By Devon Kinkead

A recent auto loan refinance campaign focused on new customer acquisition provides valuable analytical insights that can directly enhance conversion rates and win rates. By adopting a comprehensive, 360-degree view of the data, lenders can identify specific opportunities to improve competitive positioning in the market.

The Power of Multi-Dimensional Analytics

The campaign results demonstrate how analyzing data across multiple dimensions simultaneously reveals optimization opportunities that single-variable analysis would miss:

Figure 1 – Conversion rate by loan origination amount

Figure 2 – Share of total loans originated by prescreened prospects by loan origination amount

Figure 3 – Conversion rate by FICO score band

Figure 4 – Share of total loans originated by prescreened prospects by FICO band

Figure 5 – Conversion rate by prospects’ income

Figure 6 – Share of total loans originated by prescreened prospects’ income

Figure 7 – Conversion rate by prospects’ Debt to Income Ratio (DTI) x 100

Figure 8 – Share of total loans originated by prescreened prospects’ DTI x 100

Key Insights

• Higher income segments ($150k+) show dramatically better conversion rates (0.59%-0.82%)
• Premium FICO scores (800+) demonstrate 50% better conversion than average
• Larger loan amounts ($50k-$100k) convert at 0.49% – nearly double the campaign average
• Multi-dimensional targeting (combining high FICO, income and loan amount) can yield 3x better results
• DTI optimization shows best performance in the 40-50 range at 0.35% conversion

Building Systematic Improvement Through Analytics

A comprehensive analytics approach enables continual refinement through these strategies:

1. Progressive Optimization Model: Each campaign iteration can be treated as a controlled experiment, with results feeding directly into predictive models that continuously improve targeting precision.
2. Competitive Gap Analysis: Rate differential data between won and lost applications (6.60% vs. 7.80%) provides clear competitive positioning insights. Understanding this spread across segments highlights specific competitive advantages.
3. Cost-Per-Acquisition Efficiency: Multi-dimensional analytics allows precise calculation of acquisition costs by segment, enabling resource allocation to the most efficient channels and borrower profiles.

Implementation Framework for Competitive Advantage

Financial institutions implementing 360-degree analytics approach can achieve systematic improvement by:

1. Creating segment-specific value propositions based on comprehensive performance data
2. Implementing dynamic and compliant pricing strategies calibrated to competitive position by segment
3. Establishing near real-time performance monitoring across all variables
4. Leveraging artificial intelligence to improve next campaign specification based on what is now known and design experiments to discover what is not known with statistical certainty.

By applying these data-driven insights consistently across campaigns, lenders can expect measurable improvements in conversion rates, win rates, and portfolio quality. The analytics clearly demonstrate that understanding the interplay between multiple factors – rather than optimizing for individual variables in isolation – provides a significant competitive advantage.

This approach transforms new customer acquisition through lending from an occasional campaign activity into a continuously optimized process, driven by comprehensive data intelligence.

Get a demo of Micronotes’ smarter prescreen capabilities.

By Devon Kinkead

The difference between a profitable and unprofitable acquisition campaign often comes down to data intelligence. Prescreened credit offers remain one of the most powerful tools for acquiring new customers, but many institutions are still shooting in the dark. The convergence of artificial intelligence and rich credit data is revolutionizing how financial institutions can systematically improve their conversion rates and win rates.

The Challenge: Turning Lost Opportunities into Wins

Financial institutions face a common frustration: sending thousands or millions of prescreen offers only to see disappointing conversion rates. Take a recent auto loan refinance campaign we analyzed:

• 9,845 offers were distributed
• 8 loans acquired (0.08% conversion rate)
• 398 customers chose competitors (4.12% total conversion)
• 1.97% win-rate in the prescreen list (8 loans won/(398 loans lost +8 loans won))
• Break-even return on investment

These numbers reveal millions in lost revenue opportunities and thousands of potential accountholder relationships that never materialized.

The AI-Powered Approach to Prescreen Marketing

Here’s how forward-thinking financial institutions are using AI and credit data to transform their acquisition strategies:

1. Pattern Recognition Beyond Human Capability

Traditional analysis might segment customers by basic credit score bands or geographic regions. AI systems, however, can identify complex patterns across hundreds of variables simultaneously. These systems can detect subtle correlations between:

• Credit score fluctuation patterns over time
• Specific combinations of credit utilization and debt-to-income ratios
• Geographic and competitive influences on rate sensitivity
• Loan characteristic preferences based on past borrowing behavior

By analyzing actual win/loss data from previous campaigns, AI can identify which specific factors influenced a prospect’s decision to accept or reject offers—insights that would be impossible to discern through conventional analysis.

