Patent Publication Number: US-2017352101-A1

Title: Insurance rating computer system and computer-implemented method

Description:
FIELD OF THE DISCLOSURE 
     The present invention relates to methods and systems for rating stakeholders upon occurrence of damages in the exploitation of equipment (buildings, transportation equipment, industrial premises, etc.) covered by insurance policies. 
     BACKGROUND OF THE DISCLOSURE 
     The construction of a property or other equipment is generally subject to warranties after delivery (warranty of fitness/habitability). Thus when damages occur in the years following delivery, the liability of building contractors such as architects, masons, electrical enterprises, painters, etc., and more generally of originators of an equipment, can be involved. This liability is often covered by an insurance policy, in such way that the cost of repairs, e.g. to consolidate a building or bring it back to a state suitable for use, are covered by the insurance company. This insurance policy implies that the insured entity pays a premium to insurance company, the amount of this premium being calculated by insurance company as a function of the damage occurrence risks. 
     These risks are usually calculated by the building contractors by taking into account the following criteria:
         damage claim antecedents,   insurance antecedents: terminations, payment failures, periods of time without insurance coverage,   turnover and related financial information   staff figures,
           type of activity, and corresponding dangerousness and risk exposure,   
           the extent and duration of warranties.       

     The amount of premium or fee is often subject to tenders by clients. To this end, insurance comparators such as www.comparethemarket.com® or www.gocompare.com® can assist the clients in selecting their insurance company. 
     However, it is difficult to directly compare the risks and the contacts, despite improvements or finer categorizations of the insurance criteria. In addition, the execution of the contracts, their renewal and the initial selection of the companies that answer the call for tenders can vary. At the end, the gap between the actual risk and the risk actual coverage can be large. The insured entities are exposed to the payment of a premium which is too high in regard of the actual risk coverage, or the insurance companies receive a premium which is insufficient in regard of the risk they cover. 
     SUMMARY OF THE INVENTION 
     The present invention aims at providing a computer system and a computer-implemented methods involving servers and terminals at different levels of the chain, that allow reducing such gaps. 
     To this end, the present invention provides according to a first aspect a computer implemented rating system for insurance management in connection with at least one operator on an equipment obtained by a plurality of equipment originators and an insurance company providing insurance for said equipment, comprising:
         an operations server defining a schedule of tasks to be performed on said equipment,   an operator terminal capable of remote communications with said operations server and of transmitting to said operations server operation-related data,   a damages server capable of communications with said operations server and comprising means capable, in response to a recognized disorder, for attributing to the disorder a damage type identifier and an identifier of an originator probably liable for the damage, and means for generating corresponding damage claims,   an insurance server capable of communications with said damages server and configured to receive damage claims,   a rating engine for rating said operator, said originators and said insurance company based on damage estimation by operator input, by damages server and by insurance company input.       

     Preferred but non limiting aspects of this system comprises the following features, taken individually or in any technically compatible combinations:
         said damages server comprises means for recognizing disorders from said operation-related data.   said operation-related data comprise pictures taken with a camera of said operator terminal before and after a task is performed.   said operation-related data comprise geolocation information concerning task performance generated in said operator terminal.   said operation-related data comprise time-stamping information concerning task performance generated in said operator terminal.   said operation-related data comprise encumbrance levels of an equipment part to be cleaned, said encumbrance levels being derived from an error rate in a reading operation of a machine-readable code provided on said part by a code reader of said operator terminal.   said operation-related data comprise camera axis data of said operator terminal associated with pictures taken.   the system further comprises an equipment information model accessible by said operations server and said damages server.   said damages server is configured to locate a disorder by applying said geolocation information to said equipment information model.   said damages server is configured to locate a damage by further applying camera axis data to said equipment information model.   said operations is capable of deriving probable operator liability of a recognized disorder as a function of the location of said disorder in said equipment information model.   said means for recognizing disorders comprise an image analysis program capable of analyzing pictures taken by said operator terminal camera.   said damage estimation comprises a damage amount and a liability level.   said liability level comprises a distribution of liabilities among a plurality of damage originators.   said rating engine is configured to compute dispute rates.   said rating engine is configured to compute responsiveness rates of operator(s), originators and insurance company.   said rating engine is configured to compute gaps between damage estimations by at least two estimators in a group comprising an operator, an originator, an insurance company, an insurance expert and a court.   said rating engine is configured to compute damage-specific gaps.   said rating engine is configured to compute originator-specific gaps.   said rating engine is configured to compute insurance company-specific gaps.   said operator is an equipment maintenance operator, and said equipment is a real estate property.       

