The researchers, Maia Berkane, Diego Alvarez and Nico Tanzi, drew on the public Home Mortgage Disclosure Act database, a federal repository that lenders must populate with details on every application they receive, including the applicant’s race, ethnicity, income, loan amount and neighborhood characteristics. They restricted their sample to the most common borrowing profile: conventional, first-lien loans on one-to-four family homes intended for owner occupancy. After filtering out records with missing covariates, the dataset ranged from roughly 12,700 usable applications in 2017 to more than 18,500 in 2021, a scale that gives the statistical tests considerable power.

The methodological centerpiece is a logistic regression of loan denial on indicators for Black, Hispanic and Asian applicants, adjusted for every relevant variable the public data offers: loan amount, loan-to-income ratio, loan-to-value ratio, income, the minority share of the census tract, the tract’s income relative to the metropolitan area, the age of housing stock and the number of owner-occupied units. Because the public HMDA files omit the FICO credit score and the debt-to-income ratio, both of which lenders weigh heavily and both of which correlate with race, the authors treat these as unmeasured confounders and confront them head-on with a sensitivity analysis borrowed from epidemiology.

That tool, the E-value developed by biostatisticians Peng Ding and Tyler VanderWeele, quantifies the minimum strength of association, on the relative risk scale, that an unmeasured confounder would need with both the exposure and the outcome to fully explain away an observed association. In this setting, the exposure is membership in a minority group and the outcome is mortgage denial. For Black applicants, the E-value stayed above 4.0 in every single year of the study, peaking at 4.78 in 2017 and still standing at 4.45 in 2022. In plain terms, any hidden factor capable of dissolving the disparity would need to be linked to both being Black and being denied a loan by a relative risk of roughly fivefold each, over and above everything already controlled for.

The raw regression results are striking in their stability. The odds ratio for Black applicants ranged from 2.30 in 2021 to 2.67 in 2017, with confidence intervals whose upper bounds hovered near or above three throughout. Translated into more interpretable conditional marginal effects, the model implies that if every White applicant in the 2017 data had instead been Black, the denial probability would have jumped from about 8 percent to about 15.4 percent. By 2022 the corresponding counterfactual shift was from 5.8 percent to 11.0 percent. The average marginal effect for Black applicants in 2022 was 6.6 percentage points, a figure that lands almost exactly on the 7 percent Black-White denial gap reported by Giacoletti and colleagues using national data from 1998 to 2018, despite the difference in era and geography.

The contrast with other minority groups is instructive. Hispanic applicants saw their marginal effect fall from 7.4 percent in 2017 to a statistically insignificant 1.7 percent in 2020 before rebounding to 4 percent in 2022, while Asian applicants peaked near 8.7 percent in 2019 and declined to 2.9 percent by the end of the period. Their E-values, generally between 2.0 and 3.0, indicate gaps that are more vulnerable to explanation by unmeasured factors. The authors are careful to note that this does not mean discrimination against Hispanic or Asian applicants is absent; rather, the evidence for a causal interpretation is weaker, and available confounders may account for more of the observed difference.

The most compelling part of the paper is its attempt to test whether the FICO score, the most obvious candidate for a missing confounder, could plausibly do the explanatory work required. Using published data showing mean FICO scores of 677 for Black Americans and 734 for White Americans in 2021, the authors reconstructed the implied score distributions and calculated that the relative risk of having a score below 677 is about 2.4 for Black versus White Americans. That falls well short of the minimum of 3.40 needed, in combination with an assumed fivefold effect of low scores on denial, to neutralize the observed Black-White odds ratio of 2.3 in 2021. In fact, making the numbers work would require the low-score effect on denial to reach a relative risk of 35, which the authors describe as extremely large and implausible given that the minimum score for a conventional loan is 620.

These findings sit within a long and troubling research tradition. The landmark Boston Fed study by Munnell and McEneaney in the 1990s, which had access to confidential credit files, found Black and Hispanic applicants roughly 60 percent more likely to be denied; a more recent Federal Reserve analysis using automated underwriting data still found a residual 2 percent gap for Black applicants after controlling for credit scores and debt ratios. Studies of historic Homeowners’ Loan Corporation redlining maps have shown that neighborhoods graded as hazardous in the 1930s, typically those with high minority concentrations, still exhibit elevated lending bias today. Philadelphia itself carries a heavy institutional legacy: the Federal Reserve Bank of Philadelphia has documented that the city’s Black-White homeownership gap has barely narrowed in three decades, and recent enforcement actions, including a 2023 settlement in which ESSA Bank & Trust agreed to pay more than $3 million over a federal redlining lawsuit, show the problem is not merely historical.

