All posts by Scott Hamlin

Colorado has a great deal to offer first-time homebuyers (FTHBs). While the Denver area attracts many people with its combination of outdoor recreation, culture, and economic opportunities, other parts of Colorado are worthy of attention as well. Take Colorado Springs for example – it ranks third among best places to live in the U.S. when considering lifestyle, the job market, and overall popularity.1 Overview of the Colorado FTHB market Colorado accounts for 2.15% of all U.S. first-time homebuyers, according to Experian Housing’s recent first-time homebuyer report. This figure puts Colorado in the top 20 of all states across the country. Colorado's charm holds a special appeal for younger generations. Known for its wealth of enriching experiences, Colorado naturally attracts adventure-seekers. With an array of outdoor activities like hiking and skiing, it's no wonder that Generation Y and Generation Z make up 75% of all first-time homebuyers in the state, surpassing the national average of ~70%. Affordability With three-quarters of all FTHBs in the younger market segments, affordability is a key consideration in buying a home as housing costs are a significant part of an individual or family’s overall cost of living.2 What determines affordability? Affordability can be assessed through various metrics. For the purposes of this study, Experian Housing defined affordability by calculating the rent-to-mortgage ratio (RTM). This involves comparing monthly rent payments to monthly mortgage payments. A higher rent-to-mortgage ratio suggests renters may find mortgage payments more feasible, potentially making home buying a more appealing option. Comparison of rent costs to mortgage costs What we observed: Based on the RTM ratio, home buying is most affordable in Colorado Springs, Pueblo, and Castle Rock, while renting may look more attractive in Lakewood, Fort Collins, and Arvada. Additional measures to consider: Other realities play a key role in determining what is affordable. A prospective homebuyer’s income, monthly expenses, downpayment funds available, and the cost of the rent or mortgage payment as an added expense against income, factor heavily in final decision-making. In this regard, Experian Housing examined other metrics for assessing affordability. Debt-to-income What we observed: Down payments Sample of CO data observations: (High, mid, low down payments) Sale prices and income What we observed: Experian Housing examined the median sales prices and median incomes across the U.S. This metric is useful to see how much of one’s income typically is going to housing costs in a given area, which again, impacts overall cost of living. Comparison is essential because while sales prices may be higher in a given area, correlation with income helps determine affordability. A closer look at Colorado Springs Colorado Springs ranks #1 in affordability based on Experian’s research, and its status of best affordable place to live considering overall living costs, jobs, and livability is solid.4 The younger generation is the fastest growing population in Colorado Springs. Colorado Springs is expected to be the largest city in the state by 2050 given its current rate of growth and expansion.5 In addition to its five military installations, with a huge U.S. Air Force presence, key job sectors include the larger defense industry, education, technology, and manufacturing. Affordability coupled with opportunity and lifestyle suggest Colorado Springs deserves a closer look and area mortgage lenders have a lot to tout. Experian’s data system offers unique value to lenders given the ability to take a more comprehensive look at a borrower’s financial behavior. Experian uses credit, property, rental, and other alternative data sources to capture the borrower profile. Access to such data also gives Experian a unique ability to conduct research for reports like this one, and the recent reports on Texas and Florida. For more information about the lending possibilities for first-time homebuyers, download our white paper and visit us online. Download white paper Learn more 1 US News & World Report: Best Places to Live in the US 2024-2025 https://realestate.usnews.com/places/rankings/best-places-to-live 2 https://stg1.experian.com/blogs/insights/top-destinations-for-first-time-homebuyers/ 3 Arvada, Lakewood and Castle Rock, part of the Denver Metro Area and what is popularly known as the Front Range Urban Corridor, also have price to income ratios of 2.8%. 4 https://www.sofi.com/best-affordable-places-to-live-in-colorado/ 5 Colorado Springs Chamber & EDC, coloradospringschamberedc

