Kyle Matthies is the Senior Product Manager of Segmentation Solutions for Experian and manages a suite of propensity and profitability tools designed to help client optimize marketing and account review strategies. Prior to joining Experian, he was a Senior Strategy Analyst at Toyota Financial Services where he was responsible for managing targeted marketing campaigns to retain off-lease customers. Kyle holds an MBA from Texas A&M University and BA from the University of Colorado at Boulder.

-- Kyle Matthies

All posts by Kyle Matthies

What lenders can learn from their customers’ card transactions

Consumers swipe their credit cards at staggering rates, but drilling into how each individual uses their card can reveal telling details about their lifestyle and spend.

Published: November 1, 2017 by Kyle Matthies
How lenders can win with a data-driven credit marketing strategy

Many institutions take a “leap of faith” when it comes to developing prospecting strategies as it pertains to credit marketing. How can a data-driven approach help?

Published: August 1, 2017 by Kyle Matthies
Auto loan originations are slowing, now what?

For an industry that has grown accustomed to sustained year-over-year growth, recent trends are concerning. The automotive industry continued to make progress in the fourth quarter of 2016 as total automotive loan balances grew 8.6% over the previous year and exceeded $1 trillion. However, the positive trend is slowing and 2017 may be the first year since 2009 to see a market contraction. With interest rates on the rise and demand peaking, automotive lending will continue to become more competitive. Lenders can be successful in this environment, but must implement data-driven targeting strategies. Credit Unions Triumph Credit unions experienced the largest year-over-year growth in the fourth quarter of 2016, increasing 15% over the previous period. As lending faces increasing headwinds amid rising rates, credit unions can continue to play a greater role by offering members more competitive rates. For many consumers, a casual weekend trip to the auto mall turns into a big new purchase. Unfortunately, many get caught up in researching the vehicle and don’t think to shop for financing options until they’re in the F&I office. With approximately 25% share of total auto loan balances, credit unions have significant potential to recapture loans of existing members. Successful targeting starts with a review of your portfolio for opportunities with current members who have off-book loans that could be refinanced at a lower rate. After developing a strategy, many credit unions find success targeting these members with refinance offers. Helping members reduce monthly payments and interest expense provides an unexpected service that can deepen loyalty and engagement. But what criteria should you use to identify prospects? Target Receptive Consumers As originations continue to slow, marketing response rates will as well, leading to reduced marketing ROI. Maintaining performance is possible, but requires a proactive approach. Propensity models can help identify consumers who are more likely to respond, while estimated interest rates can provide insight on who is likely to benefit from refinance offers. Propensity models identify who is most likely to open a new trade. By focusing on these populations, you can cut a mail list in half or more while still focusing on the most viable prospects. It may be okay in a booming economy to send as many offers as possible, but as things slow down, getting more targeted can maintain campaign performance while saving resources for other projects. When it comes to recapture, consumers refinance to reduce their payment, interest rate, or both. Payments can often be reduced simply by ‘resetting’ the clock on a loan, or taking the remaining balance and resetting the term. Many consumers, however, will be aware of their current interest rate and only consider offers that reduce the rate as well. Estimated interest rates can provide valuable insight into a consumer’s current terms. By targeting those with high rates, you are more likely to make an offer that will be accepted. Successful targeting means getting the right message to the right consumers. Propensity models help identify “who” to target while estimated interest rates determine “what” to offer. Combining these two strategies will maximize results in even the most challenging markets. Lend Deeper with Trended Data Much of the growth in the auto market has been driven by relatively low-risk consumers, with more than 60% of outstanding balances rated prime and above. This means hypercompetition and great rates for the best consumers, while those in lower risk tiers are underserved. Many lenders are reluctant to compete for these consumers and avoid taking on additional risk for the portfolio. But trended data holds the key to finding consumers who are currently in a lower risk tier but carry significantly less risk than their current score suggests. In fact, historical data can provide much deeper insight on a consumer’s past use of credit. As an example, consider two consumers with the same risk score at a point in time. While they may be judged as carrying similar risk, trended data shows one has taken out two new trades in the past 6 months and has increasing utilization, while the other is consolidating and paying down balances. They may have the same risk score today, but what will the impact be on your future profitability? Most risk scores take a snapshot approach to gauging risk. While effective in general, it misses out on the nuance of consumers who are trending up or down based on recent behavior. Trended data attributes tell a deeper story and allow lenders to find underserved consumers who carry less risk than their current score suggests. Making timely offers to underserved consumers is a great way to grow your portfolio while managing risk. Uncertain Future The automotive industry has been a bright spot for the US economy for several years. It’s difficult to say what will happen in 2017, but there will likely be a continued slowing in originations. When markets get more competitive, data-driven targeting becomes even more important. Propensity models, estimated interest rates, and trended data should be part of every prescreen campaign. Those that integrate them now will likely shrug off any downturn and continue growing their portfolio by providing valuable and timely offers to their members.