2. Predictive Modeling with Back-Testing

The true power of AI in prescreen marketing lies in its predictive capabilities combined with back-testing for human review:

• Predictive Targeting: AI can predict which prospects are most likely to respond positively to specific offer terms.
• Counter-Factual Analysis: For each lost sale, AI can model “what if” scenarios to determine which adjusted offer terms would have improved the odds of winning a particular customer and why.
• Strategy Simulation: Before launching a modified campaign, AI can simulate expected results based on historical response patterns.

In a recent analysis, we used AI to identify three strategic adjustments to an auto refinance campaign. Our models predicted these changes could increase the win rate from 1.97% to 6.00%—more than tripling the campaign’s win-rate and corresponding lender competitiveness.

3. From Broad Segments to Individual-Level Personalization

Traditional prescreen campaigns operate at the segment level—everyone in a particular credit band receives roughly the same offer. AI enables a shift toward truly individualized offers while remaining compliant with FCRA/UDAAP regulations and fair lending laws.

Real-World Strategy Development: A Case Study

To illustrate the power of this approach, consider how AI can transforms a lender’s auto refinance strategy:

1. Data Integration: We combined the lender’s prescreen campaign data with detailed information on lost sales, including which sales were lost at what terms.
2. Pattern Discovery: AI analysis revealed three critical insights:
   • High-FICO borrowers (700+) were extremely sensitive to rate differences as small as 0.5%
   • Large loans (>$30,000) had materially different success factors than smaller loans
   • Certain geographic markets showed unique competitive dynamics requiring tailored approaches
3. Strategy Development: Based on these insights, the AI recommended three specific strategies:
   • Tiered rate adjustments for high-FICO borrowers
   • A specialized fast-track program for loans over $30,000
   • Geographic-specific incentive bundles for high-competition markets
4. Back-Testing Validation: Before implementation, each strategy was back-tested against historical data, confirming that these approaches would have converted more specific lost opportunities into wins.
5. Implementation Roadmap: The final output included a detailed implementation plan with projected ROI for each strategy component.

Back-Testing Results: Turning Theory into Wins

The true power of AI-driven strategy development is the ability to back-test recommendations against actual prospect data. Below are 9 examples from the lender’s lost sales data that demonstrate exactly how each proposed strategy would have improved the odds of converting specific lost sales into wins:

Moving Beyond Intuition to Data-Driven Certainty

The most significant shift in this AI-powered approach is moving from intuition-based marketing to data-validated and back-tested strategies. Every recommendation is backed by concrete examples from your own prospect portfolio—specific customers who would have a higher probability of converting with the proposed changes.

This approach doesn’t just drive higher conversion rates; it creates a continuous learning system where each campaign becomes smarter than the last. Your marketing doesn’t just improve incrementally—it evolves strategically even if every recommendation isn’t immediately implemented.

The Future of Prescreen Marketing

As AI systems become more sophisticated and regulatory frameworks evolve, we’re moving toward an agentic future with:

• Real-Time Offer Optimization: Adjusting offer terms dynamically as market conditions shift.
• Cross-Product Intelligence: Using insights from one product line to enhance targeting in others.
• Regulatory Compliance Automation: Ensuring all personalized offers meet FCRA/UDAAP and fair lending requirements.
• Behavioral Economics Automation: Ensuring that offers are optimized for the way people make choices.

Getting Started with AI-Powered Prescreen Marketing

For financial institutions looking to harness these capabilities, the journey begins with asking better questions of your data:

1. Don’t just measure campaign success—analyze your failures at an individual level
2. Capture and integrate competitive intelligence on lost opportunities
3. Look beyond basic credit metrics to multidimensional patterns
4. Invest in back-testing capabilities to validate strategies with humans before deployment
5. Build a continuous learning loop between campaigns

The financial institutions that thrive in the coming decade won’t just be those with the largest marketing budgets—they’ll be the ones that use AI and credit data most intelligently to identify and convert the right prospects with the right offers at the right time.

In a world where basis points of market share translate to millions in revenue, the competitive edge gained through AI-powered prescreen marketing isn’t just valuable—it’s essential. Talk to Micronotes today about the future of prescreen marketing.

