Analysis of Residential Property Sales in Mansfield, Ohio

Transcription

1 Analysis of Residential Property Sales in Mansfield, Ohio July 00 Community Research Partners in collaboration with Center for Urban and Regional Analysis The Ohio State University

2 Analysis of Residential Property Sales in Mansfield, Ohio July 00 Community Research Partners Roberta F. Garber, Executive Director Center for Urban and Regional Analysis The Ohio State University Edward J. Malecki, Director Hazel A. Morrow-Jones, Associate Director Wenqin Chen, Data Manager

3 Analysis of Residential Property Sales in Mansfield, Ohio Contents Page I. Background and Introduction...1 What is Predatory Lending?...1 II. Research Methodology... III. Data Analysis and Findings...4 Parcels with Atypical Price Patterns...5 Locations of Identified Transactions...6 IV. Issues with the Data...6 Limitations of the Auditor s Transaction Data...6 Additional Data Sources...6 V. Next Steps...7 Conduct Additional Research on Questionable Patterns...8 Develop Strategies to Address Predatory Lending and Problematic Transactions...8 Tables 1. Examples of Predatory Lending Practices.... Richland County Auditor s Transaction Data Records, Mansfield Transaction Analysis Methodologies Analysis 1: Mansfield Residential Parcels with 3+ Transactions and Annualized Price Increase >/= 10%, Analysis : Mansfield Residential Parcels with 3+ Transactions, Annualized Price Increase >= 10%, and Fewer than 180 Days Between at Least One Set of Transactions, Analysis 3: Mansfield Residential Parcels with + Transactions and Atypical Price Patterns, Maps 1. Number of Transactions per Parcel. Number of Days Between Transactions 3. Parcels with Atypical Price Patterns 4. Number of Parcels with Questionable Transactions by Census Tract

4 Analysis of Residential Property Sales in Mansfield, Ohio Page 1 I. Background and Introduction In August 001, representatives of the City of Mansfield met with staff of Community Research Partners (CRP) to discuss their concerns about residential properties that may be part of a predatory lending flipping scheme in the community. City officials believe that a group of unscrupulous individuals purchased several hundred residential properties scattered throughout the community, repeatedly refinancing, or flipping, the loans based on inflated appraisals. While the city had identified some of these properties, they believed that there were many more. These include: Properties owned by one of the individuals involved in the flipping scheme, currently for sale or occupied as rental properties; Properties that were sold at inflated prices to individuals not part of the flipping scheme; and Properties that have been foreclosed upon or that are in receivership. The city asked CRP to undertake research to locate and map these properties and to determine their current status and ownership. CRP collaborated with the Center for Urban and Regional Analysis (CURA) at The Ohio State University to complete the data analysis and mapping for the project. What is Predatory Lending? While Mansfield asked CRP to focus primarily on the type of flipping that involves rapid turnover of properties, they recognize that this may be a part of a broader array of predatory lending practices. Communities and housing advocacy groups throughout Ohio have become increasingly concerned about predatory lending. A statewide organization that is addressing this issue is the Coalition on Homelessness and Housing in Ohio (COHHIO). A fact sheet of COHHIO s Ohio Community Reinvestment Project (OCRP) states that lending practices become predatory when lenders target specific populations (usually lowincome, minority and/or elderly) with high pressure marketing techniques, charge excessive fees, frequently refinance or flip the loan, and frequently mislead the borrower. OCRP notes, Ohio is not immune to the practice. In low- and moderateincome and minority communities throughout the state, one or two predatory lenders often dominate the market, while prime lenders are nowhere to be found. OCRP describes predatory lenders as, literally harvesting the equity that homeowners have built up over the years If the borrower makes the monthly loan payments, which are oftentimes inflated with excessive fees, high interest rates and pricey insurance premiums, the lender is making a profit. If the borrower is unable to make the monthly payments, the lender forecloses and sells the house for a profit. Table 1 provides examples of predatory lending practices.

