111111
`
`1111111111111111111111111111111111111111111111111111111111111111111111111111
`us 20050154657 Al
`
`(19) United States
`(12) Patent Application Publication
`Kim et ai.
`
`(10) Pub. No.: US 2005/0154657 Al
`J ul. 14, 2005
`(43) Pub. Date:
`
`(54) CONDITION SCORING FOR A PROPERTY
`APPRAISAL SYSTEM
`
`(76)
`
`Inventors: Christopher D. Y. Kim, Littleton, CO
`(US); Charles J. Gadd, Littleton, CO
`(US); Andrea Cope, Littleton, CO
`(US); Santiago Silva, Littleton, CO
`(US)
`
`Correspondence Address:
`HENSLEY KIM & EDGINGTON, LLC
`1660 LINCOLN STREET, SUITE 3050
`DENVER, CO 80264 (US)
`
`(21) Appl. No.:
`
`11/034,456
`
`(22) Filed:
`
`Jan. 12,2005
`
`Related U.S. Application Data
`
`(60) Provisional application No. 60/536,107, filed on Jan.
`12, 2004. Provisional application No. 60/536,111,
`filed on Jan. 12, 2004. Provisional application No.
`60/536,215, filed on Jan. 12, 2004.
`
`Publication Classification
`
`(51)
`
`Int. CI? ..................................................... G06F 17/60
`
`(52) U.S. CI. ................................................. 705/30; 705/19
`
`(57)
`
`ABSTRACT
`
`An appraisal system obtains reliable information relating to
`subjective property characteristics of a property and quan(cid:173)
`tifies the contributions of such subjective characteristics on
`the value of the property. An appraiser enters subjective
`property information regarding a subject property into the
`appraisal system, which evaluates other properties using
`property data obtained from property databases to identify
`comparable properties. Key condition data for the compa(cid:173)
`rable properties is extracted from subjective property char(cid:173)
`acteristics available from the real estate property data. The
`key condition data for both the subject property and the
`comparable properties is catagorized and assigned condition
`scores based on the characteristic's impact on the property
`valuation. The condition scores for each property are com(cid:173)
`bined into composite condition scores, which can be quan(cid:173)
`tifiably compared with property characteristics to assist in
`selecting comparable properties. The condition scores of the
`subject property may also be employed to adjust the result(cid:173)
`ing appraisal value.
`
`Client Computer
`108
`
`Web Browser
`106
`
`NETWORK
`11.Q
`
`Property Tax
`Records Database
`ill
`
`Appraisals
`Database
`ill
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`Web Server
`104
`
`Appraiser
`Valuation
`Engine
`102
`
`Database
`ill
`
`1100
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`MLS Server
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`

`Patent Application Publication Jui. 14,2005 Sheet 2 of 15
`
`US 2005/0154657 Al
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`4. Appraisers guidelines (Fannie Mae) are followed 10 bring you the most accurate comparables
`3. Comparables are searched by the closest and mosl Similar and then matched In the smallest dalai!.
`2. Data Is UPdated weeklyJo( the most recent information.
`t. Tax, Deed, and MLS Information are combined to bring you the most comprehensive property Information.
`
`• Wetd
`• Je1ferson
`• Elbert
`• Douglas
`• Denver
`• Broomfield
`• Boulder
`• Arapahoe
`• Adams
`
`NOTE: Currenlly we have the follOWing counties available fOr sear<hing:
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`Step 2 -Select any amenities the subject has in order to insure the best match.
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`39.574412592233 Long: ·105,101158640777
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`"i
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`,style:
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`T'ype:
`
`Lat:
`
`Step 1 --Verify the Information from the tall record and edit If necessary.
`
`402 {
`
`1980
`
`YOC:
`
`Owner O<:<:pd: Y
`
`GAOO CHARLES J
`
`OwnerNatna
`
`519200
`
`MEAOOWS FLO 112 THE
`
`SUbNum:
`
`SUbName:
`
`Stondard SubName:' MEAOOWS
`
`S260 W CANYON PI..