By Joe Heller

Credit unions are constantly searching for efficient ways to grow their loan portfolios while managing costs. One strategy stands out for its effectiveness: prescreening — the practice of making pre-approved credit offers to qualified members and prospects. However, the traditional prescreening process is labor-intensive and often yields conversion rates that leave significant room for improvement.

That’s where Micronotes Automated Prescreen changes the game. Our analysis reveals a compelling truth: any credit union that prescreens today or plans to prescreen should use Micronotes. Here’s why.

The Economics Are Undeniable

Our ROI analysis demonstrates that even a minimal improvement in conversion rates delivers substantial returns. Consider these numbers from our recent analysis:

• Current average prescreen conversion rate: 0.25%
• Automated prescreen annual cost: $100,000 (excluding data and direct mail pass-throughs)
• Average net income per loan: $3,000
• Typical annual prescreen volume: 100,000 offers

With these figures, the math becomes straightforward:

The Breakeven Point Is Remarkably Low

A credit union needs just 33.3 additional funded loans annually to cover the cost of Micronotes. This translates to a required conversion rate increase of just 0.03% — moving from 0.25% to 0.28%.

Let that sink in. If your credit union is planning to send 100,000 prescreen offers this year, you need only 33 more of those offers to convert to loans to completely cover the cost of automating and optimizing your entire prescreen operation.

The Realistic Returns Are Substantial

Based on our experience and data, credit unions implementing Micronotes Automated Prescreen typically see conversion rate improvements of 0.10% or higher. At this conservative estimate:

• New conversion rate: 0.35% (up from 0.25%)
• Additional annual revenue: $300,000
• ROI: 300% (a 3x return on investment)

And this calculation doesn’t even account for the reduced labor costs and operational efficiencies gained by automating your prescreen process. It also doesn’t cover programmatic improvements in conversion rates through win-rate analytics.

Beyond the Numbers: Strategic Benefits

The ROI analysis tells a compelling financial story, but the benefits extend beyond dollars and cents:

1. Team Efficiency: Your marketing and lending teams can focus on higher-value strategic activities rather than managing prescreen campaigns.
2. Data-Driven Optimization: Our platform continuously analyzes performance data to refine targeting and messaging, steadily improving conversion rates over time.
3. Simplified Compliance: Our automated system helps ensure consistent compliance with regulatory requirements.
4. Enhanced Member Experience: More relevant offers delivered at the right time lead to higher member satisfaction.

Is Automated Prescreen Right for Your Credit Union?

If your credit union does any of the following, Micronotes delivers clear value:

• Currently runs prescreen campaigns (regardless of size or frequency)
• Plans to implement prescreen marketing in the near future
• Wants to grow loan volume through targeted hyper-personalized marketing
• Seeks to improve efficiency of existing marketing operations

If your strategy relies heavily on other channels like indirect lending or general marketing platforms, Micronotes may not be your primary solution. But for any credit union with prescreen as part of its growth strategy, the business case is clear.

The Bottom Line

The data doesn’t lie: a 0.03% increase in conversion rate covers your costs. A realistic 0.10% improvement delivers a 3x return on investment. With Micronotes, you’re not just hoping for better results—you’re investing in a proven system that delivers measurable ROI while freeing your team to focus on what matters most.

For credit unions serious about growing their loan portfolios efficiently, Automated Prescreen isn’t just a nice-to-have—it’s a financial imperative.

Ready to see how Automated Prescreen can transform your credit union’s marketing efficiency and ROI? Contact us today for a personalized analysis based on your specific portfolio and goals.

By Devon Kinkead

Financial institutions are constantly searching for more effective ways to identify high-value opportunities and connect with qualified borrowers and people need their help. The HELOC debt consolidation opportunity represents one of the most promising avenues for growth given both record credit card debt and home equity, but executing these campaigns efficiently has traditionally required significant resources and expertise.

The Evolution of Prescreen Marketing

The concept of finding mispriced debt is compelling, but the execution has historically been challenging. Financial institutions needed to manually coordinate between credit bureaus, marketing teams, and compliance departments to create effective prescreen campaigns. This cumbersome process often resulted in generic offers that failed to capture consumer attention.

Enter automated prescreen technology – a game-changing approach that transforms how financial institutions target both existing customers and prospects with personalized HELOC consolidation offers.

How Automation Powers Hyper-Personalization

Modern automated prescreen solutions leverage advanced algorithms and real-time data access to create truly personalized HELOC offers. Here’s how the technology makes hyper-personalization possible:

1. Comprehensive Data Integration

Micronotes Automated Prescreen combines multiple data sources:

• Credit bureau data on 230+ million consumers (updated weekly)
• Property values and equity positions
• Current loan terms and interest rates
• Financial institution’s core data
• Underwriting criteria and rate sheets

This integration allows for precise identification of consumers with mispriced debt who could benefit from HELOC consolidation.

