{"id":50543,"date":"2026-05-20T20:21:56","date_gmt":"2026-05-20T17:21:56","guid":{"rendered":"https:\/\/mk.gen.tr\/lenders-wrestle-with-the-nuances-of-modern-credit-score-pricing\/"},"modified":"2026-05-20T20:21:56","modified_gmt":"2026-05-20T17:21:56","slug":"lenders-wrestle-with-the-nuances-of-modern-credit-score-pricing","status":"publish","type":"post","link":"https:\/\/mk.gen.tr\/en\/lenders-wrestle-with-the-nuances-of-modern-credit-score-pricing\/","title":{"rendered":"Lenders wrestle with the nuances of modern credit score pricing"},"content":{"rendered":"<p>Mortgage lenders are currently wrestling with a high-stakes puzzle: how to accurately compare the new credit score models hitting the market. The differences are significant and carry major implications for risk assessment, <a href=\"https:\/\/www.housingwire.com\/articles\/vantagescore-uwm-broker-loans\/\">loan pricing<\/a> and secondary market returns.<\/p>\n<p>In late April, the <strong>Federal Housing Finance Agency<\/strong> (FHFA) <a href=\"https:\/\/www.housingwire.com\/articles\/fhfa-vantagescore-pilot-gses-hud\/\">rolled out<\/a> a program allowing the exclusive use of <strong><a href=\"https:\/\/www.housingwire.com\/articles\/transunion-vantagescore-price-cut\/\">VantageScore<\/a><\/strong> 4.0 for loans delivered by a group of lenders to the government-sponsored enterprises (GSEs) <strong>Fannie Mae <\/strong>and <strong>Freddie Mac<\/strong>. The future use of <strong>FICO<\/strong> 10T will also act as an alternative to the long-standing FICO Classic. <\/p>\n<p>Not to be left behind, <strong>U.S. Department of Housing and Urban Development<\/strong> (HUD) Secretary <a href=\"https:\/\/www.housingwire.com\/tag\/scott-turner\/\">Scott Turner<\/a> signaled that <strong>Federal Housing Administration<\/strong> (<a href=\"https:\/\/www.housingwire.com\/articles\/fha-premiums-loan-fees\/\">FHA<\/a>) loans will also adopt these alternatives in the coming months.<\/p>\n<p>For now, lenders participating in the FHFA\u2019s rollout program have a temporary workaround. They\u2019re applying a 20-point cut from FICO to VantageScore to figure out where a loan should be priced in the grid. <\/p>\n<p>While <strong>United Wholesale Mortgage <\/strong>(<a href=\"https:\/\/www.housingwire.com\/articles\/uwm-in-house-ai-mortgage-underwriting-servicing\/\">UWM<\/a>) publicly announced this strategy, sources tell <strong>HousingWire<\/strong> it\u2019s actually the practice among other participating lenders. These lenders are also relying on multiple models to double-check accuracy and minimize risk.<\/p>\n<p><strong>Guild Mortgage<\/strong> has already started to compare how the same loan scores across all three models, but it\u2019s in the \u201cvery early stages of collecting this data,\u201d according to David Battany, the company\u2019s executive vice president for capital markets.<\/p>\n<p>\u201cWhen you see a delta between two models of 40 or 80 points, that\u2019s pretty significant,\u201d Battany said this week during a session on the new credit score models at the<strong> <\/strong><a href=\"https:\/\/www.housingwire.com\/articles\/mba-rollback-mortgage-rules-high-rates\/\"><strong>Mortgage Bankers Association<\/strong><\/a> (MBA)\u2019s Secondary and Capital Markets Conference in New York. \u201cWhen you think of Classic FICO, every 40 points of score equals a doubling of default rate.\u201d<\/p>\n<p>But default risk isn\u2019t the only curveball secondary market investors need to model. Economists warn that these new scores could trigger other unintended consequences.<\/p>\n<p>\u201cFor us, the prepaid risk is that you have a low FICO borrower, and he scores higher on Vantage, because most Vantage scores are a little bit higher,\u201d Jeana Curro, managing director and head of agency MBS research at <strong>Bank of America,<\/strong> said during a session on general market trends. \u201cThat creates a refi opportunity that you know would not be foreseen, would not be estimated by models.\u201d<\/p>\n<p>Curro stressed that the industry still has a \u201cway to go\u201d with implementation, as not everyone is fully prepared. In her opinion, <a href=\"https:\/\/www.housingwire.com\/tag\/imbs\/\">nonbanks<\/a> are driving the conversation, while traditional banks are being left behind.<\/p>\n<h2 class=\"wp-block-heading\">Tricky calibration<\/h2>\n<p>FICO and VantageScore themselves warned about the nuances between their models and the potential headaches of calibration.<\/p>\n<p>\u201cI wouldn\u2019t underscore it and make it sound too easy to do the calibration,\u201d said Ethan Dornhelm, head of scores analytics at FICO. \u201cCertainly, calibrations are possible, but we do see that there can be drift over time, and given that the two algorithms that are the modernized credit scores are different, they could drift slightly differently. So, it will be a case of not just calibrating one time and being done with it, but rather careful and close monitoring over time.\u201d<\/p>\n<p>VantageScore recommends probability-of-default mapping, saying that translation tables are straightforward.