The authors acknowledge the limits of their approach. Observational data of this kind is subject to selection bias, since applicants are not a random sample of the population, and to measurement error, and the public HMDA files simply do not contain everything a lender sees. The E-value, like the p-value, cannot prove causation on its own; it is a sensitivity metric, and its meaning depends on how strong the known confounders already are. But the authors argue that this is precisely the point: sensitivity analysis has been almost entirely absent from the mortgage discrimination literature, even though it is the central challenge for establishing causality in any observational study, and importing it from epidemiology gives fair lending researchers a way to express how robust their findings are to what the data cannot show.

The implications reach into policy. The authors suggest that the persistence of the Black-White gap, unchanged across six years of wildly different market conditions, points toward disparate impact operating through facially neutral underwriting thresholds on loan-to-value, loan-to-income and credit score criteria that lenders calibrate to minimize default risk but which may impose disproportionate barriers on Black applicants. If that interpretation holds, then closing the gap will require more than enforcing anti-discrimination statutes one lender at a time; it will require scrutinizing the threshold policies themselves, and, crucially, giving regulators and researchers access to the credit variables that have been missing from the public record for nearly fifty years.

Subject of Research: Racial disparities in mortgage lending decisions and sensitivity to unmeasured confounders in the Philadelphia metropolitan area

Article Title: Philadelphia then and now, disparities in mortgage lending and sensitivity to unmeasured confounders

Article References: Berkane, M., Alvarez, D., & Tanzi, N. (2026). Philadelphia then and now, disparities in mortgage lending and sensitivity to unmeasured confounders. Heliyon, 12(15), Article e45520. https://doi.org/10.1016/j.heliyon.2026.e45520

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45520

Keywords: mortgage lending, racial disparities, Philadelphia, HMDA data, E-value, unmeasured confounders, logistic regression, redlining, credit scores, fair lending, sensitivity analysis, homeownership gap

The technical backbone of this shift is the Energy Performance Certificate, or EPC, a document that has existed across the European Union since 2002. An EPC grades a building’s energy efficiency on a scale, and for years it functioned mainly as an informational tool for buyers and tenants. That changed in 2020, when the EU Taxonomy, the classification system that defines which economic activities count as environmentally sustainable, came into force. From that point on, the criteria for judging the greenness of buildings were anchored very heavily in EPC ratings, and banks began relying on those criteria to make green lending decisions. A high rating can open the door to green loans and somewhat more favourable financing terms, while a poor rating can push a property into a risk category that makes financing difficult or, in extreme cases, impossible.

The mechanism behind this is straightforward risk arithmetic. A property with a very low energy rating is likely to require significant energy renovations and other investments, and its value is expected to decline over time as regulations tighten and buyers increasingly discount inefficient stock. From a bank’s perspective, that combination of looming capital expenditure and depreciating collateral is unattractive. ‘In practice, a property with a very poor energy rating may not qualify for a loan at all, because banks may consider it too high-risk,’ says Maria Holopainen, a doctoral researcher at Aalto University. ‘Properties with a high energy rating that qualify for green lending may, in turn, receive somewhat more favourable financing terms than conventional loans.’ In other words, the EPC has become a de facto credit signal, one that most consumers do not realise is being read.

Seppo Junnila, Professor of Real Estate Economics at Aalto University and a co-author of the study, stresses that this is not a future scenario but a present reality. ‘For people taking out a mortgage, or considering buying a home, it is important to understand that the environmental performance of the property already affects banks’ lending decisions and loan terms,’ he says. His warning extends beyond energy performance. While the current focus of lenders is squarely on efficiency ratings, Junnila notes that in the longer term, access to more favourable financing is likely to depend on a wider range of environmental sustainability criteria, broadening the set of building attributes that can make or break a mortgage application.