2. Financial Personalization That Drives Results

Rather than generic “You’re pre-approved” messaging, automated prescreen enables specific offers like:

“John, you can refinance your $40,639 debt from 19.890% to 8.642% and stop overpaying $280 per month in interest.”

This financially personalized approach leverages behavioral economics principles to demonstrate concrete value, resulting in higher conversion rates and win rates for loans.

3. Geotargeting Built Into the Process

The system automatically applies geographic filters to ensure targeting remains focused on prospects within the financial institution’s footprint. This ensures branch proximity for people who prefer in-person interactions while maximizing operational efficiency and brand recognition.

4. Multi-Channel Delivery for Maximum Impact

Once identified and personalized, offers can be delivered through multiple channels with friction-reducing calls to action:

• Custom branded email
• Direct mail with personalized tables and charts
• Digital banking re-presentment
• QR codes for easy response

5. Compliance Built Into the Workflow

Perhaps most importantly, Automated Prescreen handles the complex regulatory requirements for firm offers of credit, ensuring all communications include required disclosures and follow FCRA and UDAAP rules.

The Business Case for Automated Prescreen

For financial institutions considering HELOC debt consolidation campaigns, automated prescreen technology delivers compelling benefits:

1. Reduced Manual Effort: Automation handles the complex data analysis and offer generation that would otherwise require significant staff resources.
2. Negative Acquisition Costs: The net interest income from successful HELOC consolidations typically exceeds campaign costs, creating a self-funding growth engine.
3. Expanded Market Share: Target qualified prospects who don’t currently have a relationship with your institution.
4. Increased Wallet Share: Identify existing accountholders who hold high-interest debt with competitors, bringing those relationships to your institution.
5. Continuous Optimization: Performance tracking shows which offers resonate best, allowing for ongoing refinement rather than one-off campaigns.

Moving Forward: From Concept to Campaign

Implementing a successful HELOC debt consolidation campaign using Automated Prescreen doesn’t require massive internal resources or years of data science expertise. Micronotes’ cloud-based solution provide the technology infrastructure while financial institutions maintain control over targeting criteria, offer parameters, and brand presentation.

The campaigns can support multiple loan types simultaneously, including:

• HELOC/HELOAN consolidation
• Traditional HELOC/HELOAN
• Auto loan refinance
• Personal loan consolidation
• Mortgage new home purchase

Take the Next Step

If you’re interested in capturing the huge HELOC debt consolidation opportunity within your footprint, it’s time to explore how Automated Prescreen can transform your marketing approach and deliver the numbers, this year.

Order your own growth analysis today or book a demo to learn how you can start acquiring and retaining more profitable relationships through Micronotes. In a market where every advantage matters, Automated Prescreen may be the differentiator your institution needs.

By Devon Kinkead

As Americans grapple with historically high credit card debt—totaling over $1.2 trillion—while simultaneously holding a staggering $35 trillion in home equity, financial institutions are sitting on a golden opportunity. The solution? Leveraging home equity to consolidate high-interest credit card debt.

The Credit Card/Home Equity Gap: A Strategic Lending Opportunity

The numbers tell a compelling story:

• Credit card APRs currently average 21.59%
• Home equity loan rates typically range from 6-10%
• Consolidating $10,000 in card debt to an 8% home equity loan can save borrowers up to $13,716 over 10 years

With 65% of U.S. households owning homes with average equity of $313,000—even a modest home equity withdrawal could eliminate their card debt multiple times over.

Enter: Micronotes Automated Prescreen

Micronotes’ Automated Prescreen platform transforms this opportunity from theory to execution. Using Experian’s Ascend database of 230+ million consumer credit records updated weekly, the platform dynamically identifies accountholders and prospects who:

• Carry high-interest credit card debt with competing lenders
• Own homes with sufficient equity to consolidate that debt affordably
• Meet creditworthiness criteria for a firm offer of credit

This approach delivers personalized, FCRA-compliant offers across digital channels—including in-app, online, SMS, and email.