5 Analysis of Residential Property Sales in Mansfield, Ohio Page Sales and Marketing Excessive Fees Terms that Trap Borrowers Other Fraudulent Practices Table 1. Examples of Predatory Lending Practices High pressure, door-to-door sales Targeting vulnerable populations (i.e. elderly, less educated) Steering to higher-cost loans despite borrower qualifying for lower-cost credit Flipping excessive refinancing Home improvement scams, in which contractors act as loan brokers Packing loans with unnecessary fees, which are often financed into the loan Padding closing costs with third party fees Excessively high points or origination fees High broker fees, including yield spread premiums Balloon payments, which conceal the true cost of financing and may force repeated refinancing Negative amortization, in which payments are less than interest, resulting in an increase in the principal balance Prepayment penalties Asset-based lending, ignoring repayment ability Reporting inflated income figures Forgeries Insufficient or improperly timed disclosure Inflated appraisals, in part to enable secondary market sale Source: Ohio Community Reinvestment Project II. Research Methodology The objectives of the research were to identify and locate properties that may have been a part of the flipping scheme and to learn about the ownership, financing and transaction history of these properties. The two main sources of data used were a set of data on Richland County property transactions from 1998 to 001 and a database of all property characteristics in Richland County. Both of these data sets were obtained from the Richland County Auditor s office. The data used for this research included only transactions that involved a property transfer. However, in predatory lending situations, flipping more frequently involves refinancing of owner-occupied properties. The research was only able to address potentially problematic transfers, not the broader problem of predatory refinancing that can lead to a property transfer or sale. Each property transaction in the Auditor s database is able to be associated with a specific geographic location through a parcel identification number that appears in each record. The transaction database provides property address, price and date of sale, and appraised land and building values. The data provided by the Auditor s office did not include data on other financial terms associated with each transaction, such as the lender, mortgage rate or loan term/type. Using the property transaction data, the following characteristics were chosen as indicators of transfers that may have involved flipping:

6 Analysis of Residential Property Sales in Mansfield, Ohio Page 3 Number of transfers during the four-year period; Frequency of transfers (number of days between transactions); and Patterns of price increases and/or decreases. The transaction data were provided by the Auditor s office in ASCII text format. Microsoft Excel was used to convert the ASCII text file of property transactions into a spreadsheet file containingcountywide13,059 unique transactions (after deleting 1,1 redundant records from the total of 14,71 records) over the years 1998 to 001. An ArcView Avenue script was used to organize the data in such a way that one parcel identification number was a single record with all the transaction information for that parcel. This reduced the total number of countywide data records from 13,059 to 11,170. By identifying the tax district codes within the City of Mansfield, the subset of data in Mansfield was found to be 5,8 transactions (see Table ). Table Richland County Auditor s Transaction Data Records, Richland County Total property transactions in Auditor s data file 14,71 Total transactions after removing redundant records 13,059 Total parcels involved in transactions 11,170 City of Mansfield Total property transactions 5,8 Total parcels involved in transactions 4,854 The Center for Urban and Regional Analysis used ESRI s ArcView and ArcGIS software to manage, manipulate and map the transaction data and to identify irregular transaction patterns at the census tract level. The Richland County Auditor s Office provided a GIS coverage file for parcels located in Mansfield. Once the property transaction database was linked to the GIS parcel coverage, residential land use code and census tract numbers were added to the data. Standard querying routines were employed to identify properties that were bought and sold more than once over the four-year period and properties that sold multiple times in the same calendar year. After identifying a set of multiple transaction properties in Mansfield, price changes between transactions were calculated, as were the number of days between transactions. 1 1 Many of the individual transactions in the County Auditor s data file were dirty, containing both entries made in error and corrections to them. For example, if a property sold for $ but was entered as $10000, there will be two records: one for $10000 and a new one for $ (commas are not used in these files, which contributes to the error rate). However, the transaction history of a property parcel allows one to identify properties that have been bought and sold too many times relative to some normal number. Given the errors, however, many records were interpreted by the researchers as corrections rather than as distinct property sales.

7 Analysis of Residential Property Sales in Mansfield, Ohio Page 4 III. Data Analysis and Findings There is not a proven method or standard for identifying properties involved in a predatory lending or flipping scheme. This project sought to identify and locate residential property transactions (sales or other ownership transfers) in Mansfield that exhibited unusual characteristics that may warrant further investigation. Three methodologies were used to analyze the data sets and identify questionable property transactions. The parcels identified using the three methodologies described in Table 3 below, and shown on Maps 1, and 3, are not mutually exclusive. The parcels in Analysis are a subset of those in Analysis 1. Analysis 3 includes some parcels in the other two analyses, as well as some that are not in the other groups. Map 4 shows the location by census tract of the 14 unique parcels identified as having questionable transactions in Analysis 1, Analysis 3 or both. Staff of the City of Mansfield has been provided with a spreadsheet with detailed information on these parcels and transactions, including address, transaction dates and prices, and ownership. Table 3 Mansfield Transaction Analysis Methodologies Number of Parcels Number of Transactions Analysis 1: Three or More Transactions and Price Increase. Residential parcels with three or more transactions between 1998 and 001 and an annualized price change greater than 10%. (See Map 1 and Table 4) Analysis : Three or More Transactions, Price Increase and Frequent Transactions. Residential parcels with: 1) three or more transactions between 1998 and 001; ) an annualized price change greater than 10%; and 3) fewer than 180 days between at least one set of transactions. (Subset of Analysis 1. See Map and Table 5) Analysis 3: Atypical Price Patterns. Residential parcels that sold two or more times between 1998 and 001 with abnormally high price increases or decreases or a see-saw price pattern (up and down over several transactions). (See Map 3 and Table 6) 113 NA Total Unduplicated Parcels with Questionable Transactions from Analysis 1 and Analysis 3 (See Map 4) 14 NA