The next frontier, according to the banking experts interviewed, is physical climate risk. Where transition risk, the risk associated with decarbonising the building stock, is currently measured largely through energy ratings, physical risk refers to the direct exposure of an asset to floods, wildfires, heat waves and other extreme weather events. The researchers found that banking professionals expect these hazards to become the next major factor affecting the financing of homes and other properties. Crucially, however, the perception of how severe and important these risks are varies enormously with geography. A bank’s assessment of a property’s climate exposure depends both on where the asset sits and on the region in which the bank itself operates, meaning that identical houses can face very different lending environments depending on their location.

Southern Europe illustrates the point vividly. ‘In southern Europe, climate risks, especially wildfires, heat waves and floods, already carry considerable weight, and there are concerns that they could create inequalities between different residential areas,’ says Holopainen. Recent severe flooding in Sweden has also raised awareness of these risks in the Nordic countries, a region long insulated from the worst physical impacts by its temperate climate. ‘The building stock in the Nordics is comparatively energy-efficient and therefore less likely to be exposed to transition risks than other parts of Europe,’ she explains. ‘However, physical climate risks may become more important in the near future.’ The implication is that the geography of mortgage risk is shifting: regions that scored well on transition metrics may find themselves newly exposed as insurers and lenders begin pricing in floods and fires.

Perhaps the most counterintuitive finding of the study concerns renovations. The European Union has set ambitious renovation targets, and from a sustainability perspective, upgrading existing buildings is widely regarded as far superior to demolition and new construction. ‘From a sustainability perspective, renovations are a far better option than new builds, in fact they are essential if we are to reach the agreed on climate targets and carbon neutrality by 2050,’ says Holopainen. ‘High-performing new buildings alone are not enough.’ Yet the current financial system pushes banks in the opposite direction, encouraging them to finance new properties rather than energy renovations of the existing stock, a structural contradiction that sits at the heart of Europe’s decarbonisation challenge.

The reason lies in the mechanics of the EU Taxonomy itself. New properties can achieve an A energy rating and therefore meet the criteria for being considered green with relative ease, which gives banks an advantage when they raise their own financing in the market, since green-labelled loan portfolios are increasingly attractive to investors. Financing renovations, by contrast, is riskier for banks, and reporting renovated properties as green is also technically more challenging, because the environmental benefit must be documented across a messier, project-by-project process rather than certified at completion. Holopainen argues that addressing this contradiction would require both stronger regulatory guidance and greater pressure from markets, investors and consumers to reward renovation lending rather than penalising it.

The study also reveals something about how banks are adapting to this changing landscape: reactively rather than proactively. The criteria for green lending are shifting, but institutions are largely responding to regulatory developments as they arrive rather than anticipating them. Banks cite the current geopolitical situation and regulatory uncertainty within the European Union, including uncertainty around the easing of sustainability reporting requirements, as obstacles to progress on sustainability in banking. This hesitancy matters because the direction of travel is clear even if the pace is not, and institutions that delay building expertise in climate-adjusted lending may find themselves repricing entire portfolios once physical risk data becomes standard in underwriting.

Underlying all of these findings is a distributional question that the researchers frame in stark terms. There is a real risk, Holopainen suggests, that expensive, energy-efficient and high-quality new homes will increasingly be bought by wealthy households and investors, while lower-quality and higher-risk properties are left to people who cannot afford more expensive homes. ‘This would mean that people who are already in a stronger financial position would be the ones benefiting from more favourable financing,’ she says. ‘The question is how to ensure that people in more vulnerable financial positions can also access sustainable homes.’ As energy ratings and, soon, climate risk scores become embedded in mortgage pricing, the housing market risks splitting into a green premium tier and a stranded, hard-to-finance remainder. For buyers, the practical takeaway is immediate: the environmental performance of a property is no longer a footnote in the purchase decision but a factor that can determine whether the purchase happens at all.

Subject of Research: The influence of building energy performance and physical climate risk on European residential mortgage lending

Article Title: Your home’s energy performance is already affecting your mortgage––soon climate risk will too

Article References: Your home’s energy performance is already affecting your mortgage––soon climate risk will too. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: mortgage lending, energy performance certificates, EU Taxonomy, green finance, climate risk, Aalto University, real estate, energy renovations, banks, sustainability, housing inequality, flood risk