Why This Matters Now

1. Timing Is Critical: Many Americans feel squeezed by rising prices and interest rates. Offering them a way to cut monthly payments through consolidation meets an urgent need.
2. Relationship Deepening: Helping customers improve their financial health enhances trust and loyalty, increasing wallet share and retention.
3. Revenue Generation: Institutions can drive profitable, secured lending growth with lower default risk compared to unsecured credit.
4. Always-On Engagement: Automated Prescreen campaigns run continuously, adapting to updated credit and pricing data for real-time marketing precision.

Real Results

Financial institutions using Micronotes’ Automated Prescreen report higher conversion rates, net negative acquisition costs, and an understanding of how to improve the competitiveness of their offers in target markets meaning, in the end, the income from new loans increasingly exceeds the cost of campaigns. By targeting only the most relevant, credit-qualified customers with personalized offers, marketing dollars go further, faster, with less marketing labor.

Final Thoughts

The convergence of record-high consumer debt and record-high home equity presents a once-in-a-generation opportunity for banks and credit unions to gain market share and wallet share. With Micronotes’ Automated Prescreen, financial institutions can act now—at scale and with precision—to help customers take control of their financial lives, while generating profitable loan growth.

Ready to turn this macroeconomic challenge into a strategic advantage? Let Micronotes help you prescreen smarter, not harder. Schedule your demo today!

By Devon Kinkead

Introduction

In the world of prescreen marketing, success is often measured by conversion rates. However, focusing solely on conversion rates can provide a misleading picture of a campaign’s effectiveness. The true measure of success is not how many leads a campaign converts but how well it performs against competitors in capturing market share. A recent personal loan campaign serves as a prime example of why the win-rate against competitors is the most critical performance indicator.

The Reality Behind Conversion Rates

A Micronotes’ client’s recent new accountholder personal loan acquisition campaign distributed 15,000 firm offers of credit, resulting in 24 funded loans totaling $372,000. This equates to a conversion rate of just 0.16%. While this number might seem low, the true challenge lies in the fact that competitors secured 155 loans from the exact same audience, totaling $3MM. These figures highlight the need to shift the focus from conversion rate to the campaign’s competitive performance.

Understanding Win Rate: A Competitive Perspective

Win rate measures the share of the market captured relative to the competition. In the case of the referenced campaign, the 24 acquired loans represent only 13% of total funded loans from firm offer recipients, significantly below the benchmark set by our highest performing clients of 23%. This gap underscores the importance of enhancing strategic efforts to outperform competitors.

Key Insights from the Campaign

1. Competitive Loan Rates Matter:
   • The average offered rate for acquired loans was 13.5%, while lost loans averaged 13.4%. Although the difference appears minor, further analysis revealed that competitors offered significantly lower rates to higher FICO score borrowers, resulting in lost opportunities in micro credit cells.
2. Loan Amounts Influence Decisions:
   • The average funded loan size was $15,493, compared to the average lost loan size of $19,420. This suggests that competitors are successfully capturing demand for higher loan amounts, an area we can optimize.
3. Geographic Performance Highlights Opportunities:
   • One city showed strong performance with 4 funded loans, whereas another city had 14 lost loans totaling $292,778 with zero acquisitions. This reveals important geographic differences in competitiveness.

Boosting Win Rate

1. Refining Rate Tiers:
   • Introduce more competitive pricing for high-FICO segments to capture prime borrowers who are currently choosing lower-rate competitors.
2. Expanding Loan Size Offerings:
   • Align loan offerings with market demand by increasing loan limits to match competitor offerings and borrower expectations.
3. Targeted Marketing Strategies:
   • Concentrate efforts on high-potential suburban areas and high-loss urban centers with incentives.
4. Incentive Programs:
   • Introduce cashback or rate discount incentives to attract borrowers who are price-sensitive and value additional perks.

Conclusion

The campaign data highlights a crucial lesson: success is not just about conversions, it’s about outperforming the competition. By focusing on improving win rates through competitive pricing, tailored loan offerings, and strategic marketing efforts, financial institutions can capture a larger share of the market and achieve sustainable growth. In today’s competitive landscape, the ultimate goal should always be to win more business than the competition, not just convert an comparatively arbitrary number of firm offers sent into loans. Connect with us today to get your competitive context right!

By Devon Kinkead

The financial services sector faces constant pressure to adapt, innovate, and keep customers engaged. But how do you not only attract new customers but also ensure they stay loyal in an increasingly competitive landscape?

During our recent Gain and Retain webinar, we unpacked actionable insights to tackle this challenge, weaving technology, personalization, and strategy into a framework for success. Let’s break it down.