8 Analysis of Residential Property Sales in Mansfield, Ohio Page 5 Table 4 Analysis 1 Mansfield Residential Parcels with 3+ Transactions and Annualized Price Increase >/= 10%, Number of Transactions per Parcel Number of Parcels Number of Transactions Three Four Five 8 40 Six 1 Total Table 5 Analysis Mansfield Residential Parcels with 3+ Transactions, Annualized Price Increase >/= 10% and Fewer than 180 days Between at Least One Set of Transactions, Number of Days Between at Least One Set of Transactions Number of Parcels* Number of Transactions Less Than 30 Days Less Than 60 Days Less Than 90 Days Less Than 180 Days Total *Some parcels may be involved with more than one transaction with different number of days between transactions. Parcels with Atypical Price Patterns In a typical transaction, a property may sell for $100,000 at the beginning of a given year, and then sell a year later for $105,000. This represents 5% appreciation over a one-year period. By comparison, another property may sell once for $50,000, then three months later for $75,000. This is a 50% return over three months, or roughly a 00% annualized return. This is highly questionable, particularly if the property is located in a low-income neighborhood. There are 113 properties in Mansfield that, based on Auditor s transaction data, sold two or more times between 1998 and 001, and had either very large price jumps (greater than 1000 %), large price jumps (from 36% to 1000%), large price drops (from -45% to -96%), or seesaw price changes (See Table 6). The category of very large price jumps includes 13 properties that were sold as a group for a total sale price of $1.5 million. The Auditor s records shows $1.5 million as the sale price for each property.

9 Analysis of Residential Property Sales in Mansfield, Ohio Page 6 Table 6 Analysis 3 Mansfield Residential Parcels with + Transactions and Atypical Price Patterns, Price Pattern Number of Parcels Large Price Drops (from -45% to -96%) See-Saw Price (up and down pattern) 8 Large Price Jumps (from 36% to 950%) 39 Very Large Price Jumps (Greater than 1,000%) 4 Total 113 Locations of Identified Transactions Map 4 shows the locations of the properties identified through the Analyses 1 and 3 described above. The largest concentrations of these parcels are located in Census Tract 3 (4 parcels), Tract 6 (3 parcels), Tract 7 (0 parcels), Tract 5 (16 parcels), Tracts 8 (11 parcels), Tract 4 (9 parcels), and Tract 1.01 (6 parcels). IV. Issues with the Data The researchers were able to identify and map the location of the 110 properties in Analysis 1 and the 113 properties identified in Analysis 3 in Mansfield with atypical transaction histories. In general, where the records are in good, computerized form, it was possible to identify patterns and select cases where a closer look is warranted. However, there was not sufficient information in the available records to proceed to the next step of examining the questionable transactions to see whether there was a reasonable explanation for the anomalies or whether they indeed formed a pattern of predatory lending practices. Limitations of the Auditor s Transaction Data The transaction data from the Richland County Auditor included only parcel identification numbers and addresses, sale date, sale amount and appraised values. Deed transfer records often also include the name of the buyers and sellers of each property, the financial institution that made the loan, terms of the loan and other information. With even these few additional variables it would have been possible to look for more patterns in the data and potentially identify additional transactions of interest in this analysis. Additional Data Sources The Auditor s data enabled the researchers to look for patterns and select cases that would be interesting to examine in more detail. Unfortunately, the lack of computerized records in a variety of contexts prevented taking the next steps in the research. The question is not whether the data exist in most cases they do and are often in public records but rather that they are not available in easily computer searchable form. This means research using the data requires a lot of staff time, which is relatively expensive.