`
`80128-7539
`
`LITTLETON
`
`Zip
`
`CIty ;
`
`Street;
`
`•
`
`My Account
`
`s.,arch for .. New Property
`
`See property Tox Record Detail
`
`Subject Property Found: 742637
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`bll!@lial~
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`D Sauna:
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`AIr CondItioning: D
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`Patio::
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`0
`D eo-ed PsIio:
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`Hot Tub:
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`'9'91 4
`
`406 {
`
`Double p""" 1Mndows: D
`0
`Mother·ln-law Api:
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`I Deck:
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`Pool:
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`Predicted Value:
`Search SOFT Range: 1~.O.ll""""""'N""~"""".J +/-sqft from Subject Sqft
`Search Range:
`
`12._
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`Step 5 .. Select the search range to look for comps.
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`Sacks to oPen Spec« 0
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`Bacl<s to Water:
`Bacl<s to Golf Course: 0
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`Becks to Perk: 0
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`
`step 4 .. Select any location features of the subject that affect its value.
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`Updsled FloOrs: OJ
`New furnace; 0
`Adjust Seles Price for Condition: 0
`Step 3 .. Select any features of the subject that affect its condition.
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`Copyrighl2003 by 6lue Lime Soltwere. Inc.
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`Feedback
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`604
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`_!2~)'~.!'!!~! ' •
`rSi--t'Wi9W~#1"fl!¥$7~.
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`Max Records Returned: r.1!~.~:-, .. -".-.,-.. ,-"----,-,,,-,,--;,,.i
`r:; Use Alternate Rank Math2
`M Use Alternate Rank Math
`f"!', Obey'Sold Date Requirements
`C Use New Type Grouping for Rearch
`I'J Automatic Price Range
`Admin Tu'nlngOptions:
`
`[j Save WelghtValues as Defaults
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`• Once you have all comps whom yOU want them you can dick the 'VIew Subject F'ropertyEst!mateci VallJfi bU1ton to get yourvaluallon,
`• ~you need to see more alternate comps emer lIIe value In the form at Ih.a botlom ortha page and click the button.
`• The lowerlhe Rank ",Iue tne clo.erlhe comp mat.:he. tile SUbl!l£~ s. keep this In mind when •• lectlng allemate camps.
`
`button. You can atso change oul any otIler comp by selecting It and tne alternate comp you wish to replace and clicking tne button.
`• Replace any comps that are oul afrange by selected Ihe all.mate camp that you wiSh to reptace and cliCking lhe ·Replace.CampS"
`•
`
`If you ellcktne address (orthe subject or any comp'IIlU can .. swlhe detail ror each PJopeny, ootntne poe .~d MLS records.
`months (yellow) .rid one >Mthin 12 months (green).
`
`• Check far a!lY problems >Mth tne pllee spread (0113 comps should a.Within 20%), also notetna! at least 2 comps muslbe witl1ln 6
`
`Step 6 -Review the top three compo selected by the system.
`
`702
`
`t
`
`My Ac<:ount •
`
`Total comps located: 301
`
`Bads to Sllbje~ pronerty page
`
`~ S<MrdI fa, a New Property
`
`

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`• Once you haVe' all camps where,you want them veti 'can click ihe ~ew Subject Property Estima1ed Val~e~ button 10 getyourvaluation,
`
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`LITTLETON, CO 80128
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`Patent Application Publication Jui. 14,2005 Sheet 15 of 15
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`

`

`US 2005/0154657 A1
`
`Jul. 14, 2005
`
`1
`
`CONDITION SCORING FOR A PROPERTY
`APPRAISAL SYSTEM
`
`RELATED APPLICATIONS
`
`[0001] The present application claims benefit of U.S.
`Provisional Patent Application No. 60/536,107, entitled
`"Condition Score Appraisal"; U.S. Provisional Patent Appli(cid:173)
`cation No. 60/536,111, entitled "Methods and Systems for
`Ranking Comparable Properties for Property Appraisals";
`and U.S. Provisional Patent Application No. 60/536,215,
`entitled
`"Data Source Determination
`for Property
`Appraisal", all filed on Jan. 12,2004 and specifically incor(cid:173)
`porated by reference herein for all that they disclose and
`teach.