Deposits Are More Elusive Than Ever

Financial institutions are grappling with two critical issues: attracting new customers and keeping the ones they already have. In today’s environment, consumer expectations for personalized services are high, yet loyalty remains fragile. Bank data reveals that more than 50% of large deposits are withdrawn within 90 days without proactive engagement​.

How can banks and credit unions close the gap between their services and what customers need during pivotal life moments?

Partnering for Smarter Solutions

Micronotes has stepped up with innovative tools designed to address these challenges head-on. By leveraging vast data sets, predictive analytics, and hyper-personalized outreach, Micronotes helps financial institutions anticipate customer needs and deliver tailored solutions right when they matter most.

For example, Micronotes’ Accountholder Retention solution uses machine learning to identify at-risk customers and initiate automated, meaningful conversations within mobile banking apps​. Similarly, Prescreen Acquire deploys hyper-personalized prescreen campaigns to connect with creditworthy prospects and accountholders using geotargeting and 230MM consumer credit records, updated weekly​. Exceptional Deposits identifies unusually large deposits and immediately reaches out to depositors through the digital banking channels to offer help during major life events.

Engage at Scale with Personalization

1. Understand Your Customers’ Moments That Matter
   Life events like buying a home, consolidating debt, or receiving a windfall are critical opportunities to build trust. Micronotes identifies these moments through its Exceptional Deposits program, which flags large deposits and automatically connects accountholders with relevant services​.
2. Turn Data into Actionable Insights
   By analyzing millions of data points, Micronotes’ tools predict accountholder behaviors and needs, enabling financial institutions to act proactively, not reactively. Whether it’s cross-selling products, retaining an accountholder ready to leave, or acquiring new creditworthy accountholders, the results are transformative.
3. Scale Conversations Without Losing the Personal Touch
   Traditional marketing may start one conversation at a time. Micronotes’ Cross-Sell achieves 26x the click-through rate of banner ads by engaging accountholders in interactive dialogues tailored to their specific situations​.

Real Results, Real Growth

Micronotes customers are already reaping the rewards of Micronotes’ gain and retain approach, from acquiring new accountholders at a profit, to expanding wallet share, to retaining depositors and their deposits. It’s a powerful combination.

Step Into the Future of Banking

2025 is the year to stop losing opportunities to competitors with outdated systems and thinking. Let Micronotes help you gain new customers and retain the ones who already trust you.

By Devon Kinkead

Personal loans and HELOCs (Home Equity Line of Credit) play unique roles in consolidating debt to lower borrowing costs. Through an analysis of recent data on Direct and Indirect Sales across different financially personalized firm offers of credit, an interesting pattern emerges: personal loan consolidation offers overwhelmingly result in direct loans, whereas HELOC offers often lead to indirect loans. This blog will explore the reasons behind this trend, provide insight into offer strategy, and explain what it means for financial institutions.

Direct vs. Indirect Sales: Definition

Let’s first define terms:

• Direct Sales: These occur when a loan matches the type of loan offered to the credit-qualified consumer. For example, if a consumer is offered a personal loan and they accept and secure that exact loan, it counts as a direct sale.
• Indirect Sales: These happen when the loan does not match the original offer made to the consumer, despite them being credit-qualified for the initial offer. In this case, the consumer is offered one loan type but ultimately secures a different loan product, leading to an indirect sale.

Figure 1 – Septermber 2024 Micronotes sales attribution data, relationship between offer name and direct vs. indirect loan booked ($)

The Comparison: Personal Loans vs. HELOCs

In the dataset analyzed, personal loan consolidation offers, such as PCL (Personal Consolidation Loan), almost exclusively result in Direct Sales. Out of 402 total personal loan consolidations, nearly all are direct except 14, or 3%.

Conversely, HELOC offers, such as HELOC Consolidation and HELOC Traditional, show a different pattern. For example, in the HELOC Traditional offer, there are 11 direct sales but 22 indirect sales, meaning more consumers who received HELOC offers ended up securing a different loan product.

Why Do Personal Loan Consolidation Offers Result in Direct Loans?

1. Simplicity and Familiarity: Personal loans are straightforward financial products. Consumers understand that a personal loan is a fixed amount with a predictable interest rate and repayment schedule. Since the offer clearly aligns with their needs, credit-qualified consumers typically accept it without exploring alternatives, leading to a direct sale.
2. Tailored to Immediate Needs: Personal loan consolidation offers are highly targeted, focusing on consumers looking to consolidate multiple debts or pay off high-interest credit card debt. Because the product directly addresses the consumer’s immediate financial concerns, they are more likely to accept the offer as-is.
3. Urgency of Debt Consolidation: Consumers seeking personal loan consolidation are often under pressure to resolve their debt quickly. A personal loan provides a direct, efficient solution to consolidate debt and lower borrowing costs, which aligns well with their need for quick relief leading to a direct sale.

