem Statement	Traditional scoring models do not account for real-time behavior or alternative data.
Objective / Value Proposition	Improve loan approval rates while reducing default risk using ML.
Key KPIs	Loan Approval Rate, Default Rate, Customer Onboarding Time
Team Size	7
Expected Timeline	10 weeks
Functional Scope	Use ML on banking transactions, credit history, and alt-data to score applicants.
Status (Production/ Under Development/ Under Review)	Production

Early Warning System for High-Risk Borrowers

Field	Description
Use Case Title	Early Warning System for High-Risk Borrowers
Business Function / Domain	Risk Management
Problem Statement	No proactive visibility into borrowers likely to default.
Objective / Value Proposition	Identify high-risk behavior trends and flag early warnings.
Key KPIs	Prediction Accuracy, Loan Recovery Rate
Team Size	4
Expected Timeline	6 weeks
Functional Scope	Monitor transactional patterns for early risk signals.
Status (Production/ Under Development/ Under Review)	Under Review

Action Taken: Joseph evaluated both for fit within the bank’s financial inclusion roadmap and decided to initiate scaling plans for the scoring engine, while proposing enhancements to the early warning system.

Stakeholder: Alex Carter (Product Release Manager)

Search Term: “Deployment Observability”

System Response:

Alex was working on a use case to automate the detection and resolution of payment exceptions (such as failed transactions, duplicate payments, suspicious reversals) across Advance Bank's digital banking systems. When he searched for “Automated Payment Exception Handling” in the Use Case Bank (UCB), he didn't find an exact match, but discovered two semantically similar entries that could be leveraged partially:

Use Case Title	Business Function / Domain	Problem Statement	Objective / Value Proposition	Key KPIs / Metrics	Status
Transaction Reconciliation Automation	Operations / Finance	High manual effort and errors during reconciliation between banking ledgers and third-party clearing systems	Automate reconciliation of internal transaction logs with external partner statements to reduce errors and manual workload	Reconciliation Time, Error Rate, Staff Productivity Index	Production
Duplicate Transaction Detector	Payments & Risk	Duplicate payments due to retry loops or system latency go undetected until reported by customers	Real-time detection of duplicate payments using rule-based logic and transaction fingerprinting	Duplicate Payment Rate, Detection Time, False Positive Rate	Under Development

Action Taken :

Alex realized that:
- Transaction Reconciliation Automation already addressed parts of exception detection, especially ledger mismatches.
- Duplicate Transaction Detector handled a subset of payment anomalies.
However, neither use case addressed:
- Comprehensive exception classification (for example, timeout, reversal, fraud-related)
- Workflow for automated resolution routing to internal teams
- Customer notification pipeline for failed or reversed payments
Instead of creating a new use case from scratch, Alex raised a Use Case Reuse + Enhancement Request, aiming to:
- Extend the “Duplicate Transaction Detector” to handle additional exception types
- Integrate its output with the reconciliation workflows already automated
- Add automated notification workflows and resolution SLAs for internal handling

This approach reduces duplication, leverages validated assets, and accelerates time to implementation.

Martha wasn’t alone in her discovery journey. While she didn’t find an exact match for her search on “Sentiment Analysis,” she quickly realized the business need was unique enough to warrant a new entry—and seamlessly created a fresh use case in the Use Case Bank using the platform’s guided template. Esther, the Chief Digital Officer, found a relevant match in the form of an AI-powered compliance tracker already under development, which she chose to enhance further. Joseph, the Portfolio Owner, discovered two promising matches—an intelligent credit scoring engine already in production and an early warning system under review—both of which aligned with his team’s credit evaluation goals. Meanwhile, Alex, the Product Release Manager, searched for “Customer Feedback Analytics for Branch Services” and came across a couple of partial matches, which he evaluated for reuse potential. When those didn’t fully meet his requirements, he documented the gaps and enriched a new use case accordingly.

That’s the power of a well-structured Use Case Bank—enabling targeted search, encouraging reuse, and accelerating innovation by bridging the gap between intent and execution.

What’s Next: Discovering What Matters

Once you add a use case to or select one from the use case bank, the next step is Use Case Discovery. This phase involves clarifying the business problem, identifying impacted personas, defining desired outcomes, and checking for existing solutions in the internal marketplace. In short, the Use Case Bank acts as the funnel through which promising ideas are filtered, setting the stage for rigorous evaluation and refinement in Discovery.

What's next? Use Case Management