Why your risk department is integral to your customer engagement strategy

Breaking down silos between risk management and customer experience

Published: June 7, 2023 Author: Symend Reading time: 6 minutes

Key Takeaways

Risk and customer engagement teams often operate in silos, creating missed opportunities
Effective risk management requires understanding customer behavior, not just credit scores
Customer engagement strategies must balance risk mitigation with experience optimization
Integrated risk-engagement approaches reduce losses while improving customer satisfaction

In most organizations, the risk department and customer engagement teams operate as separate entities with different priorities, metrics, and cultures. Risk focuses on minimizing losses and protecting the business. Customer engagement focuses on satisfaction, loyalty, and experience. But this separation creates a critical blind spot that undermines both objectives.

The truth is, risk management and customer engagement are two sides of the same coin. Organizations that integrate these functions see better outcomes on both fronts—lower losses and happier customers.

The Traditional Divide

Understanding why these teams typically operate separately helps explain why integration is so powerful.

The Risk Department Perspective

Primary Goal: Minimize financial losses and exposure
Key Metrics: Delinquency rates, charge-off rates, loss rates, fraud detection
Approach: Data-driven, policy-focused, cautious
Tools: Credit scores, risk models, approval algorithms
Culture: Conservative, analytical, focused on protecting the business

The Customer Engagement Perspective

Primary Goal: Maximize satisfaction, loyalty, and lifetime value
Key Metrics: NPS, CSAT, retention rate, engagement rate
Approach: Customer-centric, experience-focused, growth-oriented
Tools: CRM systems, engagement platforms, personalization engines
Culture: Empathetic, creative, focused on delighting customers

The Problem with Separation

When these teams operate independently, organizations face:

Risk policies that frustrate good customers
Engagement strategies that ignore risk signals
Inconsistent customer experiences as customers move between "good standing" and "at risk"
Missed opportunities to prevent delinquency through proactive engagement
Duplicated data collection and analytics efforts

Why Risk and Engagement Must Work Together

Risk Prevention Through Engagement

The best way to manage risk isn't to deny credit or aggressively collect—it's to prevent delinquency in the first place through effective engagement.

Consider these scenarios:

A customer's engagement patterns change (stops opening emails, doesn't log into app). This is both a churn risk signal and a delinquency risk signal.
A customer's payment timing becomes irregular. This suggests cash flow issues that warrant proactive support.
A customer suddenly increases balance utilization. This could indicate financial stress requiring early intervention.

Customer engagement teams see these signals first—but only risk teams traditionally act on them. Integration allows preventive action before accounts become problematic.

Better Risk Assessment Through Behavioral Data

Traditional risk models rely heavily on credit bureau data and payment history. But engagement behavior provides early warning signals that credit scores miss:

Communication Response Patterns: Customers who suddenly stop responding to communications are at higher risk
Self-Service Usage: Customers actively managing their accounts are lower risk than those who never log in
Payment Scheduling Behavior: Customers who proactively schedule payments show different risk profiles than those who pay reactively
Support Interaction Patterns: Customers asking questions about hardship programs are signaling potential payment issues

Integrating engagement data into risk models improves prediction accuracy by 20-30%.

Risk-Informed Engagement Optimization

Understanding a customer's risk profile should inform engagement strategy:

Low-Risk Customers: Minimal touchpoints, focused on convenience and efficiency
Moderate-Risk Customers: Proactive engagement with payment reminders and easy access to assistance
High-Risk Customers: Intensive support, flexible payment options, financial counseling resources

One-size-fits-all engagement wastes resources on low-risk customers while under-serving high-risk ones. Risk-informed segmentation optimizes resource allocation.

The Integrated Approach

Shared Data and Analytics

Create unified customer profiles that combine risk data and engagement data:

Payment history + engagement history
Credit score + behavioral score
Transaction data + interaction data
Risk triggers + engagement triggers

Collaborative Strategy Development

Risk and engagement teams should jointly develop strategies for key customer segments:

New customer onboarding that balances risk mitigation with welcoming experiences
Early delinquency intervention that prevents charge-offs while maintaining relationships
Credit limit management that considers both risk exposure and customer needs
Collections approaches that maximize recovery while preserving customer value

Unified Metrics

Develop metrics that reflect both risk and engagement objectives:

Customer Lifetime Value (CLV): Accounts for both revenue and risk
Recovery Rate with Retention: Measures collections success plus continued customer relationship
Early Intervention Success Rate: Tracks prevention of delinquency progression
Risk-Adjusted Engagement ROI: Measures engagement effectiveness by risk segment

Real-World Applications

Early Warning Systems

Integrated teams can build early warning systems that combine risk and engagement signals:

Customer X shows payment date volatility + declining app usage ? Trigger proactive outreach with payment flexibility options
Customer Y increases balance rapidly + opens emails but doesn't click ? Segment suggests financial stress with high engagement potential

Intelligent Collections

Risk data informs which customers to pursue aggressively versus which benefit from supportive engagement:

High Historical Payment Rate + Recent Delinquency: Likely temporary issue, engage supportively with payment plans
Poor Payment History + Low Engagement: Higher risk, more traditional collections approach may be appropriate

Dynamic Credit Policies

Engagement data can inform credit decisions:

Customers with strong engagement patterns may qualify for higher limits despite borderline credit scores
Customers with declining engagement might trigger proactive limit reductions before delinquency occurs

Implementation Roadmap

Phase 1: Data Integration

Identify key data points from both risk and engagement systems
Create unified customer data platform
Establish data governance and access protocols

Phase 2: Pilot Projects

Select specific use cases for integration (e.g., early delinquency intervention)
Form cross-functional teams from risk and engagement
Test integrated approaches with small customer segments
Measure impact on both risk and engagement metrics

Phase 3: Scale and Optimize

Expand successful pilots to broader populations
Develop integrated workflows and processes
Train staff on collaborative approach
Continuously refine based on results

Cultural Change

Technical integration is important, but cultural integration is critical. This requires:

Shared Goals

Establish objectives that both teams own jointly, such as "Reduce 90+ day delinquency by 25% while maintaining or improving NPS."

Regular Collaboration

Create standing meetings where risk and engagement teams review results, share insights, and jointly problem-solve.

Cross-Functional Training

Risk teams should understand engagement principles; engagement teams should understand risk management. Build empathy through education.

Reward Integration

Recognize and celebrate successes that result from risk-engagement collaboration. Make integration a path to advancement.

Measuring Success

Integrated risk-engagement strategies should improve multiple dimensions:

Risk Metrics: Lower delinquency rates, reduced charge-offs, improved early-stage recovery
Engagement Metrics: Higher customer satisfaction, improved retention, increased lifetime value
Efficiency Metrics: Lower cost per dollar recovered, reduced operational waste
Experience Metrics: Fewer complaints, higher trust scores, improved brand perception

The goal isn't to sacrifice one for the other—it's to improve both simultaneously.

Conclusion

Your risk department isn't just integral to your customer engagement strategy—it should be an active partner in designing and executing it. When risk management and customer engagement work together, organizations achieve something powerful: they protect the business while building customer relationships, reduce losses while improving experiences, and manage risk while growing value.

Breaking down the walls between risk and engagement isn't just good organizational design—it's a competitive necessity in a world where customer expectations and risk landscapes both evolve rapidly. The organizations that master this integration will lead their industries in both financial performance and customer loyalty.