`
`[0002] The present application is also related to U.S.
`patent application Ser. No. ___ [Attorney Docket No.
`236-004-USP], filed Jan. 12, 2005 and entitled "Ranking
`Comparable Properties for Appraisal", specifically incorpo(cid:173)
`rated by reference herein for all that it discloses and teaches.
`
`TECHNI CAL FIELD
`
`to property
`relates generally
`invention
`[0003] The
`appraisal systems, and more particularly to condition scor(cid:173)
`ing in a real estate property appraisal system.
`
`BACKGROUND
`
`[0004] Generally, an appraiser attempts to judge the value
`of a given real estate property using a variety of objective
`and subjective characteristics of the property. Some exem(cid:173)
`plary objective characteristics may include without limita(cid:173)
`tion the location of the property, the size of the property, and
`the square footage of any structures on the property. A
`typical appraisal involves selecting recently-sold properties
`having characteristics similar to those of the subject property
`and using the recent sales prices of these "comparable"
`properties to set a value for the subject property.
`
`[0005] While not trivial, objective property characteristics
`are relatively easy to obtain, quantify, and compare in an
`appraiser valuation engine. As such, existing computerized
`appraisal systems can employ objective property character(cid:173)
`istics to develop comparable properties. However, subjec(cid:173)
`tive property characteristics are typically more difficult to
`obtain, less reliable in their accuracy, and more difficult to
`use in a quantitative comparison process of an appraisal. As
`such, it is generally left to the appraiser to make a subjective
`evaluation of subjective property characteristics and apply
`his or her impressions resulting from that evaluation during
`the selection of comparable properties and the setting of
`property values.
`
`[0006] Naturally, the impact of such subjective impres(cid:173)
`sions on a property valuation can vary dramatically among
`different appraisers and even with the same appraiser on
`different days. Furthermore, existing approaches have been
`ineffective in automating the incorporation of such subjec(cid:173)
`tive property characteristics into the appraisal process. As
`such, it is difficult to obtain consistent valuations across
`many property samples in a relatively fast manner.
`
`SUMMARY
`
`Implementations described and claimed herein
`[0007]
`address the foregoing problems by obtaining reliable infor-
`
`mation relating to subjective property characteristics and
`quantifying the contributions of such subjective character(cid:173)
`istics on the value of a property. By incorporating the
`subjective characteristics of a given property and the sub(cid:173)
`jective characteristics of "comparable" properties, a more
`accurate valuation for the subject property may be obtained.
`[0008] Accordingly, an appraiser can enter subjective
`property information regarding a subject property into an
`appraisal system. The appraisal system evaluates other prop(cid:173)
`erties using real estate property data obtained from one or
`more property databases to identify comparable properties.
`Key condition data for
`the comparable properties is
`extracted from subjective property characteristics available
`in or discemable from the real estate property data. The key
`condition data for both the subject property and the com(cid:173)
`parable properties is categorized and assigned condition
`scores based on the characteristic's perceived impact on the
`value of the property. The condition scores for each property
`are combined into composite condition scores, which can be
`quantifiably compared in combination with other objective
`property characteristics to assist in selecting comparable
`properties for the appraisal. The condition scores of the
`subject property may also be employed to adjust the result(cid:173)
`ing appraisal value.
`[0009]
`In some implementations, articles of manufacture
`are provided as computer program products. One implemen(cid:173)
`tation of a computer program product provides a computer
`program storage medium readable by a computer system and
`encoding a computer program. Another implementation of a
`computer program product may be provided in a computer
`data signal embodied in a carrier wave or other communi(cid:173)
`cation media by a computing system and encoding the
`computer program.