As a mortgage lender, understanding the intricacies of the New York housing market is crucial, especially when dealing with first-time homebuyers (FTHBs). While the housing market fluctuates nationwide, New York presents unique challenges and opportunities that require a nuanced approach. Distinguishing NYC from the rest of New York New York City's housing market, along with its suburbs, stands distinct from the rest of the state. With a high cost of living and unique lifestyle, NYC demands a tailored mortgage marketing strategy. This article will highlight key factors affecting affordability in New York, providing valuable insights for mortgage lenders working in this market. Overview of the New York FTHB market According to Experian Housing’s recent report on first-time homebuyers, the state of New York accounts for nearly 4.9% of all first-time homebuyers nationwide.1 More than half of first-time homebuyers are from Generation Y. When combined with Gen Z, these younger buyers make up just over 67% of the state's FTHBs, a figure slightly below the national average of 69%. Affordability metrics: The rent-to-mortgage ratio For many Americans, homeownership represents stability, security, and the future for family, community, and life. However, the decision to buy versus rent often hinges on affordability. Mortgage lenders must understand this dynamic to better assist their clients. Affordability can be defined in various ways. For the purposes of this study, Experian Housing defined affordability by comparing rental and mortgage payments, known as the rent-to-mortgage ratio (RTM ratio). A higher ratio indicates that buying a home is more economically attractive. Again, this metric does not consider incomes and debt levels, but simply housing rental prices and mortgage costs. Based solely on the RTM ratio, the transition from renting to homeownership may be more attractive in New York City, Syracuse, and Oyster Bay, while the transition may be more difficult in Cheektowaga, Amherst, and Hempstead. For mortgage lenders, understanding local markets and buyer profiles is essential. Building trust through personalized service, such as educating buyers on relevant loan programs and showcasing geographic expertise, can set you apart. With this knowledge, you can help buyers make informed decisions about affordability, whether they prefer living in the city or the suburbs. In some areas, the suburbs may offer more affordable options, while in others, the city center might be more cost-effective. Additional factors: Income, debt, and down payments Affordability extends beyond just rent and mortgage payments. Prospective homebuyers must consider their income, monthly expenses, and access to funds for a down payment. Mortgage lenders need to account for these factors when advising first-time homebuyers. Debt-to-income Average DTI across the 14 cities observed was 25.6%. The chart below highlights those at the higher and lower end of the spectrum. Down payments Down payments varied greatly, but the median across the cities observed was 16.5%. The chart below highlights an example at the high, mid, and low point. Sale prices and income Experian Housing analyzed median sales prices and incomes across the U.S., with New York serving as a prime example of the importance of this comparison in assessing affordability. This correlation is crucial; while sales prices may be high, understanding how they align with local incomes helps lenders accurately gauge market dynamics and guide buyers more effectively. In conclusion, having a deep understanding of the New York housing market is invaluable for mortgage lenders aiming to support first-time homebuyers. By leveraging insights into market dynamics, affordability metrics, and borrower profiles, lenders can offer tailored advice that meets the specific needs of their clients. This not only helps buyers navigate the complexities of homeownership but also builds lasting trust and loyalty. Equipped with these insights, you, as a lender, can play a pivotal role in making the dream of homeownership a reality for first-time buyers in New York. Let's continue to empower our clients with the knowledge and guidance they need to make informed and confident decisions in their homebuying journey. For more insights, check out our recent studies on the Florida and Texas markets and download our first-time homebuyer whitepaper. Download white paper Learn more

At Experian, we believe in fostering innovation and collaboration to solve complex challenges. Recently, Ivan Ahmed, one of our talented product management leaders at Experian Housing, had the opportunity to participate in the FHFA 2024 TechSprint, where his team won the award for the best Risk Management and Compliance idea. In this article, we share Ivan's experience as he reflects on the TechSprint, the inspiration behind his team's project, and the valuable lessons learned. Can you share your experience participating in the FHFA 2024 TechSprint? What was the atmosphere like, and how did it feel to be recognized for the best Risk Management and Compliance idea? Let me start by explaining what a TechSprint is. It is a fast-paced, high-energy collaborative workshop where diverse experts and stakeholders come together to design technological solutions to complex problems. Each team is given a high-level problem and use case. From there, stakeholders and domain experts must develop a proof of concept within 3 days to best address the problem. On the last and final day, called the “Demo Day,” teams must showcase their solution in front of a panel of judges. It’s a fun, high-energy, challenging, and rewarding experience. A TechSprint is a convergence of everything I love – technology, business, and design and I think FHFA did a wonderful job orchestrating the event. Each team consisted of representatives from different functions in the housing ecosystem, including lenders, technologists, product managers, and regulators. We were given access to a room, whiteboards, and, most importantly, delicious snacks. We were also given access to industry subject matter experts outside our teams, including representatives from Fannie Mae and Freddie Mac, FHFA, and leaders from top companies. What I found the most