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Adverse market events can affect credit supply not only by hurting financial fundamentals but also by changing the risk-taking behaviors of individual decision-makers. We provide micro-level evidence of this individual decision-making channel in the U.S. mortgage market. We find that mortgage application rejection rates are more sensitive to foreclosure intensity when loan officers are more exposed to foreclosure news, despite the same housing market and bank fundamentals. Loans originated from the affected branches have lower ex post default rates, consistent with higher lending standards being applied. In the aggregate, this effect results in tighter credit supply during housing market downturns. [ABSTRACT FROM AUTHOR]

The paper analyses the Loss Given Default (LGD) rates of residential mortgages, using a model based on stochastic collateral value. The implementation of the model is based on exponential Ornstein-Uhlenbeck processes fitted to the Hungarian regions' house price indices. According to the model results, in case of a mortgage with a 80% loan-to-value ratio at origination, the expected LGD is around 30–40%, depending on the region. The highest LGD rates are estimated for villages, while the lowest rates are expected in Budapest and cities in the middle of the country. The range of the regional differences can reach 7 percentage points. According to the LGD Risk index based on the aggregated model, the LGD risk profile of recently issued mortgages has improved significantly since 2009 in Hungary. Due to the strong negative relation between the house prices and mortgage default rates, the expected return on defaulted collateral value tends to be low. The results could be relevant for credit institutions in their mortgage origination decisions and enhance analysis of lending processes and the associated risks. [ABSTRACT FROM AUTHOR]

The article explores the impact of credit availability on house prices in the Irish residential market, particularly in the context of the global financial crisis of 2007/08. It discusses the increase in mortgage credit and house prices before the crisis, as well as reforms in credit availability and regulations. The study uses a model to analyze the relationship between credit standards and house prices, providing insights that may be relevant to other EU member states. The findings suggest that recent house price increases in Ireland could be influenced by changes in credit conditions, underscoring the importance of monitoring this relationship for financial stability. The collection of academic articles and reports delves into various aspects of housing markets, credit conditions, and economic cycles, with a focus on Ireland and the UK, offering valuable insights for policymakers and researchers interested in understanding housing market dynamics and macroeconomic trends in these regions. [Extracted from the article]

AbstractThis article provides direct evidence of the role of housing in central banks’ monetary policy decisions through the examination of the minutes of the Reserve Bank of Australia Board (RBA) and the UK’s Monetary Policy Committee (MPC). It focuses on three periods when economic shocks necessitated monetary policy activism: the Global Financial Crisis, the Covid-19 pandemic and the subsequent inflationary resurgence. It enhances understanding of the monetary transmission mechanism by identifying the role of lender behaviour which contributed to the adoption of Quantitative Easing by the MPC; and of the ‘leaning against the wind’ debate by revealing the RBA’s view on rising house prices as a bulwark against mortgage default and financial instability. However, it also reveals these central banks’ underdeveloped understanding of the role of rental housing, and challenges the fragmentation of fiscal and monetary policy between elected governments and independent central banks. [ABSTRACT FROM AUTHOR]

The interest rate hikes intended to combat inflation have not only significantly increased mortgage payments, but also significantly depressed house prices. The probability of default for mortgages is typically estimated through the debt servicing ability of the obligor. The alternative estimation based on the default option, although well studied in literature, is typically not used by practitioners. This option is normally 'deep out of money' and moves in the money if the loan to value (LTV) increases significantly, even creating negative equity. This is typically a remote probability due to the down payment requirements, but not as much under the current environment, where the house price depreciation has significantly increased LTVs, especially for newer mortgages underwritten when house prices were at their peak. This paper discusses the potential risk management oversights in this environment, illustrating that the increasing default risk is not adequately captured in probability of default (PD) models based on debt servicing ability alone. This is also true for the loss given default (LGD) risk if the contemporaneous LTV effects are not captured. Numerical examples are provided to demonstrate the material increase in PD, LGD and the combined expected loss risk with increasing LTV. It also discusses an alternative default option PD model, its calibration and its usage for stress testing along with LGD modelling, which together capture the contemporaneous LTV effects. [ABSTRACT FROM AUTHOR]

Using the Credit Risk Transfers (CRTs) issued by Fannie Mae and Freddie Mac, we study how, absent government intervention, mortgage markets would price hurricane risk. Currently, such risk is priced equally across locations even if it is location‐specific. We hand collect a novel and detailed database to exploit CRTs' heterogeneous exposure to Hurricanes Harvey and Irma. Using a diff‐in‐diff specification, we estimate the reaction of private investors to hurricane risk. We use the previous results to calibrate a model of mortgage lending. We simulate hurricane frequencies and mortgage default probabilities in each US county to derive the market price of mortgage credit risk, that is, the implied guarantee fees (g‐fees). Market‐implied g‐fees in counties most exposed to hurricanes would be 70% higher than inland counties. [ABSTRACT FROM AUTHOR]

