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In recent years, electric vehicles (EVs) have been making a name for themselves as they continue to grow within the automotive industry, and as more models roll out, data in the fourth quarter of 2023 shows consumer interest continues to increase. According to Experian’s State of the Automotive Finance Market Report: Q4 2023, EVs comprised 8.6% of total new retail transactions, an increase from 7.1% in Q4 2022. Furthermore, the number of consumers who leased an EV jumped from 9.8% to 30.7% year-over-year, and the number of consumers who purchased EVs went from 61.9% to 44.8% in the same period. When analyzing how consumers transacted EVs in Q4 2023, it’s notable that leasing accounted for 91.1% of BMW iX transactions and 79.0% of BMW i4. Additionally, 78.0% of Nissan Ariya’s were leased this quarter, followed by the Volkswagen ID.4 at 74.5%, Hyundai IONIQ 6 (64.0%), and Kia EV6 (56.8%). !function(e,n,i,s){var d="InfogramEmbeds";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,"script","infogram-async","https://e.infogram.com/js/dist/embed-loader-min.js"); Alongside a wider range of models being introduced to the market, new incentive and rebate programs have drawn more consumers in as they look for a vehicle that fits their lifestyle and financial needs. This makes it crucial for automotive professionals to not only stay on top of these trends but also understand how other areas of the industry are evolving. Average loan amounts stabilize as interest rates rise Looking at the finance market at a broader level, the average loan amount for a new vehicle declined $1,143 year-over-year to $40,366 in Q4 2023, and the average loan amount for a used vehicle decreased from $27,907 last year to $26,685 this quarter. Meanwhile, the average interest rate for a new vehicle reached 7.2% in Q4 2023, up from 6.1% in Q4 2022—resulting in the average monthly payment increasing from $720 to $738 year-over-year. On the used side, the average interest rate went from 10.4% last year to 11.9% this quarter, leading to the average monthly payment slightly going up to $532, from $530 in Q4 2022. As interest rates continue to rise, it’s common to see more consumers opting for shorter-term loans to help alleviate monthly payments, a trend professionals should keep in mind as they assist those who are in the market for a vehicle. For instance, new vehicle loans up to 48 months increased from 10.9% in Q4 2022 to 13.8% in Q4 2023, and 49- to 60-month loan terms went from 16.9% to 18.3% in the same time frame. Meanwhile, 61- to 72-month terms slightly declined from 38.7% to 38.2%, and 73- to 84-month terms went from 32% to 28.2% year-over-year. On the other hand, used vehicle loan terms only experienced a slight shift—with loans up to 48 months increasing from 10.7% in Q4 2022 to 11.3% in Q4 2023 and 49- to 60-month loans going from 17.6% to 18.8% over the same period. Furthermore, 61- to 71-month terms slightly increased from 42.3% to 42.6%, and 73- to 84-month terms decreased from 28.7% last year to 26.5% this quarter. To learn more about automotive finance trends, view the full State of the Automotive Finance Market: Q4 2023 presentation on demand.

This article was updated on March 12, 2024. The number of decisions that a business must make in the marketing space is on the rise. Which audience to target, what is the best method of communication, which marketing campaign should they receive? To stay ahead, a growing number of businesses are embracing artificial intelligence (AI) analytics, machine learning, and mathematical optimization in their decisioning models and strategies. What is an optimization model? While machine learning models provide predictive insights, it’s the mathematical optimization models that provide actionable insights that drive decisioning. Optimization models factor in multiple constraints and goals to leave you with the next best steps. Each step in the optimization process can significantly improve the overall impact of your marketing outreach — for both you and your customers. Using a mathematical optimization software, you can enhance your targeting, increase response rates, lower cost per acquisition, and drive engagement. Better engagement can lead to stronger business performance and profitability. Here are a few key areas where machine learning and optimization modeling can help increase your return on investment (ROI): Prospecting: Advanced analytics and optimization can be used to better identify individuals who meet your credit criteria and are most likely to respond to your offers. Taking this customer-focused approach, you can provide the most relevant marketing messages to customers at the right time and place. Cross-sell and upsell: The same optimized targeting can be applied to increase profitability with your existing customer base in cross-sell and up-sell opportunities. Gain insights into the best offer to send to each customer, the best time to send it, and which channel the customer will respond best to. Additionally, implement logic that maintains your customer contact protocols. Retention: Employing optimization modeling in the retention stage helps you make quicker decisions in a competitive environment. Instantly identify triggers that warrant a retention offer and determine the likelihood of the customer responding to different offers. LEARN MORE: eBook: Debunking the top 5 myths about optimization Gaining insight and strengthening decisions with our solutions Experian’s suite of advanced analytics solutions, including our optimization software, can help improve your marketing strategies. Use our ROI calculator to get a personalized estimate of how optimization can lift your campaigns without additional marketing spend. Start by inputting your organization’s details below. initIframe('62e81cb25d4dbf17c7dfea55'); Learn more about how optimization modeling can help you achieve your marketing and growth goals. Learn more

This article was updated on March 11, 2024. As a lender, it’s important to understand a consumer’s credit behavior and whether it's improving or deteriorating over time. Sure, you can pull a credit score at any moment, but it's merely a snapshot. Knowing a consumer’s credit information at a single point in time only tells part of the story. Two consumers can have the same credit score, but one consumer’s score could be moving up while another’s score could be moving down. To understand the whole story, lenders need the ability to leverage trended data to assess a consumer’s credit behavior over time. What to know about trended data Trended data provides key balance and payment data for the previous 24 months. By analyzing historical payment information, lenders can determine if a consumer is consistently paying more than the minimum payment, has a demonstrated ability to pay, and shows no signs of payment stress. It can conversely identify if a consumer is making only minimum payments and has increasing payment stress. Experian’s Trended Data is comprised of five fields of historical payment information over a 24-month period. It includes: Balance Amount Original Loan / Limit Amount Scheduled Payment Amount Actual Payment Amount Last Payment Date Knowing how a consumer uses credit, or pays back debt over time, can help lenders offer the right products and terms to increase response rates, determine up-sell and cross-sell opportunities, and limit loss exposure. Using a consumer’s historical payment information also provides a more accurate assessment of future behavior, helping lenders effectively manage changes in risk, predict balance transfer activity, and prevent attrition. The challenge For lenders to extract the benefits of trended data, they need to analyze an enormous amount of data. Five fields of data across 24 months on every trade is huge and can be difficult for lenders with limited analytical resources to manage. For example, a single consumer with 10 trades on file would have upwards of 1,200 data points to analyze. Multiply that by a file of 100,000 consumers and you are now dealing with over 120,000,000 data points. Additionally, if lenders utilize the trended data in their underwriting processing and intend to use it to decline consumers, they need to create their own adverse action reason codes to communicate to the consumer. Not all lenders are equipped to take on this level of effort. Still, there are trended data solutions to assist lenders with managing and unlocking the power of trended data. How Experian can help Experian’s pre-calculated solutions allow even the smallest lenders to quickly and effectively action on the benefits of trended data, minus the hassles of analyzing it. Trended data, and the solutions built from it, allow lenders to effectively predict where a consumer is going based on where they’ve been. And really, that can make all the difference when it comes to smart lending decisions. Get started today