impactful was the ability to pressure test our ideas and solutions against these industry subject matter experts. Ideating in a vacuum can be challenging, so being able to stress test things rapidly with these experts allowed us to change course quickly as new information was introduced. Winning the best Risk Management and Compliance idea award was rewarding, especially as we were able to ideate a solution to such a critical accessibility issue. Ultimately, our goal was to help create a fairer, more equitable, and inclusive housing finance system. A big shoutout to my teammates, Wemimo Abbey, Joseph Karbowski, Will Regenauer, and Eddy Atkins. What inspired Team Arsenal to focus on identifying potential gaps in ADA compliance within multifamily buildings, and what were some of the key challenges your team faced during the process? My mother has suffered from several disabilities most of her life. With age, she has become more wheelchair-dependent, and traveling has become a major challenge. On a recent family trip, the entry to our hotel building wasn’t ADA-compliant, and I had to carry her up a flight of stairs. It was frustrating to deal with. I later went down a rabbit hole around ADA compliance and, much to my surprise, learned that only 0.15% of all homes in the U.S. are wheelchair accessible! As we explored the problem space further as a team, we learned how difficult it is to ensure that new and existing rental homes are ADA-compliant. We hypothesized that a solution is needed to establish incentives for borrowers, lenders, and GSEs to meet compliance. A technological solution could more easily enable multi-family lenders and builders to identify rental units that are non-ADA compliant and could provide ways to address the gaps. We noticed two primary challenges: an enforcement gap and an incentive gap. We learned that agency loans (Fannie Mae and Freddie Mac) account for most multi-family home loan originations. If we could tackle the enforcement challenge at the GSE level, we could set up the proper incentives for all players in the multi-family lending process. By providing tools to both the borrower and the GSE’s, we could help foster a more inclusive and accessible rental housing market. How do you envision your AI-driven solution impacting the rental housing market and improving ADA compliance for multifamily buildings? We wanted to ensure that we leveraged the true power of Generative AI, which meant that our solution could take multimodal inputs and produce multimodal outputs. For example, we could train the Generative AI model on photos of interior multi-family rental units and structured or unstructured text like building sketches, site layouts, and local building codes. We could then incorporate ADA design requirements and analyze discrepancies. The result would be a compliance report or tool outlining the adherence level to ADA design requirements and providing tips and recommendations on remediation. The solution could be delivered as a free tool by the GSEs, who could incentivize its usage by offering price concessions to borrowers. Developers could also use the tool to evaluate whether new or existing builds were ADA-compliant. How did your background and experience with Experian contribute to developing your team's winning idea at the FHFA TechSprint? Much of my role at Experian has involved exploring ways to leverage proprietary and public record property data for marketing, account review, and analytical use cases. I work very closely with property data at Experian, so I was very familiar with the types of input fields of property data that would be the most relevant to improving a generative AI model output. Specifically, in our use case, we wanted to train the model to better identify homes and features that were non-compliant with ADA and provide clear remediation steps. We knew that public record property information was available from various sources and could be leveraged as additional third-party input data to improve our model accuracy. What advice would you give to other teams or individuals looking to participate in future TechSprint events, especially those aiming to tackle complex issues like risk management and compliance? It’s important to remember that an ideal solution is both impactful and practical. Practicality is achieved when the solution has both business and technical viability. Therefore, it’s crucial to carefully vet problems and solutions by understanding their viability. Working as a team to solve the problem means leveraging the expertise of subject matter experts around you. Each team member should draw on their strengths, making the collective effort stronger than individual contribution. Most importantly, fairness, inclusivity, and accessibility matter. An effective solution should strive to have a positive social impact in addition to other considerations. Winning with purpose Ivan’s journey through the FHFA 2024 TechSprint exemplifies the innovative and collaborative spirit that drives our team at Experian. His reflections highlight the impact of well-designed technological solutions on critical issues like ADA-compliance in multifamily housing. We hope Ivan’s experience inspires others to explore their potential in solving complex problems and to participate in future TechSprints, where innovative thinking and a commitment to social good can lead to meaningful change.

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