This study explores the drivers and consequences of consumers' voluntary information disclosure in the context of online consumer financing. Using unique secondary data from a Chinese online consumer financing company, we uncover a non‐linear relationship between borrowers' credit ratings and the quantity of voluntary information disclosure, and an inverted U‐shaped relationship between the amount of information disclosure and loan default. Specifically, low‐credit borrowers who opt for more voluntary information disclosure manifest a higher likelihood of default than those who disclose less, suggesting a strategic inclination toward information disclosure. Finally, we identify that disclosing high‐cost information reduces loan default, whereas disclosing low‐cost information increases default. Our findings enrich the existing literature on consumer information disclosure by providing insights into the underlying motivation and highlighting the applicability of signaling theory and privacy calculus theory. This has practical implications for lenders, borrowers, and regulators in overcoming barriers in online lending. [ABSTRACT FROM AUTHOR]

We conducted a survey experiment in the U.S. to analyze how the consent or dissent of a deceased individual influences the social acceptability of digital resurrection. The results showed a substantial relative treatment effect of consent versus dissent, with a 2-point difference in acceptability on a 5-point scale. When the deceased had consented, 58 % of respondents viewed digital resurrection as socially acceptable, whereas this number was only 3 % when the deceased had dissented. These findings suggest that relevant legal regulations should respect the decision of the deceased. Our study then explored the optimal default rule using observational research: 59 % of respondents were against the idea of their own digital resurrection. An opt-in rule seems socially desirable, where the default is the prohibition of digital resurrection, and exceptions allow it only with consent from the deceased. [ABSTRACT FROM AUTHOR]

The determinants of mortgage default have been an area of rising interest since the 2008 recession. There are two distinguishing features of mortgage default analysis. First, predictor variables are often only recorded at origination. However, many important variables such as credit scores vary over time. Second, there are omitted variables (such as borrower's income and job security). If omitted variables are correlated with included regressors or if only origination values are used in a dynamic model, then biases may be present in econometric models for default risk. Our focus is to develop a ridge regression model to impute the dynamics of time-varying predictors and to capture unobserved borrower heterogeneity. The model is evaluated using cross-validation, and the relevant parameters are tuned to maximize out-of-sample predictive performance. After allowing for imputed dynamics and borrower heterogeneity, we find that the loan-to-value ratio becomes a larger signal of default risk and that credit scores as well as full documentation become smaller signals of default risk. These changes primarily are driven by imputing static variables, rather than dynamics, and may pertain to either omitted liquidity factors or strategic factors. [ABSTRACT FROM AUTHOR]

Joint liability aspires to improve micro‐loan performance through the support of, and pressure from, the group borrowers. This paper examines how the group composition, in terms of the mixture of kinship (Family) ties and social (Friends and Neighbours) ties among the borrowers, affects the default rates. Using binary logistics regression and three machine learning models, responses from 507 group micro‐loan borrowers from four major Moroccan cities were analysed. The results show that the stronger the family and kinship ties are within a loan group, the higher is the default rate. On the contrary, the stronger the social ties are among the group, the lower is the default rate. Other key findings include that the diversion of fund usage from investment to consumption is not found to significantly cause default. Also, loan default can be a consequence of borrowers' strategic choice rather than financial distress. As compared to the female members, male borrowers are found to be causing higher default rates. Interestingly, the gender‐related default rates are lower when more of the male borrowers are only socially related. Finally, group size is found to be positively associated with default. Our findings can help micro‐finance institutions refine their lending policies and guidance on groups' composition and size to reduce default rates. [ABSTRACT FROM AUTHOR]

All over the world, home loans and mortgages are part and parcel of the products and services being offered by the financial institutions-such as banks and homeowner mortgage institutions to their numerous customers. Prior, during and post home loan transactions, they owe their customers the duty to ensure full disclosure of all the terms and conditions in the mortgage agreements without withholding any information. This paper examines any act contrary to uberrimae fidei-utmost good faith in the transactions. Uberrimae fidei requires the highest standard of good faith on both the lender and borrower to disclose all material facts that could influence the decisions of the other party in seeking and granting home loans and mortgages. Failure might result in severe consequences by exploring both the civil and criminal responsibilities and liabilities of the party who acted mala fide-in bad faith. Against this backdrop, this paper examines the protection offered by the laws to ensure level playing field prior, during and after mortgage lending transactions. [ABSTRACT FROM AUTHOR]

