128 research outputs found

    Optimization of Home Mortgage Mover Predictive Model Applying Geo-Spatial Analysis and Machine Learning Techniques

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    In the last decade digital innovations and online banking services have significantly changed customers banking preferences and behaviour. Banking industry is going through the changes and developments in the provision of banking services that are affecting the structure and the organization of the bank network. However, private home loan, referred as Home Mortgage hereinafter, continue to remain among the products, that customers prefer to have personal interaction about with professional advisors prior making the decision to apply for the loan with financial institution

    Google search intensity, mortgage default and house prices in regional residential markets

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    The internet provides a new way for households to access relevant information, while their online search behaviour may also contain information for their concerns and intentions, or even be used to predict real economic activity. This thesis explores the use of Google search data to predict mortgage default and regional house price dynamics in an empirical macroeconomic framework. The thesis is composed of three independent empirical studies. The first study examines the dynamic interdependence between mortgage default and house price across different housing market segments, i.e., top-tier vs. bottom-tier houses and recourse states vs. non-recourse states, based on a Panel VAR model. In particular, this study uses the Mortgage Default Risk Index (MDRI) proposed by Chauvet et al. (2016). It captures the intensity of Google search for keywords and phrases such as “mortgage foreclosure” or “foreclosure help” and measures the potential default risk of households. It is shown that shocks to house price returns have a significantly stronger effect on actual foreclosures in non-recourse states than in recourse states. The results suggest that borrowers are financially sophisticated and strategic as they are less likely to default in recourse states. Additionally, the MDRI has a stronger negative impact on top-tier home price returns, while the foreclosure rate of homes more pronouncedly decreases bottom-tier home price returns. These findings hold for the entire sample and recourse states. However, in non-recourse states, the impacts of the MDRI and the HF on bottom- and top-tier house price returns are about the same. The second study examines the impact of house prices on the foreclosure rates in the local housing market and explores whether the MDRI helps predict future house prices and foreclosures. In particular, this study uses an error correction framework to capture both the long-run equilibrium fundamental component of house prices as well as the short-run dynamics of house prices, including the component of bubbles. It is found that the MDRI shows a negative impact on both components of house prices but, more importantly, a negative impact on foreclosure rates. Furthermore, it is shown that foreclosure rates are negatively affected by the fundamental component of house prices but are not sensitive to their bubble component. This study sheds new light on the predictive power of household sentiment derived from Google searches on prices and foreclosure rates in local housing markets. The third study recognizes that, by searching online, households are transmitting information to and simultaneously receiving information from the Google Search engine. While they might divulge information about their financial concerns or vulnerability, they are also gathering information and learning through their search behaviour. This chapter aims to examine the comprehensive impact of the disclosure and information-learning effects of online searches on mortgage default. To that end, based on the assumption of different pre-existing knowledge of households, this study defines two kinds of Google search activities of households, i.e., naïve and sophisticated searches, and practically performed by aggregating the search activities for different query terms. It is found that sophisticated search activity has a positive impact on mortgage delinquency but a negative impact on foreclosure starts, while naïve search activity only positively affects foreclosure starts. The results suggest that the Google search activity of households is a combination of information disclosure and information-learning processes. Furthermore, borrowers are more likely to learn from sophisticated online searches, and they can use the information to avoid foreclosure starts

    Bridging the racial disparity in wealth creation in Milwaukee

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    This paper investigates the persistent racial disparities in homeownership and wealth creation in Milwaukee. Despite past efforts, homeownership rates for Black and Hispanic households remain significantly lower compared to White households, contributing to wealth inequalities. We develop a Wealth Creation Index that highlights pronounced racial/ethnic disparities in wealth accumulation. The study identifies additional factors such as crime rates, proximity to quality schools, and lot size, which impact these disparities. Findings also reveal lower home value appreciation for minority and female homeowners, and the disproportionate negative effects of foreclosures on their properties. The research provides insights for informing public policy, guiding investments, and benchmarking interventions to address disparities and promote equitable homeownership

    Improving the Efficiency of Mortgage Loan Modification

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    A majority of delinquent mortgage loans during the foreclosure crises were unmodified. Lending institutions lost on average 50% of a home\u27s value in future profit from each foreclosure. The purpose of this single case study was to explore what strategies mortgage loan officers might use to improve the selection of delinquent borrowers for mortgage loan modification. The conceptual framework for this study was contract theory. The target population included mortgage loan officers from one community bank who successfully implemented strategies to modify loans for delinquent borrowers during the foreclosure crisis. Semistructured interviews were the data collection method. Emergent themes were identified in the data using a form of pattern matching called explanation building. The following key themes emerged: asymmetric information is essential to a mortgage loan officer\u27s ability to select delinquent borrowers for mortgage loan modification and mortgage loan officers could create value for their organizations through mutually beneficial contracts. The results of this study can be used by leaders in financial institutions to improve the processes and procedures pertaining to mortgage loan modification. Improving mortgage loan modification practices can reduce foreclosure and the impact foreclosures have on the deterioration of communities, property values, and the degraded ability of governments to provide services due to the loss of revenue

    Overview applications of data mining in health care: The case study of Arusha region

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    A research article was submitted to International Journal of Computational Engineering Research||Vol, 03||Issue, 8| 2013Data mining as one of many constituents of health care has been used intensively and extensively in many organizations around the globe as an efficient technique of finding correlations or patterns among dozens of fields in large relational databases to results into more useful health information. In healthcare, data mining is becoming increasingly popular and essential. Data mining applications can greatly benefits all parties involved in health care industry. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform huge amount of data into useful information for decision making. This paper explores data mining applications in healthcare in Arusha region of Tanzania more particularly; it discusses data mining and its applications in major areas such as evaluation of treatment effectiveness, management of healthcare itself and lowering medical cost

    Analysis of loss given default

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    CREDIT RISK, INVESTOR BEHAVIOR AND RESIDENTIAL MORTGAGE DEFAULT

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    Ph.DDOCTOR OF PHILOSOPH

    Metropolitan Spatial Structure: Measuring the Change

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    Since 1990s the metropolitan spatial structure has been alleged to be growing smarter. Excessive suburbanization trends characterizing urban form since the Second World War are now believed to be reversing in favor of urban environment. The reversal is driven by changing household preferences as well as a series of changes that urban areas have gone through which make them more attractive living environments for some demographic groups. This is a dissertation consisting of three related essays which examine change in the metropolitan spatial structure over the past two decades to determine if suggested changes are in fact observable in urban form. In measuring change, I consider a number of measures that characterize urban form, particularly density, concentration, clustering, infill and growth allocation of urban growth. Given the prevalence of foreclosure crisis in the later part of the first millennium decade, I also explore the impact of urban form on accumulation of foreclosures as an indicator of future spatial structure change. The study finds two different trends at force facing the American metropolitan spatial structure. For the metropolitan areas with weak growth pressures or those loosing population since 1990, suburbanization trends continue to define spatial structure. However, in the metropolitan areas that are facing moderate and strong population growth pressures and constituting the majority of the largest urban areas in the U.S., the importance of urban center is ever more significant and their spatial structure is greatly dependent on denser urban form. Desirability for urban environment also manifested itself in the spatial distribution of foreclosures in Maryland
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