Why Do HELOC Offers Often Result in Indirect Loans?

1. Complexity of Home Equity Products: HELOCs are more complicated than personal loans. These products involve leveraging home equity, often with variable interest rates, which introduces more risk and complexity. As a result, consumers may start by considering a HELOC but then explore different financial options, leading to an indirect sale.
2. Consumer Preferences for Simpler Products: Although all consumers in this dataset were pre-qualified for the HELOC offers they received, many still opted for a different loan product. This may occur because other products, like a home equity loan or cash-out refinance, may feel like a safer or simpler choice. Ultimately, even though they were credit-qualified for the HELOC, consumers often choose a product that better aligns with their financial comfort level.
3. Loan Switching: After reviewing the terms and complexities of a HELOC, some consumers may realize that a different product, such as a fixed-rate home equity loan, might better meet their needs, particularly if they prefer a predictable payment structure. This switch from the original offer results in an indirect sale.

Implications for Offer Strategy

Given these observations, financial institutions can refine their strategies for both personal loan and HELOC offers to increase the likelihood of direct sales, an measure of product offer fit, and better serve their customers, members, and prospects.

For Personal Loan Consolidation Offers:

• Maintain Simplicity and Targeting: The success of personal loan consolidation offers in achieving direct sales lies in their simplicity and precise targeting. Financial institutions should continue to focus on clear, easy-to-understand offers that address specific consumer needs like debt consolidation to lower borrowing costs.
• Streamline the Application Process: Ensuring a seamless, user-friendly application process can help maintain the high rate of direct conversions. Offering tools like instant approval for prescreened offers could further increase consumer confidence in accepting the offer directly.

For HELOC Offers:

• Provide Upfront Education: Since HELOCs are more complex, providing consumers with clear, easy-to-understand information about the product’s benefits and potential risks can increase the number of direct sales. Educating consumers on when a HELOC is the right choice can yield more direct conversions.
• Offer Alternative Home Equity Products: Given that many consumers who are offered a HELOC end up with a different product, lenders can benefit from bundling HELOC offers with other home equity options, such as a home equity loan or cash-out refinance. By presenting these alternatives upfront, institutions can meet consumer needs without driving them to intermediaries.

Personalization of Offers: As the data shows, consumers often opt for a loan type that fits their immediate needs and financial comfort. Financial institutions should use advanced data analytics to personalize offers, ensuring that each product offered resonates with the specific financial situation of the consumer. This strategy improves conversion rates for both direct and indirect sales.

Figure 2 – Example of financial personalization in a firm offer of credit.

Conclusion: Different Products, Different Sales Journeys

The contrast between personal loan consolidation and HELOC offers reveals the differing levels of consumer understanding and comfort with these financial products. Personal loan consolidation offers are simple, targeted, and address immediate needs, resulting in a comparatively high rate of direct sales. In contrast, HELOCs, with their complexity and reliance on home equity, often lead consumers to explore other options, driving up indirect sales.

For consumers, the key takeaway is to carefully assess the offers they receive, ensuring that the product they choose fits their long-term financial goals. For lenders, understanding these trends can help optimize their offer strategies. By refining how they present HELOC and personal loan products, financial institutions can increase both direct and indirect sales while better serving their customers, members, and prospects.

Ultimately, a more tailored, flexible, and educational approach to prescreen marketing will lead to greater consumer satisfaction and more effective loan conversions.

By Devon Kinkead

Vertically-integrated automated prescreen marketing systems are finding their way into community banking with obvious, and not so obvious returns. A review of 20 campaigns Micronotes’ customers ran reveals that 68% of the loan volume is in indirect sales; that is — an existing or prospective accountholder was offered one loan, like a HELOC, but originated a different loan, like a mortgage. Given the sheer volume of indirect loans, they represent an important but overlooked component of the return on investment analysis.

Direct Versus Indirect Sales

Direct Sales: These are the sales directly attributed to the prescreen marketing campaign. For example, a prescreen offer for a HELOC consolidation loan was made to a prospect on February 1st, 2024 and a HELOC loan was originated on February 24, 2024.