This paper discusses differences in the likelihood of loan default between Black and other farmers who took out USDA direct operating loans from 2011 to 2020. By controlling for financial, demographic, and other factors using a Cox proportional hazards model, we found that Black farmers have a higher incidence of default than other farmers. We advanced the research on the relative loan performance of different racial/ethnic minority groups, revealing heterogeneity in the likelihood of default that indicates using a single grouping for all minorities obscures important differences. There could be multiple contributing factors to higher rates of default among Black borrowers that deserve future attention and study, though it is beyond the scope of this paper to identify a causal mechanism. [ABSTRACT FROM AUTHOR]

A home is often the largest asset held by U.S. households. If home equity accumulation is slowed through acquiring a home equity loan, threatened through mortgage default, or undermined through the occurrence of negative home equity, homeowners may experience increased financial stress. This study used the 2018 National Financial Capability Study to assess the relationship between three mortgage statuses (having a home equity loan, negative home equity, or mortgage default) and financial stress among nonretiree mortgage holders (N = 5,058). Financial stress was measured by an index of financial difficulty perceptions. Findings revealed that negative home equity is related to greater levels of financial stress than mortgage default or having a home equity loan. Additionally, experiencing a large drop in income intensified the positive relationship between negative home equity and the financial stress index. These findings suggest that conditions seemingly outside the control of homeowners may influence their financial stress perceptions. [ABSTRACT FROM AUTHOR]

The recent boom in house prices in many countries during the COVID-19 pandemic and the possibility of household financial distress are of concern among some central banks. We revisit the empirical modelling of house prices and household debt with a policy-oriented perspective using Norwegian data over the last four decades within the cointegrated VAR model. Our findings suggest, in line with previous work, a long-run mutually reinforcing relationship between these financial magnitudes, and thus the potential for the build-up of financial instabilities and spillover effects to the real economy. Applying a policy control analysis, we find that both house prices and debt are controllable magnitudes to some pre-specified target levels through the mortgage interest rate, which enables the central bank to reduce large fluctuations and bubble tendencies in the housing market. The present control analysis thus provides some useful policy implications from empirically relevant representations of two important financial factors entering the decision process of the policy maker. [ABSTRACT FROM AUTHOR]

This research studies the effects of mortgage subsidies and asymmetric information in the US mortgage market. I exploit discontinuities in interest rates generated by pricing rules and find patterns consistent with advantageous selection. I estimate an industry model that highlights the relationship between mortgage subsidies, intermediary lenders' incentives, and borrowers' advantageous selection. The model shows that mortgage subsidies enable advantageous selection, creating a deadweight loss of $7.90 billion. The counterfactual analysis reveals that pricing borrowers' private information eliminates advantageous selection only if mortgages are not subsidized. Without the mortgage subsidy, pricing borrowers' private information improves efficiency by $728.58 million. [ABSTRACT FROM AUTHOR]

The investors will only know how much the bank repays them, not the actual amount the borrower could pay to the bank. The optimal contract between the bank and investors (in this context, depositors) to provide incentives for delegated monitoring is a debt contract issued by the bank promising to pay the depositors. Townsend ([50]) assumes contractual commitment to judicial verification of the borrower's cash after a default, reducing borrower payoffs to zero, and subtracting a fixed cost from total investor payoffs. Investors and borrowers are risk neutral, but borrowers have no funds of their own, and each investor's spare funds to invest are small relative to the amount needed to fund the borrower's project. The investor can liquidate the collateral if the borrower pays too little, preventing the borrower from absconding with it, or the investor can impose a nonmonetary penalty on the borrower.[2] Bankruptcy in the world today is some combination of these two actions. [Extracted from the article]

This study leverages novel machine learning techniques to quantify the complex empirical relationship between mortgage default and its drivers. The primary model employed is the authors' newly developed shape-constrained GAMI-Net, which introduces lattice-function-based main effects and pairwise interactions that take user-defined shape constraints. Their approach of adding shape constraints to a lattice module enhances the interpretability and applicability of the model in real-world scenarios. The authors compare the performance of shape-constrained GAMI-Net with alternative machine learning and traditional statistical methods using Freddie Mac's publicly available mortgage dataset. The results demonstrate competitive predictive performance and high interpretability for the shape-constrained GAMI-Net model. [ABSTRACT FROM AUTHOR]

We identify occupancy fraud—borrowers who misrepresent their occupancy status as owner‐occupants rather than investors—in residential mortgage originations. Unlike previous work, we show that fraud was prevalent in originations not just during the housing bubble but also persists through more recent times. We also demonstrate that fraud is broad‐based and appears in government‐sponsored enterprise and bank portfolio loans, not just in private securitization; these fraudulent borrowers make up one third of the effective investor population. Occupancy frauds obtain credit at lower interest rates, suggesting a motivation for undertaking fraud. These fraudulent borrowers perform substantially worse than similar declared investors, defaulting at a 75% higher rate. We also provide evidence consistent with fraudulent borrowers' defaults being more "strategic," suggesting that this population poses a risk in the face of declining house prices. [ABSTRACT FROM AUTHOR]