Published: May 16, 2017 by Kyle Matthies
3 ways to enhance your credit marketing efforts

When you think of criteria for prescreen credit marketing, what comes to mind? Most people will immediately discuss the risk criteria used to ensure consumers receiving the mailing will qualify for the product offered. Others mention targeting criteria to increase response rates and ROI. But if this is all you’re looking at, chances are you’re not seeing the whole picture. When it comes to building campaigns, marketers should consider the entire customer lifecycle, not just response rates. Yes, response rates drive ROI and can usually be measured within a couple months of the campaign drop. But what happens after the accounts get booked? Traditionally, marketers view what happens after origination as the responsibility of other teams. Managing delinquencies, attrition, and loyalty are fringe issues for the marketing manager, not the main focus. But more and more, marketers must expand their role in the organization by taking a comprehensive approach to credit marketing. In fact, truly successful campaigns will target consumers that build lasting relationships with the institution by using the three pillars of comprehensive credit marketing. Pillar #1: Maximize Response Rates At any point in time, most consumers have no interest in your products. You don’t have to look far to prove this out. Many marketing campaigns are lucky to achieve greater than a 1% response rate. As a result, marketers frequently leverage propensity to open models to improve results. These scores are highly effective at identifying consumers who are most likely to be receptive to your offer, while saving those that are not for future efforts. However, many stop with this single dimension. The fact is no propensity tool can pick out 100% of responders. Layering just a couple credit attributes to a propensity score allows you to swap in new consumers. Simultaneously, credit attributes can identify consumers with high propensity scores that are actually unlikely to open a new account. The net effect is even higher response rates than can be achieved by using a propensity score alone. Pillar #2: Risk Expansion Credit criteria are usually set using a risk score with some additional attributes. For example, a lender may target consumers with a credit score greater than 700 and no derogatory or delinquent accounts reported in the past 12 months. But, most of this data is based on a “snapshot” of the credit profile and ignores trends in the consumer’s use of credit. Consider a consumer who currently has a 690 credit score and has spent the past six months paying down debt. During that time, utilization has dropped from 66% to 41%, they’ve paid off and closed two trades, and balances have reduced from $21,000 to $13,000. However, if you only target consumers with a score greater than 700, this consumer would never appear on your prescreen list. Trended data helps spot how consumers use data over time. Using swap set analysis, you can expand your approval criteria without taking on the incremental risk. Being there when a consumer needs you is the first step in building long-term relationships. Pillar #3: Customer profitability and early attrition There’s more to profitability than just originating loans. What happens to your profitability assumptions when a consumer opens a loan and closes it within a few months? According to recent research by Experian, as many as 26% of prime and super-prime consumers, and 38% of near-prime consumers had closed a personal loan trade within nine months of opening. Further, nearly 32% of consumers who closed a loan early opened a new personal loan trade within a few months. Segmentation can help identify consumers who are likely to close a personal loan early, giving account management teams a head start to try and retain them. As it turns out, many consumers use personal loans as a form of revolving debt. These consumers occasionally close existing trades and open new trades to get access to more cash. Anticipating who is likely to close a loan early allows your retention team to focus on understanding their needs. If you don’t, you’re competition will take advantage through their marketing efforts. Building the strategy Building a comprehensive strategy is an iterative process. It’s critical for organizations to understand each campaign is an opportunity to learn and refine the methodology. Consistently leveraging control and test groups and new data assets will allow the process to become more efficient over time. Importantly, marketers should work closely across the organization to understand broader objectives and pain points. Credit data can be used to predict a range of future behaviors. As such, marketing managers should play a greater role as the gatekeepers to the organization’s growth.

Published: January 19, 2017 by Kyle Matthies
Tis’ the season for hefty consumer credit card spending

The holidays can be a stressful time of year for consumers, and also an important time for lenders to anticipate the aftermath of big credit card spend.

Published: December 6, 2016 by Kyle Matthies
How lenders can use data to anticipate balance transfer activity

Experian estimates card-to-card consumer balance transfer activity to be between $35 and $40 billion a year, representing a sizeable opportunity for proactive lenders seeking to grow their revolving product line. This opportunity, however, is a threat for reactive lenders that only measure portfolio attrition instead of working to retain current customers. While billions of dollars are transferred every year, this activity represents only a small percentage of the total card population. And given the expense of direct marketing, lenders seeking to capitalize on and protect their portfolio from balance transfer activity must leverage data insights to make more informed decisions. Predicting a consumer’s future propensity to engage in card-to-card balance transfers starts with trended data. A credit score is a snapshot in time, but doesn’t reveal deep insights about a consumer’s past balance transfer activity. Lenders that rely only on current utilization will group large populations of balance revolvers into one bucket – and many of these individuals will have no intention of transferring to another product in the near future. Still, balance transfer activity can be identified and predicted by utilizing trended data. By analyzing the spend and payment data over time to see when one (or multiple) trade’s payment approximately matches another trade’s spend, we have the logic that suggests there has been a card-to-card transfer. What most people don’t realize is that trended data is difficult to work with. With 24 months of history on five fields, a single trade includes 120 data points. That’s 720 data points for a consumer with six trades on file and 72,000,000 for a file with 100,000 records, not to mention the other data fields in the file. It’s easy to see why even the most sophisticated organizations become paralyzed working with trended data. While teams of analysts get buried in the data, projects drag, costs swell, and eventually the world changes as rates climb and fall. By the time the analysis is complete, it must be recalibrated. But there is a solution. Experian has developed powerful predictions tools that combine past balance transfer history, historical transfer amounts, current trades carried and utilized, payments, and spend. Combined, these data fields can help identify consumers who are most likely to transfer a balance in the future. With Experian’s Balance Transfer Index the highest scoring 10 percent of consumers capture nearly 70 percent of total balance transfer dollars. Imagine the impact on ROI of reducing 90 percent of the marketing cost of your next balance transfer campaign and still reaching 70 percent of the balance transfer activity. Balance transfer activity represents a meaningful dollar opportunity for growth, but is concentrated in a small percentage of the population making predictive analytics key to success. Trended data is essential for identifying those opportunities, but financial institutions must assess their capabilities when it comes to managing the massive data attached. The good news is that regardless of financial institution size, solutions now exist to capture the analytics and provide meaningful and actionable insights to lenders of all sizes.