`[0010] The computer program product encodes a com(cid:173)
`puter program for a computer process executing on a com(cid:173)
`puter system. The computer process quantifies condition of
`a real estate property. Real estate property data that includes
`a plurality of subjective condition characteristics relating to
`the real estate property is received. Key condition data is
`extracted from the subjective condition characteristics in the
`real estate property data. Elements of the key condition data
`are categorized into one or more predefined condition cat(cid:173)
`egories, wherein each predefined condition category is asso(cid:173)
`ciated with a condition contribution score. A condition
`contribution score is associated with the real estate property,
`if an element of the key condition data is categorized in the
`predefined condition category associated with the condition
`contribution score.
`[0011]
`In another implementation, a method is provided
`that quantifies condition of a real estate property. Real estate
`property data that includes a plurality of subjective condition
`characteristics relating to the real estate property is received.
`Key condition data is extracted from the subjective condi(cid:173)
`tion characteristics in the real estate property data. Elements
`of the key condition data are categorized into one or more
`predefined condition categories, wherein each predefined
`condition category is associated with a condition contribu(cid:173)
`tion score. A condition contribution score is associated with
`the real estate property, if an element of the key condition
`data is categorized in the predefined condition category
`associated with the condition contribution score.
`[0012]
`In another implementation, an appraisal system
`that quantifies condition of a real estate property is provided.
`
`

`

`US 2005/0154657 A1
`
`Jul. 14, 2005
`
`2
`
`A database receives real estate property data including a
`plurality of subjective condition characteristics relating to
`the real estate property. An appraisal valuation engine
`extracts key condition data from the subjective condition
`characteristics in the real estate property data. The appraisal
`valuation engine also categorizes elements of the key con(cid:173)
`dition data from the real estate property data into one or
`more predefined condition categories, wherein each pre(cid:173)
`defined condition category being associated with a condition
`contribution score. A condition contribution score is asso(cid:173)
`ciated with the real estate property, if an element of the key
`condition data is categorized in the predefined condition
`category associated with the condition contribution score.
`
`In yet another implementation, a system quantifies
`[0013]
`condition of a real estate property. The system provides
`means for receiving real estate property data that includes a
`plurality of subjective condition characteristics relating to
`the real estate property, means for extracting key condition
`data from the subjective condition characteristics in the real
`estate property data, means for categorizing elements of the
`key condition data from the real estate property data into one
`or more predefined condition categories, each predefined
`condition category being associated with a condition con(cid:173)
`tribution score, and means for associating a condition con(cid:173)
`tribution score with the real estate property, if an element of
`the key condition data is categorized in the predefined
`condition category associated with the condition contribu(cid:173)
`tion score.
`
`[0014] Other implementations are also described and
`recited herein.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`[0015] FIG. 1 illustrates an exemplary system for provid(cid:173)
`ing property appraisals using subjective property character(cid:173)
`istics.
`[0016] FIG. 2 illustrates a login page of an exemplary
`appraiser valuation engine.
`[0017] FIG. 3 illustrates a property identification page of
`an exemplary appraiser valuation engine.
`[0018] FIG. 4 illustrates a portion of a condition and
`weighting page of an exemplary appraiser valuation engine.
`[0019] FIG. 5 illustrates another portion of a condition
`and weighting page of an exemplary appraiser valuation
`engine.
`[0020] FIG. 6 illustrates yet another portion of a condition
`and weighting page of an exemplary appraiser valuation
`engine.
`[0021] FIG. 7 illustrates a portion of a comparable prop(cid:173)
`erty page of an exemplary appraiser valuation engine, the
`page portion showing a map that marks locations of the
`comparable properties and a subject property.
`[0022] FIG. 8 illustrates another portion of a comparable
`property page of an exemplary appraiser valuation engine,
`the page showing a portion of a top-ranked comparable
`properties list.
`[0023] FIG. 9 illustrates another portion of a comparable
`property page of an exemplary appraiser valuation engine,
`the portion showing another portion of a top-ranked com(cid:173)
`parable properties list.
`
`[0024] FIG. 10 illustrates yet another portion of a com(cid:173)
`parable property page of an exemplary appraiser valuation
`engine, the page showing a portion of an alternative com(cid:173)
`parable properties list,
`[0025] FIG. 11 illustrates yet another portion of a com(cid:173)
`parable property page of an exemplary appraiser valuation
`engine, showing a portion of an alternative comparable
`properties list.