This paper examines the integration of climate risks into structural credit risk models. We focus on applications in housing finance and argue that mortgage defaults due to climate disasters have different statistical features than default due to household-specific reasons. We propose two models incorporating climate risk based on two separate default definitions. The first focuses on default as a response to a decrease in home value, and the second defines default as a consequence of missed mortgage payments. Using mortgage performance data during Hurricane Harvey, we conduct an empirical study whose results suggest that climate events are potentially another source of undiversifiable credit risk affecting homeowners' ability to make contractual monthly payments. We also show that incorporating this climate-specific default process may capture additional uncertainty in default probability assessments. [ABSTRACT FROM AUTHOR]

We show that a substantial share of households contributes their own labour to the acquisition of their main residence. These contributions help households faced with credit constraints, since they reduce the need for external financing. We develop a simple theoretical model and show that own labour contributions decrease with the level of financial resources available, while they increase with the mortgage interest rate. These theoretical results are supported by empirical analysis, which also shows that own labour contributions vary by household characteristics (age, gender, profession) and by type of dwelling (house, apartment). [ABSTRACT FROM AUTHOR]

This study increases understanding of the mortgage default settlement process by examining how borrowers make decisions during contract negotiations. We explore two main research questions: (1) Do borrowers experience a difference between psychological and legal contracts? and (2) Does inequity aversion, or the dislike of being taken advantage of, influence the willingness of a borrower to withdraw from a mortgage default settlement contract? Our findings suggest borrowers do not conflate legal versus psychological contracts in this setting, a result which contradicts previous research findings. Moreover, as defaulting borrowers appear to place relatively little value on a clean credit report, they do not differentially enter/withdraw from contract negotiations based on a lender's unwillingness/inability to clear their credit report. These findings, which run counter to conventional wisdom, may well reflect the emerging divide in the U.S. between individuals and large institutions. Specifically, borrowers do not appear to trust lending institutions, nor do they seem to care deeply about conventional underwriting and risk signaling metrics such as credit reports. Thus, in order to successfully and optimally resolve the voluminous magnitude of outstanding, toxic mortgage debt, a revolutionary new approach to negotiating with borrowers that reflects these new norms must be considered. Examination of a second dataset suggests these results are based on the cultural and legal environment in the U.S., and therefore may not be generalizable to other countries. [ABSTRACT FROM AUTHOR]

I study how credit and default affect optimal health insurance, constructing a life‐cycle model of health investment with a strategic default option on emergency room bills and financial debts. The model is calibrated to the U.S. economy and used to compare the optimal policy for Medicaid by the availability of the default option and credit. I find that strategic default induces the optimal policy to be more redistributive. With (Without) the option, the optimal income threshold for Medicaid eligibility is 44% (25%) of the average income. In these findings, the interaction between strategic default and preventative medical spending is important. [ABSTRACT FROM AUTHOR]

One of the main issues facing Indian banks is Non-Performing Assets. NPAs show how well banks are doing. A high percentage of non-performing assets (NPAs) indicates a significant likelihood of many loan defaults, which can have an impact on the profitability of a bank and net worth as well as the asset's value. Non-Performing Assets (NPAs) are a problem for Indian banks. The existence of NPAs has a significant impact on the banks' ability to generate income and profitability. In addition, the non-performance or non-receipt of interest and principal restricted banks' money in the form of funds and prevented their usage for further banking operations, resulting in a decline in the banks' profit margin. In this context, the bank must be aware of the issues and NPA recovery laws. Understanding the amount of Non-Performing Assets (NPAs) and how it affects the profitability of the banks is the goal of the current study. The study took into account the Gross and Net NPA of Public & Private sector banks from 2016 to 2022 for this objective. The analysis found that during the time, the Gross & Net NPA of both public and private sector banks gradually increased. According to this study, there is a strong correlation between the Gross NPA and Net NPA of banks in the public and private sectors. In order to lower the NPA and strengthen the recovery system, this paper advises regulators and the appropriate bank authorities to take the necessary actions. [ABSTRACT FROM AUTHOR]