10 Analysis of Residential Property Sales in Mansfield, Ohio Page 7 Examples of next step data include: Building permits Building permits can be used to determine whether major changes, additions or renovations were made to buildings that justified a large price increase. Utility payment records Utility payment records can be used to identify organizations and individuals that have had problems in making utility payments. This can provide additional evidence of problems with questionable properties or identify other ownership patterns to investigate. Property tax records Entities with utility payment problems and questionable transactions would also be more likely to have tax payment problems as part of an overall gray area investment problem. Names of buyers and sellers This information from deed transfer records could be used to more easily determine whether the same entities or individuals were involved in unusual transactions over and over again. Researchers could look for large numbers of transactions between the same pairs of partners or search for other transactions in which they were involved. Names of financial institutions If this information were available on the deed transfer records it would be easier to know which financial institutions were involved in questionable transactions. The financial institutions might be victims, unaware of the nature of some of the transactions, or they could be part of the problem. Names of appraisal firms If it were known which financial institutions made the loans it would be possible discuss the identity of the appraisers used for the transactions. Knowing which appraisers were used in the questionable cases would add one more link to the predatory lending chain. There may be concerns about out of town lenders and appraisers and their role in questionable transactions. V. Next Steps It is not possible to conclude with certainty from the data available to date if there is a pattern of flipping or predatory lending in Mansfield. Additional research is needed to form definitive conclusions about specific transactions, individuals and organizations. There are, however, enough questions raised by the research to warrant further investigation. There is also reason to be concerned about the potential impact of these unusual transaction patterns on the Mansfield housing market. This may include housing vacancies, absentee landlords and artificially inflated housing prices, all of which can have a destabilizing impact on a community. There are several steps that the City of Mansfield and other community stakeholders can take to build upon the research in this report. These fall into two categories: 1) conduct more in-depth research on questionable ownership and financial transactions, and ) develop strategies to address problematic transactions and predatory lending.

11 Analysis of Residential Property Sales in Mansfield, Ohio Page 8 Conduct Additional Research on Questionable Patterns The previous section of the report identified sources of additional data that could be used to identify with more certainty predatory lending practices and the individuals and institutions involved in these practices in Richland County. It is recommended that this begin with a sample of the questionable properties identified in this research, focusing on the census tracts with the greatest number of these properties. Additional research could include: Transaction research. Conduct a title search or use other data to obtain more information on the transaction chain, including the names of buyers and sellers, lenders and appraisers, as well as foreclosure records. Property research. Conduct research on the properties in question, including occupancy/vacancy status, code violations, utility arrearages and lead based paint issues. Develop Strategies to Address Predatory Lending and Problematic Transactions The research in this report can be used to begin a community discussion on strategies to address and prevent predatory lending and other problematic housing transfer activities. Strategies might address: 1. Targeting efforts to areas with concentrations of questionable/atypical property transactions.. Identifying community resources for purchase, redevelopment and/or rehabilitation of affected properties. 3. Dealing with problem lenders and appraisers. 4. Educating purchasers and owners about avoiding predatory lending practices. 5. Improving availability and accessibility of computerized property records from the county and other sources.

12 Map 1: Number of Transactions per Parcel Residential Parcels with 3 or More Transactions and 10% or Higher Annualized Price Increase , City of Mansfield, Richland County, Ohio Number of Transactions N = 110 N Map prepared by the Center for Urban and Regional Analysis, July 00

13 Map : Number of Days Between Transactions Residential Parcels with 3 or More Transactions and 10% or Higher Annualized Price Increase , City of Mansfield, Richland County, Ohio Less Than 30 Days Less Than 60 Days Less Than 90 Days Less Than 180 Days N = 87 Map prepared by the Center for Urban and Regional Analysis, July 00 0 N

14 Map 3: Parcels with Atypical Price Patterns Residential Parcels with or More Transactions and Atypical Price Patterns , City of Mansfield, Richland County, Ohio Large Price Drops (from -45% to -96%) See-saw Price Large Price Jumps (from 36% to 950%) Very Large Price Jumps (Greater than 1000%) N = 113 Map prepared by the Center for Urban and Regional Analysis, July 00 N

15 Map 4: Number of Parcels with Questionable Transactions by Census Tracts Parcels Identified on Map 1, Map 3 or Both Tract Unknown Total Analysis 1 & XX Census Tracts & Tract Number Boundary of City of Mansfield Streets Number of Questionable Parcels Number of Questionable Parcels XX N = 14 Map prepared by the Center for Urban and Regional Analysis, July 00 0 N