`[0026] FIG. 12 illustrates a portion of an estimated value
`page of an exemplary appraiser valuation engine.
`[0027] FIG. 13 illustrates another portion of an estimated
`value page of an exemplary appraiser valuation engine.
`[0028] FIG. 14 illustrates operations of an exemplary
`appraiser valuation engine.
`[0029] FIG. 15 illustrates an exemplary system useful in
`implementations of the described technology.
`
`DETAILED DESCRIPTION
`
`[0030] Subjective property characteristics are not well
`utilized in real estate appraisal processes. First, while objec(cid:173)
`tive property characteristics are easily obtained from public
`records databases and property information services, such as
`a Multiple Listing Service (MSL), sources of reliable and
`consistent subjective property characteristics are rare or
`non-existent. Furthermore, typical property valuation sys(cid:173)
`tems, such as Automatic Valuation Models ("A VMs"), are
`not configured to operate on subjective data. For example,
`the condition (e.g., the physical and aesthetic condition) of
`a property is an important property characteristic to be
`considered when setting a value of a property. However, in
`contrast to objective property characteristics, such as square
`footage, the condition of a property has substantial subjec(cid:173)
`tive components that do not lend themselves to quantitative
`comparison in a typical property valuation system. For
`example, whether new bathroom features contribute posi(cid:173)
`tively to the value of a house is a subjective consideration.
`
`[0031] Moreover, such subjective characteristics influence
`both the value of a property being appraised as well as
`comparable properties considered in the appraisal process.
`As such, an exemplary property appraisal system collects
`and quantifies subjective information about the condition of
`a subject property as well as the conditions of potential
`comparable properties in order to evaluate this information
`using an appraiser valuation engine. Other subjective prop(cid:173)
`erty characteristics may also be considered in this manner.
`[0032] FIG. 1 illustrates an exemplary system 100 for
`providing property appraisals using subjective property
`characteristics.
`In
`the
`illustrated
`implementation, an
`appraiser valuation engine 102 resides on a web server 104
`and accesses an appraisal system database 112. In an exem(cid:173)
`plary scenario, an appraiser will access the appraiser valu(cid:173)
`ation engine 102 across a communications network 110
`using a web browser 106 on a client computer 108. How(cid:173)
`ever, alternative implementations are contemplated, includ(cid:173)
`ing non-web-based solutions and configurations where the
`user accesses an appraiser valuation engine that is resident
`on the client computer, rather than on a server computer.
`[0033] The appraisal valuation engine 102 has access to
`property information, such as information available from a
`Multiple Listing Service (MLS) server 114, property tax
`
`

`

`US 2005/0154657 A1
`
`Jul. 14, 2005
`
`3
`
`records databases 116, and appraisals databases 117,
`although other property information sources may also be
`employed. Subject property data may be retrieved from
`these databases. In one implementation of the described
`system, the comparable property data is also available from
`the remote databases and is periodically (e.g., nightly)
`downloaded, "cleaned", and stored in the appraisal system
`database 112. Alternatively, or in addition, comparable prop(cid:173)
`erty data may be downloaded responsive to a request from
`a user and stored at that time in the appraisal system
`database 112.
`
`[0034] When using the system 100 in the illustrated sce(cid:173)
`nario, the appraiser is attempting to determine an accurate
`value of a subject property. One stage of this valuation
`process is to find reference properties with characteristics
`that are "comparable" to those of the subject property.
`Valuation judgments about the subject property can then be
`based on characteristics of these comparable properties,
`such as recent sale prices.
`
`[0035] As such, the appraiser accesses the appraiser valu(cid:173)
`ation engine 102 and inputs information that identifies the
`subject property, such as the property's address. Given the
`identification information about the subject property, the
`appraiser valuation engine 102 may access one or more
`property information sources (e.g., 112, 114, 116, and/or
`117) to obtain relevant real estate property data, such as
`MLS data, tax assessment data, previous sale data, previous
`appraisal data, etc. In addition, the appraiser val