Since 2012, the AEI Housing Center has been a leader in cutting-edge data and research on numerous housing market metrics such as mortgage risk, house price appreciation, new construction, and months' supply of inventory. The AEI Housing Center's research on mortgage risk led to the publishing of the stressed mortgage default rate (SMDR), which assesses the riskiness of loans and how loans originated today would fare under similar stress levels to '06 and '07. During the pandemic, loose monetary and fiscal stimulus drove high house price appreciation, which has abated from the 2022 peak and is currently at 1.4%. We estimate that YoY HPA will be about 4% by year-end. Months' supply remains historically tight at 2.4, contributing to the ongoing seller's market. The housing supply shortage in many high demand metros has effectively halted the filtering process, where homes pass to lower-income residents as the structure depreciates, which is critical to ensuring housing affordability. Housing supply constraints and zoning regulations in places such as California interrupt the filtering process, leading to higher housing prices, higher displacement pressures, and greater levels of homelessness. [ABSTRACT FROM AUTHOR]

Over the past years, studies shed light on how social norms and perceptions potentially affect loan repayments, with overtones for strategic default. Motivated by this strand of the literature, we incorporate collective social traits in predictive frameworks on credit card delinquencies. We propose the use of a two-stage framework. This allows us to segment a market into homogeneous sub-populations at the regional level in terms of social traits, which may proxy for perceptions and potentially unravelled behaviours. On these formed sub-populations, delinquency prediction models are fitted at a second stage. We apply this framework to a big dataset of 3.3 million credit card holders spread in 12 UK NUTS1 regions during the period 2015–2019. We find that segmentation based on social traits yields efficiency gains in terms of both computational and predictive performance compared to prediction in the overall population. This finding holds and is sustained in the long run for different sub-samples, lag counts, class imbalance correction or alternative clustering solutions based on individual and socio-economic attributes. [ABSTRACT FROM AUTHOR]

The transaction price of identical housing units can vary widely due to heterogeneity in buyer and seller preferences, matching, and search costs, generating what we term "markups" above or below the average market price. We measure markups for 3.4 million purchase‐money mortgages and show that they can predict mortgage defaults and credit losses conditional on default even after accounting for collateral coverage (loan‐to‐value ratio) and a comprehensive set of other covariates. The findings suggest that standard collateral coverage estimation may be inaccurate, with implications for both individual and portfolio‐level credit risk assessment. [ABSTRACT FROM AUTHOR]

I model the role of strategic defaults and informal moneylenders on multiple‐installment loan contracts offered by microfinance institutions (MFIs). The results show that a single‐installment loan is not viable due to MFIs' vulnerability to strategic defaults and borrowers' lack of collateral. In contrast, a multiple‐installment contract requires borrowers to borrow from the moneylender, who is immune to strategic default, in order to repay the MFI's early installments that are due before the project yields a return. Consequently, both default costs and borrowing costs increase and incentives to commit strategic default decline, making the multiple‐installment contract profitable for MFIs. [ABSTRACT FROM AUTHOR]

There are three prevailing theories of mortgage default: strategic default (driven by negative equity), cash flow default (driven by negative life events), and double-trigger default (where both negative triggers are necessary). It has been difficult to compare these theories in part because negative life events are measured with error. We address this measurement error using a comparison group of borrowers with no strategic-default motive. Our central finding is that only 6% of underwater defaults are caused exclusively by negative equity, an order of magnitude lower than previously thought. We then analyze the remaining defaults. We find that 70% are driven solely by negative life events (i.e., cash flow defaults), while 24% are driven by the interaction between negative life events and negative equity (i.e., double-trigger defaults). Together, the results provide a full decomposition of the theories underlying borrower default and suggest that negative life events play a central role. [ABSTRACT FROM AUTHOR]

We test the ability of the Decoy Effect to enhance debt collection efforts and find that by disclosing the Annual Percentage Rate (APR) in settlement offers, participants are less influenced by the decoy and more apt to select the repayment option that is in their best interest. At the same time, by reporting the APR, borrowers are more willing to make repayments on the modified loan, resulting in a net gain to debt collection efforts. Because disclosing the APR is Consumer Financial Protection Bureau (CFPB) compliant, this simple disclosure has the ability to increase debt collection returns while helping borrowers make better decisions when selecting debt modification repayment plans. Our results suggest an applicability to all types of defaulted debt including mortgages, sub-prime auto loans, credit cards, student loans, and payday loans. [ABSTRACT FROM AUTHOR]

Reverse mortgages are designed to offer additional sources of financing incomes to senior homeowners. In the United States, home equity conversion mortgages (HECMs) are nonrecourse reverse mortgage loans insured by the Federal Housing Administration (FHA). Based on a fairly recent stream of the reverse mortgage literature, the relatively high loan-to-value ratio has jeopardized the financial soundness of such contracts. In the wake of the 2008 financial crisis, rising property taxes and homeowner insurance defaults impaired HECM solvency; hence, policy changes were implemented to help prevent borrower default. In this paper, we propose a pricing solution which, as we demonstrate in the paper, effectively improves program solvency by fairly matching the benefits and liabilities of HECM participants. The methodology allows for customization of fair mortgage loan payments and premiums and improves program accessibility based on borrowers' individual credit and default risk. Our proposed pricing solution and the corresponding newly designed rating system provide HECM policymakers with a better payment arrangement and offer important policy implications for the current HECM program. Rather than borrower property taxes and insurance delinquency, we demonstrate that the mispricing of HECM mortgage insurance premiums and the corresponding loan payments could be the primary reasons for program insolvency. [ABSTRACT FROM AUTHOR]