Indirect Sales: These are the sales indirectly attributed to the prescreen marketing campaign. For example, a prescreen offer for a HELOC consolidation loan was made to a prospect on February 1st, 2024 and a mortgage was originated on April 24, 2024.

Key Data Insights

Figure 1 – Direct vs. Indirect closed loan volume across different offer types. Note: no data for rent-to-own because this was a small scale test campaign.

Indirect sales vary by offer type, with indirect sales materially exceeding direct sales in HELOCs and auto loan refinancing and entirely absent in auto lease-to-own and HELOAN consolidation. Personal loan offers show relatively few indirect sales while mortgages show a significant fraction of indirect sales.

Summarily, return on investment computations must included indirect sales to accurately reflect the real net interest income generated by a prescreen loan campaign, particularly with HELOCs, auto loan refinance, and mortgages.

Conclusion

Understanding the real benefit of automated prescreen marketing requires a comprehensive dataset, excellent analytics, and a good working knowledge of probabilities. Micronotes has developed a vertically-integrated automated prescreen marketing tool that enables community financial institutions to launch campaigns and comprehensively measure the return on campaigns and understand the unique characteristics of each prescreen offer type. Armed with this knowledge, Micronotes’ customers continue to invest wisely to acquire new borrowers and expand wallet share with existing accountholders.

By Devon Kinkead

As we navigate the complexities of the economic landscape in 2024, understanding consumer credit trends is paramount for financial institutions, policymakers, and consumers alike. A recent presentation by Andrew Robbins, a Solution Consultant at Experian at the June 2024 Micronotes Gain and Retail Forum, offers a comprehensive overview of these trends and their implications. Here, we delve into the key insights from this presentation.

Economic Update

Despite a slowdown in the first quarter of 2024, the overall economic outlook remains robust, with a forecasted growth of 2% for the year. The Bureau of Economic Analysis and Experian’s Macroeconomic Scenarios Report highlight that underlying demand measures are strong, indicating resilience in the economy.

Job Market and Inflation:

• Job Creation: After a dip in April, job creation rebounded in May, maintaining a solid labor market with minimal projected increases in unemployment.
• Inflation: Although inflation remains a challenge, with the Consumer Price Index showing stubbornly high rates, there is an expectation of a rate cut by the Federal Reserve in late 2024 and several more in 2025.

Consumer Behavior:

• Savings and Spending: Consumers have depleted some of their pandemic savings but still have substantial net worth and manageable debt burdens. This suggests room for continued spending, which is crucial for economic stability.

Consumer Credit Trends

The presentation provides a detailed analysis of various aspects of consumer credit, underscoring significant trends and their implications.

Credit Card Balances and Scores:

• Balances: Credit card balances have surged by nearly 12% over the past two years, with non-mortgage balances rising by over 11%. This indicates increased consumer reliance on credit for purchases.
• Credit Scores: The average credit score remains relatively stable, but there are slight year-over-year variations.

Generation-Specific Insights:

• Gen Z: This generation has shown a notable increase in credit card spending, especially during the holiday season. Their card balances and usage patterns are becoming a significant factor in the overall credit landscape.

Account Balances and Delinquencies:

• Total Balances: There has been a steady increase in total account balances, despite the number of accounts remaining constant. This suggests higher spending or borrowing per account.
• Delinquencies: Delinquencies have risen slightly, with balances 30+ days past due increasing by 70 basis points over two years.

Hard Inquiries:

• Trends: Hard inquiries for credit have decreased overall compared to the previous five years, particularly in mortgage and bankcard sectors. However, there has been an uptick in personal loan and auto loan inquiries in 2024 compared to the previous year.

Prescreen vs. ITA Campaigns

The presentation also touches on marketing strategies, specifically the use of prescreening versus Invitation to Apply (ITA) campaigns in direct mail marketing. There has been a strategic shift towards ITA campaigns due to their cost-effectiveness and alignment with current economic conditions and budgetary constraints.

Direct Mail Volume:

• Trends: Although there was a slight decrease in overall direct mail volume in recent months, Prescreen mail volumes remain at about 400MM per month while ITAs hover around 150MM per month.

Conclusion

The insights from Experian’s presentation provide a valuable snapshot of the current state of consumer credit in the United States. Despite economic challenges, consumers continue to spend, albeit with increasing reliance on credit. Financial institutions must navigate these trends carefully, balancing growth opportunities with the risks associated with higher consumer debt levels. Understanding these dynamics is crucial for making informed decisions in today’s complex financial landscape.