Published: August 1, 2016 by Kyle Matthies

It’s more than mercury that will be up this summer. As temperatures climb, so do automotive sales, which often reach annual highs during the warmest months of the year. Fueled by pent-up demand coming out of the recession, historically low interest rates, and increased competition among both manufacturers and lenders, auto sales are continuing to be a bright spot in the U.S. economy. Summer sales spike According to recent research by Experian Automotive, 2015 sales of new non-luxury vehicles began rising in May and peaked in August at nearly 20 percent above the monthly average for the year. It is not surprising, given the number of notable manufacturer marketing campaigns that often air through the summer months, beginning with Memorial Day and running all the way through Labor Day weekend. The projection is that this trend will continue in 2016. Financing moves metal Financing continues to play an important role in facilitating new car sales. Experian research shows a consistent increase in the percentage of new vehicles sold with financing with the trend reaching a period high of 85.9 percent in Q4 2015, a 2.3 percent increase over the previous year. The increased financing, is due in part, to continued post-recession liquidity. As the economy has rebounded, lenders have re-emerged with attractive financing rates for buyers. In addition, captive lenders are continuing to support manufacturers with 0 percent subvention offers to increase sales. Total loan value is on the rise as well, reaching $29,551 in Q4 2015, a 4.1 percent increase over the previous year. Average MSRP is trending up too, but at a slower year-over-year rate of 3.6 percent. The slower growth in MSRP relative to total loan value is leading to increased loan-to-value ratios which reached 109.4 percent in Q4 2015. The increases in loan value and MSRP are putting pressure on monthly payment with average new vehicle payments reaching $493 per month on new loans in the fourth quarter. Seeking relief, consumers are turning to longer loan terms and leasing to maintain lower payments. As a result, average new vehicle loan terms ticked slightly higher to 67 months while lease penetration on new vehicles reached 28.9 percent, a 19 percent increase over the previous year. Leveraging the trends Timing is everything when it comes to auto lending. Direct mail remains an effective communication tool for lenders, but mass mailers without regard to response rates yield poor ROIs and put future campaigns in jeopardy. Targeting consumers who are most likely to be in the market at a point in time can increase response rates and improve overall campaign performance. Experian’s In the Market Model – Auto leverages the power of trended credit data to identify consumers that will be most receptive to an offer. By focusing on high-propensity consumers, lenders can conduct more marketing campaigns during the year with the same budget and achieve supercharged results. Context-based marketing allows lenders to tailor offers by leveraging insights on a consumer’s existing loans. Product offers can additionally be customized based on estimated interest rates, months remaining, or current loan balance on open auto loans. Targeted refinance offers can also be delivered to consumers with high interest rates or focus new-loan offers on consumers with minimal months or balance remaining on existing loans. Understanding current auto loans allows lenders to target offers that are relevant to their prospects and gain an advantage over the competition. Increases in loan-to-value (LTV) ratios at origination and longer loan terms are putting many consumers in deep negative equity positions. As a result, many consumers will not qualify for refinance offers without significant down payments leading to low underwriting conversion rates and poor customer experience. Lenders seeking to improve on these metrics should leverage Experian’s Auto Equity Model, which provides an estimate of the amount of equity a consumer has in their existing auto trades. Focusing refinance offers on consumers with negative equity, while suppressing those with deep negative positions, can help improve response rates while minimizing declines due to LTV requirements. Takeaways Lenders should be gearing up for the summer auto sales spike. Proactive strategies will allow savvy marketers to deploy capital and grow their portfolio by taking advantage of customer insight. Timing and context matter, and as auto sales trends reveal, now is the opportune time to optimize marketing efforts and capitalize on the season.

Published: June 8, 2016 by Kyle Matthies
Trends suggest summer season will see spike in auto sales

As temperatures climb, so do automotive sales, which often reach annual highs during the warmest months of the year. 

Published: June 8, 2016 by Kyle Matthies

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