Direct damage from flooding at residential properties has typically been categorized as insured, with liabilities accruing to insurers, or uninsured, with costs accruing to property owners. However, residential flooding can also expose lenders and local governments to financial risk, though the distribution of this risk is not well understood. Flood losses are not limited to direct damages, but also include indirect effects such as decreases in property values, which can be substantial, though are rarely well quantified. The combination of direct damage and property value decrease influences rates of mortgage default and property abandonment in the wake of a flood, creating financial risk. In this research, property‐level data on sales, mortgages, and insurance claims are used in combination with machine learning techniques and geostatistical methods to provide estimates of flood losses that are then utilized to evaluate the risk of default and abandonment in eastern North Carolina following Hurricane Florence (2018). Within the study area, Hurricane Florence generated $366M in observed insured damages and an estimated $1.77B in combined uninsured damages and property value decreases. Property owners, lenders, and local governments were exposed to an additional $562M in potential losses due to increased rates of default and abandonment. Areas with lower pre‐flood property values were exposed to greater risk than areas with higher valued properties. Results suggest more highly resolved estimates of a flooding event's systemic financial risk may be useful in developing improved flood resilience strategies. Plain Language Summary: The financial impacts of flooding are complex and their distribution across different groups is difficult to quantify. Traditionally, the focus has been on estimating damages that directly impact insurers and property owners, but lenders and local governments can also be affected. Following a flood, uninsured damage and reductions in property value can combine to reduce a property owner's equity, hampering their ability to borrow money and recover from the flood. This can lead to mortgage default or even property abandonment, resulting in financial consequences for the property owner, the mortgage lender, and/or the local government. This research estimates uninsured damage and property value changes throughout eastern North Carolina following Hurricane Florence via a novel machine learning approach, using data on the physical characteristics of residential properties, insurance claims, property sales, and mortgages. Results indicate that uninsured damage and property value decreases combined to be substantial and this combination significantly increased risk of mortgage default and/or abandonment. Lower valued properties experienced higher rates of default and abandonment than high valued properties, with risk varying widely across communities. This type of analysis allows for property‐level assistance to be targeted toward the most vulnerable. Key Points: Estimates of uninsured flood damage and property value decrease can be used to predict rates of mortgage default and abandonmentFinancial risk, previously not well quantified, thus expands beyond property owners and insurers to include lenders and local governmentsA new analytical approach estimates $562M in financial risk from Hurricane Florence with disproportionate impact at low valued properties [ABSTRACT FROM AUTHOR]

We use a dataset of 12 million residential mortgages to investigate the loan default behavior in several European countries. We model the default occurrence as a function of borrower characteristics, loan-specific variables, and local economic conditions. We compare the performance of a set of machine learning algorithms relative to the logistic regression, finding that they perform significantly better in providing predictions. The most important variables in explaining loan default are the interest rate and the local economic characteristics. The existence of relevant geographical heterogeneity in the variable importance points at the need for regionally tailored risk-assessment policies in Europe. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive history of default risk for newly originated home mortgages in the USA over the past quarter century. The loan-level source data include the entire guarantee book for Fannie Mae and Freddie Mac. We track many loan characteristics and produce a summary measure of risk. Among our many results, we show that mortgage risk had already risen in the 1990s, planting seeds of the financial crisis well before the actual event. Our results also cast doubt on explanations of the crisis that focus on borrowers with low credit scores. The aggregate series are available for download at https://www.fhfa.gov/papers/wp1902.aspx. [ABSTRACT FROM AUTHOR]

We analyze the impact of soft information on US mortgages for default prediction and provide a new measure for lender soft information that is based on the interest rates offered to borrowers and incremental to public hard information. Hard and soft information provide for a variation in annual default probabilities of approximately 3%. Soft information has a lesser impact over time and time since origination. Lenders rely more on soft information for high‐risk borrowers. Our study evidences the importance of soft information collected at loan origination. [ABSTRACT FROM AUTHOR]

