Many even support one of the most crucial new web trends: responsive design, which can. Office Flesher Score Professional Freelance Copy In the United States, our primary readability tests are the Flesch Reading Ease formula and the FleschKincaid Grade Level formula. Flesch Reading Ease was created by reading expert Rudolf Flesch and popularized in his 1949 book The Art of Readable Writing.North West Reign North West Reign, Top of 1st:View the profiles of people named Mac Fluegar. Join Facebook to connect with Mac Fluegar and others you may know.Rojas Original Assignee Experian Information Solutions, Inc. WO2008147918A2 - System and method for automated detection of never-pay data sets- Google Patents WO2008147918A2 - System and method for automated detection of never-pay data sets- Google Patents System and method for automated detection of never-pay data setsDownload PDF Info Publication number WO2008147918A2 WO2008147918A2 PCT/US2008/064594 US2008064594W WO2008147918A2 WO 2008147918 A2 WO2008147918 A2 WO 2008147918A2 US 2008064594 W US2008064594 W US 2008064594W WO 2008147918 A2 WO2008147918 A2 WO 2008147918A2 Authority WO WIPO (PCT) Prior art keywords never pay data records score Prior art date Application number PCT/US2008/064594 Other languages French ( fr)( en Inventor Christopher J. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading The New Global Politics: Global Social Movements in the Twenty-First.
238000000034 method Methods 0.000 claims description 11 Publication of WO2008147918A2 publication Critical patent/WO2008147918A2/en Publication of WO2008147918A3 publication Critical patent/WO2008147918A3/en Links Filed Critical Experian Information Solutions, Inc. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.) Filing date Publication date Priority to US93190207P priority Critical Priority to US60/931,902 priority Application filed by Experian Information Solutions, Inc. ![]() 230000002349 favourable Effects 0.000 description 2 281999990011 institutions and organizations companies 0.000 description 3 230000018109 developmental process Effects 0.000 description 3 230000003542 behavioural Effects 0.000 description 3 Install mac os on emulator281000001425 Microsoft companies 0.000 description 1 281000114330 Experian companies 0.000 description 1 238000004450 types of analysis Methods 0.000 description 2 ![]() -1 electric Substances 0.000 description 1 230000003111 delayed Effects 0.000 description 1 230000002596 correlated Effects 0.000 description 1 238000005457 optimization Methods 0.000 description 1 230000003287 optical Effects 0.000 description 1 238000006011 modification reactions Methods 0.000 description 1 230000004048 modification Effects 0.000 description 1 239000007789 gases Substances 0.000 description 1 230000000007 visual effect Effects 0.000 description 1 230000001960 triggered Effects 0.000 description 1 230000011218 segmentation Effects 0.000 description 1 230000001105 regulatory Effects 0.000 description 1 G06Q40/00— Finance Insurance Tax strategies Processing of corporate or income taxes G06Q— DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR 238000005303 weighing Methods 0.000 description 1 G06Q20/10— Payment architectures specially adapted for electronic funds transfer systems specially adapted for home banking systems G06Q20/00— Payment architectures, schemes or protocols Risk analysis for mortgages G06Q40/025— Credit processing or loan processing, e.g. Interest calculation, credit approval, mortgages, home banking or on-line banking The never-pay population includes without limitation those customers that make a request for credit, subsequently obtain the credit instrument, and over the life of the account, never make a payment or substantially never make a payment. Prior to providing a credit account to an applicant, or during the servicing of such a credit account, many financial service providers want to know whether the applicant or customer will be or is likely to be within the "never-pay" population. G06Q30/06— Buying, selling or leasing transactions Various financial service entities provide credit accounts, such as, for example, mortgages, automobile loans, credit card accounts, and the like, to consumers and or businesses. Office Flesher Score Software Modules MayIt will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts. A software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. In general, the term "module," as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry andExit points, written in a programming language, such as, for example, Java, Lua, C or C++. In an embodiment, a never-pay automated detection system, the system comprising: a processor configure to run software modules a data storage device storing a plurality of consumer records comprising credit bureau data, tradeline data, historical balance data, and demographic data, the data storage device in electronic communication with the computer system and a never-pay module configured to: identify a subset of the plurality of consumer records from the data storage device receive a first never-pay data profile from a storage repository, the first never-pay data profile identifying consumer records that are likely or substantially likely to never make a payment apply the first never-pay data profile to each of the subset of the plurality of consumer records to generate a first never-pay score for each of the subset of the plurality of consumer records and store in a database an aggregate never- pay score associated with the subset of the plurality of the consumer records, the aggregate never-pay score comprising at least the first never-pay score the processor able to run the never-pay module. Most financial service providers can attribute a certain percentage of their losses to the never-pay population. The computing system 100 includes, for example, a personal computer that is IBM, Macintosh, or Linux/Unix compatible. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub- modules despite their physical organization or storage. The modules described herein are preferably implemented as software modules, but may be represented in hardware or firmware. It will be further appreciated that hardware modules may be comprised of connected logic units, such as, for example, gates and flip-flops, and/or may be comprised of programmable units, such as, for example, programmable gate arrays or processors. The computing system 100 further includes a memory 130, such as, for example, randomAccess memory ("RAM") for temporary storage of information and a read only memory ("ROM") for permanent storage of information, and a mass storage device 120, such as, for example, a hard drive, diskette, or optical media storage device.
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