<\/p>\n<p>\u201cWhat we recommend doing is to basing it on the probability default, so you have the similar expected outcomes when you\u2019re looking at converting the scores, and we\u2019re about to provide some more data on that,\u201d said Rikard Bandebo, chief strategy officer and chief economist at VantageScore.<\/p>\n<p>Most lender systems are built around a single credit-score field. Adding a second introduces major operational and policy questions. A concern is with cherry-picking, since lenders might simply submit whichever score makes the loan look more affordable for the borrower and ignore the actual probability of default.<\/p>\n<p>\u201cWith regards to <a href=\"https:\/\/www.housingwire.com\/articles\/fhfa-score-change-gamification\/\">gaming<\/a>, there have been studies not commissioned by either FICO or Vantage that have expressed concerns that at a given score band, defaults may increase by as much as 30% if gaming runs completely amok, and we just don\u2019t know at this point what the dynamics are going to look like in this two-score lender choice setting, as far as how much gaming actually occurs,\u201d Dornhelm said.<\/p>\n<p>VantageScore downplayed these fears. Bandebo acknowledged that while the potential for gaming warrants study, research from <strong>Prosperity Now<\/strong> indicates that \u201cit\u2019s actually not going to increase the risk any more than the current system.\u201d<\/p>\n<h2 class=\"wp-block-heading\">Secondary market jitters<\/h2>\n<p>Lender adoption is only chapter one. The broader mortgage ecosystem \u2014 comprising warehouse lenders, secondary investors and other key players \u2014 has largely been in a \u201cwait-and-see\u201d holding pattern, sources say.<\/p>\n<p>In late April, <strong>Newrez<\/strong> originated <a href=\"https:\/\/www.housingwire.com\/articles\/freddie-newrez-vantagescore\/\">$10 million in mortgages<\/a> scored with VantageScore 4.0, which were then securitized by <strong>Freddie Mac<\/strong>. This pilot effectively helped federal housing agencies greenlight the broader use of modern credit scores.<\/p>\n<p>Bob Johnson, head of originations at Newrez, explained that Freddie Mac approached the company to see if it could \u201ctest the plumbing.\u201d Newrez was \u201cable to make those deliveries and fully test out the system,\u201d he said.<\/p>\n<p>But the secondary market was not fully tested, sources said. The first multilender GSE securitization containing VantageScore-underwritten loans totaled just under $8 million within an $11 billion pool, according to Dornhelm. He added that FICO reported one single-lender securitization under FICO 10T, with more expected in the home equity line of credit (<a href=\"https:\/\/www.housingwire.com\/articles\/the-rise-of-helocs-what-it-means-for-originators-in-todays-market\/\">HELOC<\/a>) space later this year.<\/p>\n<p>VantageScore counters by pointing to its proven track record outside the mortgage realm. The model already drives roughly 10% of asset-backed securities (ABS) issuance \u2014 including credit cards and personal loans \u2014 through major issuers like <strong>Synchrony <\/strong>and <strong>Toyota<\/strong>. Bandebo added that ratings agencies are ready and view the transition as manageable.<\/p>\n<h2 class=\"wp-block-heading\">Different models, some similarities<\/h2>\n<p>The <a href=\"https:\/\/www.housingwire.com\/articles\/fha-hud-credit-scores-llpa\/\">new score models<\/a> are similar to Classic FICO because they all predict the likelihood of default over a two-year horizon, use the 300-850 score range, and incorporate utility and telecom data when available.<\/p>\n<p>What makes them different is that both FICO 10T and VantageScore 4.0 use time-series balance, payment and utilization data rather than a single point-in-time snapshot. Both new scores factor in rental payment history \u2014 although less than 5% of files currently contain it, which represents a major growth area for financial inclusion. They are also built on more recent data and better reflect modern consumer behaviors.<\/p>\n<p>But points of contention remain. While FICO 10T builds bespoke models for each bureau, saying that it maximized their unique data, VantageScore 4.0 uses one algorithm across all three bureaus for score consistency.<\/p>","protected":false},"excerpt":{"rendered":"<p>Mortgage lenders are currently wrestling with a high-stakes puzzle: how to accurately compare the new credit score models hitting the market. The differences are significant and carry major implications for risk assessment, loan pricing and secondary market returns. In late April, the Federal Housing Finance Agency (FHFA) rolled out a program allowing the exclusive use&#8230;<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/posts\/50543"}],"collection":[{"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/comments?post=50543"}],"version-history":[{"count":0,"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/posts\/50543\/revisions"}],"wp:attachment":[{"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/media?parent=50543"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/categories?post=50543"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mk.gen.tr\/en\/wp-json\/wp\/v2\/tags?post=50543"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}