When borrowers are delinquent, senior debtholders prefer liquidation, whereas junior debtholders prefer to maintain their option value by delaying resolution or modifying the loan. In the mortgage market, a conflict of interest ("holdup") arises when servicers of securitized senior liens are also the owners of the junior liens on the same property. We show that holdup servicers are able to delay action on the first-lien mortgage. When they do act, servicers are more likely to choose resolutions that maintain their option value, favoring modification and soft foreclosures over outright foreclosures. Holdup behavior is more likely to result in borrower self-curing. [ABSTRACT FROM AUTHOR]

The Community Reinvestment Act (CRA) encourages banks to lend to low‐ and moderate‐income individuals. This paper estimates the effect of the CRA on mortgage lending, exploiting variation in the set of banks whose lending performance is assessed in a given neighborhood due to redefinitions of Metropolitan Statistical Areas in 2003. Incorporating a typical tract into one additional banks' assessment area increased mortgage lending there by approximately 2%. Lending to low‐income borrowers was particularly affected. While income‐conditional default risk was little changed, CRA‐induced loans were riskier than average, due to their borrowers' lower incomes. [ABSTRACT FROM AUTHOR]

Mortgage losses have two elements: the financial loss associated with the sale of the property, and costs associated with the time it takes for the default to be processed and to eventually sell the property (holding costs). The results show that both the dollar loss on the sale and the time-related holding costs have substantial variations across space and over time. Most of the losses are associated with the sale of a property, not the holding costs. This variation can, at least in part, be attributed to borrower and loan characteristics and economic conditions. The legal environment (borrower and lender rights) can have strong effects on the length of the holding period (the default timeline) and therefore holding costs, but there is no evidence that it has an impact on the dollar loss associated with the sale of the property. [ABSTRACT FROM AUTHOR]

The real estate market has been booming in China for the past 10 years. Highly leveraged on banks' credit, it has aroused regulators' attention because of the potential catastrophic consequence, and it may produce on the whole financial system if the housing price boom bursts and massive defaults on mortgages occur. In this article, reverse stress testing engineering has been employed to study the factors impacting significantly on the mortgages' defaults and their implicit transition mechanism under different simulated scenarios. This work, which produces more precise snapshots of the financial institutes' risk tolerances by pushing the risk factors to their limits, could be used by regulators for formulating housing price control policies and by banking management for implementing the credit default risk warning system. [ABSTRACT FROM AUTHOR]

During the Global Financial Crisis, house prices sharply declined in all West‐European countries, but after an initial recovery the Dutch housing market experienced a second dip. This paper examines whether the introduction of the tightened Code of Conduct for Mortgage Loans in 2011 had an effect on Dutch house prices. We compare the evolution of Dutch house prices with a synthetic control of other European countries. Our results suggest that the introduction of the new Code of Conduct did indeed have a substantial negative effect on Dutch house prices in the 2 years following its introduction. Several robustness checks confirm this conclusion. [ABSTRACT FROM AUTHOR]

This paper uses new data from the PSID to quantify the relative importance of negative equity versus ability to pay, in driving mortgage defaults between 2009 and 2013. These data allow us to construct household budgets sets that provide better measures of ability to pay. Changes in ability to pay have large estimated effects. Job loss has an equivalent effect on the propensity to default as a 35% decline in equity. Strategic motives are also found to be quantitatively important, as we estimate more than 38% of households in default could make their mortgage payments without reducing consumption. [ABSTRACT FROM AUTHOR]

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This paper uses a quasi‐natural experiment to identify the impact of interest rates on mortgage default. Using loan‐level panel data for Ireland, we deal with selection bias by exploiting the variation between two adjustable‐rate mortgages offered in the 2000s. We link interest rates to default directly through borrower installments. We find a strong, statistically significant, impact of interest rates on default; a 1% increase in installment is associated with a 5.8% increase in the likelihood of default. We also find evidence that negative equity amplifies the increase in default risk caused by higher interest rates. [ABSTRACT FROM AUTHOR]

We investigate the relationship between building energy efficiency and the probability of mortgage default. To this end, we construct a novel panel data set by combining Dutch loan-level mortgage information with provisional building energy ratings provided by the Netherlands Enterprise Agency. Using the logit regression and the extended Cox model, we find that building energy efficiency is associated with a lower probability of mortgage default. There are three possible channels that might drive the results: (i) personal borrower characteristics captured by the choice of an energy-efficient building, (ii) improvements in building performance that could help to free-up the borrower's disposable income, and (iii) improvements in dwelling value that lower the loan-to-value ratio. We address all three channels. In particular, we find that the default rate is lower for borrowers with less disposable income. The results hold for a battery of robustness checks. This suggests that the energy efficiency ratings complement borrowers' credit information and that a lender using information from both sources can make superior lending decisions than a lender using only traditional credit information. These aspects are not only crucial for shaping future energy policy, but also have implications for the risk management of European financial institutions. [ABSTRACT FROM AUTHOR]

