How AI Analysis Revealed that 45% of Credit Union Contacts Were About Credit and Created a Roadmap to Reduce Costs by 50% | Real Case Study
In-depth analysis identified systemic inefficiencies: extensive manual validation in 100% of contacts, outdated data in 30% of cases, and high financial potential underexploited. Engaged members seek multiple products, but processes limit revenue.
Contact Distribution by Topic
We analyzed thousands of interactions to map exactly where members concentrate their demands
Contact Reason Concentration
Analysis revealed that almost half of contacts are related to credit operations:
| Contact Category | Percentage | Main Topics |
|---|---|---|
| Loans, credit and renegotiation | 45% | Simulations, early payoff, amortization, rates |
| Withdrawals and paid-in capital | 20% | Application withdrawals, use of excess capital |
| Invoices and payments | 15% | Non-receipt, minor delays, manual issuance |
| Registration updates and access | 15% | Incorrect email/phone, login, documents |
| Other topics | 5% | General information, referrals, specific questions |
The Real Problems Hidden in the Data
AI analysis revealed three fundamental patterns that explain inefficiencies and missed opportunities
Universal Manual Validation
100% of contacts require extensive manual validation (SSN, mother's name, date of birth, phone, email), causing increased AHT and friction especially for elderly members.
Affects all interactionsChronic Outdated Data
Approx. 30% of contacts have digital problems: invoices not received, old emails, outdated phones, app failures. Strong correlation with recurrence.
Cause of repeated contactsUnderexploited Financial Potential
Financially active members with multiple contracts solve several topics in the same contact. Clear cross-sell opportunity currently underexploited.
Uncaptured revenueCritical Insight
Main Operational Bottlenecks
CriticalImplementation Timeline
Strategy structured in three phases with quantified gains: from operational efficiency to commercial intelligence
Short Term
0-3 months
Focus: Cost and Recurrence Reduction
- Standardize single validation checklist: Fewer redundant questions, faster process
- Create standard script for invoices: Automatic resend via email + SMS + WhatsApp
- Proactive alerts: Notify member about invalid email or outdated phone
- Quick closure script: When member only wants specific information
Estimated Gains:
- AHT reduction: 10-15%
- Invoice/app recurrence: 20-25%
- Operational savings: 8-12%
Medium Term
3-9 months
Focus: Efficiency and Monetization
- Complete portal/app: Automatic invoice duplicate, payoff and amortization simulation, clear visualization of paid-in capital
- Self-service registration update: Member updates email and phone without service
- Light commercial script: Contextual offer after payoff or simulation
- Member segmentation: Identify multi-contract, high balance, advance history
Estimated Gains:
- Additional AHT: 20-25%
- Human contacts avoided: 30-40%
- Cross-sell revenue increase: 5-10%
- NPS improvement: +8 to +12 points
Long Term
9-18 months
Focus: Scale, Predictability and Intelligence
- Automatic AI monitoring: Intent detection (withdrawal, payoff, new credit) and risk/opportunity classification
- Proactive communication: Alerts before due dates, automatic payoff suggestions
- Intelligent offer engine: Based on member's history and financial profile
- Gradual migration to digital channels: Simple contacts resolved without humans
Estimated Gains:
- Total operational cost reduction: 35-50%
- Member LTV increase: 10-20%
- Minor delinquency reduction: 15-25%
- Sustained NPS above +60
Consolidated Operational Transformation
Expected impact after complete roadmap implementation in 18 months
Current Situation vs. After Full Implementation
| Metric | Current Situation | After 18 Months |
|---|---|---|
| Average AHT | High (manual validation) | -35% |
| Recurrence | High (outdated data) | -45% |
| Human contacts | 100% manual service | -40% |
| NPS | Already good (70% satisfied) | +60 sustained |
| Total operational cost | High | -50% |
| Cross-sell revenue | Underexploited | +15% |
Executive Summary
How to Solve Main Bottlenecks
Bottleneck: Extensive Manual Validation (100% of Contacts)
High PriorityEvery contact requires SSN, mother's name, date of birth, phone and email. Dramatically increases AHT and creates friction for elderly or digitally challenged members.
Recommended Solutions:
- Implement facial or fingerprint biometric authentication in app
- Reduce checklist to 2-3 essential data points (SSN + one additional factor)
- Create expedited flow for members with positive history
- Integrate phone recognition via verified WhatsApp Business
Bottleneck: Recurring Digital Problems (30% of Contacts)
High PriorityInvoices not received, outdated or corporate emails, old phones, app failures (login, recovery, document upload). Generates recurrence and manual issuance.
Recommended Solutions:
- Proactive alerts when email/phone is invalid or outdated
- Multiple automatic channels for invoices: email + SMS + WhatsApp + app
- Complete self-service flow for registration updates
- Automatic validation of corporate vs. personal emails
- Improve app UX: simplified login, quick password recovery
Bottleneck: Lack of Financial Self-Service
Opportunity45% of contacts are about credit (simulations, payoff, amortization), but everything depends on the agent. Members want to solve on their own and quickly.
Recommended Solutions:
- Portal/app with complete credit, payoff and amortization simulator
- Clear visualization of paid-in capital and how to use it
- Contract history with real-time status
- Automatic invoice duplicate without contact needed
- Proactive push notifications: "You can pay off with X% discount"
Opportunity: High Underexploited Financial Potential
RevenueMembers with multiple contracts, interest in early payoff and questions about new contracts. Same member solves multiple topics in one contact. Poorly structured cross-sell.
Recommended Solutions:
- Intelligent segmentation: multi-contract, high balance, advance history
- Light commercial script: contextual offers after payoff or simulation
- AI offer engine: based on history and financial profile
- Agent dashboard showing real-time opportunities during service
- Proactive campaigns via email/WhatsApp for specific profiles
Positive Reality: High Explicit Satisfaction (70%)
StrengthIn over 70% of contacts, members thank, show confidence and accept satisfaction survey. Good human quality of service.
How to Leverage:
- Confirms problem is NOT people, but processes and technology
- Solid foundation to implement changes without member resistance
- Opportunity to maintain high NPS while reducing costs
- Free agents from operational tasks to focus on strategic relationships
AI-Powered Interaction Analysis by CYF
Behind each insight is our analysis platform — transforming thousands of conversations into actionable intelligence for credit unions
Our Solution
We use automatic call transcription + large language models (LLMs) + hybrid AI pipelines to understand:
- What members really need (credit, withdrawal, payoff intent)
- Where processes get stuck (validation, registration, invoices)
- Hidden commercial opportunities (multi-contract, unused capital)
- Recurrence patterns and their real causes
This combination of audio, text and artificial intelligence reveals insights like "45% of contacts about credit" and "50% cost reduction potential" — transforming service into strategy.