After 5 years of subsidy, interest rates for mortgages modified under the Home Affordable Modification Program (HAMP) reset, increasing annually in increments of up to 1 percentage point until they reach a predetermined rate. We identify the causal effect of increasing interest rates on default, delinquency, and prepayment using an event study design and confirm the effects using a regression kink design. New delinquency and default spike at time of reset among those whose rates increase, with smaller persistent effects continuing. These delinquency and default effects are smaller for lower balance loans in the second reset, for which additional subsidies at the time of second reset are relatively more valuable. We find that a 1 percentage point increase in the mortgage rate led to a roughly 20% increase in the default hazard. This implies that the reset rate increase is cost-effective for lenders given the default environment at the time of reset: increased revenue from higher rates exceeds estimated losses from additional defaults. [ABSTRACT FROM AUTHOR]

We show that banks with high environmental, social, and governance (ESG) ratings issue fewer mortgages in poor localities—in number and dollar amount—than banks with low ESG ratings. This lending disparity happens at both the county and census tract level, worsens in disaster areas of severe hurricane strikes, is robust to alternative ESG ratings (including using only the social (S) component), and cannot be explained by banks' differential deposit networks. We find no difference in mortgage default rates between high- and low-ESG banks, rejecting an alternative explanation based on differential credit screening quality. We report a complementary, not substitution, relation between high-ESG banks' mortgage lending and their community development investments (like affordable housing projects) in poor localities. Loan-application-level analyses confirm that high-ESG banks are more likely than low-ESG banks to reject mortgage loans in poor neighborhoods. The evidence hints at social wash: banks deploy prosocial rhetoric and symbolic actions while not lending much in disadvantaged communities, the social function they arguably ought to perform. Community Reinvestment Act (CRA) examinations partially undo the social wash effect. [ABSTRACT FROM AUTHOR]

The Coronavirus Aid, Relief, and Economic Security (CARES) Act was passed in response to both the global pandemic's immediate negative and expected long-lasting impacts on the economy. Under the Act, mortgage borrowers are allowed to cease making payments if their income was negatively impacted by Covid-19. Importantly, borrowers were not required to demonstrate proof of impaction, either currently or retrospectively. Exploring the economic implications of this policy, this study uses an experimental design to first identify strategic forbearance incidence, and then to quantify where the forborne mortgage payment dollars were spent. Our results suggest strategic mortgage forbearance can be significantly reduced, saving taxpayers billions of dollars in potential losses, simply by requiring a 1-page attestation with lender recourse for borrowers wishing to engage in COVID-19 related mortgage payment cessation programs. Additionally, we demonstrate the use of these forborne mortgage payments range from enhancing the financial safety net for distressed borrowers by increasing precautionary savings, to buying necessities, to equity investing and debt consolidation. [ABSTRACT FROM AUTHOR]

We investigate the role of local housing prices in the default of peer-to-peer (P2P) loans. From the data of Lending Club and Zillow, we find that borrowers, who reside at a ZIP code where median home price is one standard deviation higher than the cross-sectional average, show a 0.75% lower default probability, given the loan interest rate into consideration. However, this effect of ZIP-code-level home price on the default probability is three times stronger for homeowner borrowers with mortgages: the marginal probability jumps from 0.75% to 2.13%. Higher home price improves a homeowner borrower's credit and wealth, and such an effect is highly leveraged by a mortgage, ceteris paribus. This channel is an interaction between borrower-specific and local information, which is distinct from the well-known socio-economic channel. Our empirical results provide an important implication on the reputation or feedback mechanisms in P2P loan markets. [ABSTRACT FROM AUTHOR]

Previous studies have yielded ambiguous results regarding the impact of income and financial experience on the decision of residential borrowers to strategically default. One explanation for these findings is the presence of an interaction effect between income and financial experience, which was ignored in earlier studies. We hypothesize that borrowers with a greater ability to assess the financial benefits of strategic default, due to a higher financial experience, and overcome the financial consequences of it, due to higher incomes, have fewer negative attitudes towards strategic default. We capture negative attitudes of US homeowners (borrowers) by measuring their anger towards residential borrowers who decided to strategically default. In particular, we (1) ask them to self-report their anger and (2) measure their anger with artificial intelligence (AI)-based emotion recognition software. We find evidence for the hypothesized interaction effect: Borrowers with higher incomes and greater financial experience, particularly regarding value of money, savings, and investments, have fewer negative attitudes towards strategic default. Our results have implications for mortgage lenders. While borrowers with higher incomes and more financial experience are likely to have a lower economic default risk, their strategic default risk may be higher. [ABSTRACT FROM AUTHOR]