     According to a second aspect, the present invention provides a computer-implemented rating method for insurance management in connection with at least one operator on an equipment obtained by a plurality of equipment originators and an insurance company providing insurance for said equipment, comprising the following steps:
         providing at an operations server a schedule of tasks to be performed on said equipment,   providing task guidance on an operator terminal capable of remote communications with said operations server;   generating at said operator terminal operation-related data and transmitting said data to said operations server,   at a damages server capable of communications with said operation server, and attributing to a recognized disorder a damage type identifier and an identifier of an originator probably liable for the damage   transmitting a corresponding damage claim to an insurance server, and   performing rating computation for rating said operator, said originators and said insurance company based on damage estimation by operator input, by damages server and by insurance company input.       

     Preferred but non limiting aspects of this method comprises the following features, taken individually or in any technically compatible combinations:
         the method further comprises a step of recognizing disorders from said operation-related data at said damages server.   the method further comprises a step of taking pictures with a camera of said operator terminal before and after a task is performed, said pictures being included in said operation-related data.   the method further comprises a step of generating geolocation information in said operator terminal during task execution and including said geolocation information in said operation-related data.   the method further comprises a step of generating time stamps in said operator terminal during task execution and including said time stamps in said operation-related data.   the method further comprises a step of determining an encumbrance level of an equipment part to be cleaned from an error rate in a reading operation of a machine-readable code provided on said part by a code reader of said operator terminal, and including said encumbrance level in said operation-related data.   the method further comprises a step of determining a camera axis in said operator terminal while a picture is taken and including camera axis information in said operation-related data.   the method further comprises locating a damage by applying said geolocation information to an equipment information model.   said damage is located by further applying camera axis data to said equipment information model.   the method further comprises a step of deriving probable operator liability of a recognized disorder as a function of the location of said disorder in said equipment information model.   said disorder recognition step comprises performing image analysis on pictures taken by said operator terminal camera.   said damage estimation comprises a damage amount and a liability level.   said liability level comprises a distribution of liabilities among a plurality of damage originators.   said rating computation step comprises the computation of dispute rates.   said rating computation step comprises the computation of responsiveness rates of operator(s), originators and insurance company.   said rating computation step comprises the computation of gaps between damage estimations by at least two estimators in a group comprising an operator, an originator, an insurance company, an insurance expert and a court.   said rating computation step comprises the computation of damage-specific gaps.   said rating computation step comprises the computation of originator-specific gaps.   said rating computation step comprises the computation of insurance company-specific gaps.   said operator is an equipment maintenance operator and said equipment is a real estate property.       

    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Other features, aims and advantages of the present invention will better appear from the following description of preferred embodiments thereof, given by way of non limiting example and with reference to the appended drawings, in which: 
         FIG. 1  diagrammatically shows a computer system for implementing the present invention, 
         FIG. 2  illustrates a maintenance method according to the present invention, 
         FIG. 3  illustrates an incident or damage handling method according to the present invention, 
         FIG. 5  illustrates an operation method according to the present invention, 
         FIG. 4  illustrates a liability record generation method according to the present invention, 
         FIG. 6  illustrates a damage handling method according to the present invention, 
         FIG. 7  illustrates a damage claim handling method according to the present invention, and 
         FIG. 8  illustrates a rating method according to the present invention. 
     
    
    
     DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT 
     A computer-implemented rating method and system according to the present invention, involving in an insurance database, will now be described. 
     It should be noted here that the same reference numerals will be used in the following for a particular information storage area or register, for the nature of the information stored therein and for the value of such information. 
     In addition, the same reference numeral shall be used for different instances of variables or data sets. For instance, two different property identifiers for respective building information models  134  will be designated by the same reference numeral  1341 . 
     1) Computer System 
       FIG. 1  diagrammatically shows a computer system  100  implementing a preferred method of the present invention. 
     Computer system  100  comprises a set of terminals  110 - 114  capable of accessing computer servers  130 ,  140 ,  150 ,  160 ,  170  via a computer network  120  such as the Internet. Each terminal and each server comprise processing means for executing programs and storage means for storing data, and communications circuits for handling communications between servers and terminal according to appropriate protocols such as HTML, FTP, SMS, email, collaborative software, etc. 
     Reference  130  designates an operations server containing schedules  131 , construction or maintenance records  132 , an operations management module  133  and a modeling module  134 . 
     The present description will practically deal with the case of operations of maintenance of gutters in a group of buildings. In this case the maintenance server  130  stores maintenance schedules  131 , maintenance notes  132 , a computerized maintenance management (CMM) module  133  and a building information model (BIM)  134 . 
     A maintenance schedule  131  contains a list of maintenance operations to be performed according to a specific timetable. Thus the maintenance agent must clear the gutters of a group of building at regular intervals to avoid that dead leaves accumulating therein cause obstruction and a water disorder. 
     A maintenance schedule  131  is associated to a property identifier  1311  and is characterized in particular by a defined frequency of cleaning actions (or number of actions per time unit), stored at  1312 . 
     A maintenance record  132  details each visit made according to the maintenance schedule  131 . Each generated record  132  contains an identifier  1321  of the maintenance company, an identifier  1322  of the visit schedule to be followed by the maintenance agent, data  1323  representative of the locations where cleaning should be performed, e.g. the gutter ends. It can additionally contain pictures  1326  taken by the maintenance agent before the operation and pictures  1327  taken after the operation, as well as geolocation data  1324  and timestamp data  1325  of these pictures, data  1332  proving the performance of maintenance operation and maintenance reports  1331 . 
     The maintenance schedule  131  and the notes  132  are generated by CMM module  133 . This module is based on a CMMS (Computerized Maintenance Management System) software package that maintains a computer database of information about maintenance operations in an organization. Preventive maintenance tends to follow planned guidelines from time-to-time to prevent equipment and machinery breakdown. The care and servicing by personnel for the purpose of maintaining equipment and facilities in satisfactory operating condition tends to provide systematic inspection, detection, and correction of incipient failures either before they occur or before they develop into major defects. 
     CMM module  133  cooperates with BIM module  134 , which for instance is a software package commercially available as FM:Interact®, co-developed by FM:Systems® et Autodesk®. 
     CMM module  133  is capable of generating a proof of passage, stored at  1332 , by applying the following rule: the proof of passage  1332  is validated only if the geolocation  1324  of the picture  1327  taken after the operation complies to the one provided in maintenance schedule  131 . 
     CMM Module  133  can be configured to measure the encumbrance level of the gutters, stored at  1335 ,  1336 . For this purpose, CMM module  133  contains a QR-Code interpretation program, known per se to the skilled person. In this regard, the QR-Code standard provides a certain level of redundancy, typically of the Reed-Solomon type, in order that a code can still be read even when strongly deteriorated. The QR-Code interpretation program is thus capable of measuring an read error rate which is proportional to the degradation of the code. In the present application, QR-Codes of appropriate size are painted or printed in the gutters of the buildings to be maintained and captured by the maintenance agent. As the gutters are more or less covered with dead leaves, the reading of the QR-Code provides a more or less important error rate. Thus module  133  is capable of measuring the degree of encumbrance of the gutters by using the error rate of the QR-Code reading caused by the presence of leaves on pictures  1326 ,  1327 . This degree of encumbrance is stored at  1335 ,  1336 . Of course other technical means can be used to determine the encumbrance level of the gutters, such as color and/or reflection based image recognition, etc. 
     The CMM module  133  can further compute the task duration  1333  by difference between the timestamps of pictures  1326  and  1327 . 
     The CMM module  133  is also capable of generating a maintenance report  1331  that synthetizes in an appropriate format the set of data  1332 ,  1333 ,  16552  relating to the corresponding maintenance record  132 . 
     Operations server  130  contains a building information modeling (BIM) program  134 . A BIM is a digital representation of physical and functional characteristics of a facility. A BIM is a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life cycle. It carries all information related to the building, including its physical and functional characteristics and project life cycle information, in a series of “smart objects”. For example, an air conditioning unit within a BIM would also contain data about its supplier, operation and maintenance procedures. Throughout the construction period, the project team must continuously update the BIM model so that it reflects the most up-to-date information which later on can be used by the facility managers for building operations and maintenance. This makes it very simple for a maintenance worker to access the required information vital to different systems in the building. The advances in smartphones and tablet devices (such as iPhone® and iPAD®) and Augmented Reality (AR)  1343  has made it possible to obtain complete information about a building component by just pointing the device towards it (AZHAR, Salman; KHALFAN, Malik; MAQSOOD, Tayyab. “ Building information modelling  ( BIM ):  now and beyond ”, Construction Economics and Building, [S.I.], v. 12, n. 4, p. 15-28, oct. 2015. ISSN 2204-9029). Information requirements can be identified and flow can be established. Identifying the necessary information and establishing flow of information is an important part of improving the contractor&#39;s work. 
     The BIM program  134  stores in particular property identifiers  1341  and their geolocations  1342 . 
     Incident and damage server  140  contains a management module  141 , a database  142  of incident records, and a database  143  of liability records. 
     Management module  141  further contains a disorder recognition program  1411  that is capable of identifying a disorder type  1423 , of establishing a proof  1425  of a disorder that affects a property based on geolocalized pictures  1424  which the program interprets in cooperation with building information model  134 . 
     Such program is for instance of the type developed by the Fraunhofer Institute for Industrial Mathematics. The researchers have extracted metrics from photographs that include the characteristically elongated shape of a hairline crack, the typical discoloration in damp places, and the structures of the material, which are different for a concrete than for a steel bridge. When the researchers load a photo into the program, the program compares the features of the new image with those of the saved images. If it detects any irregularities, it marks the respective area on the picture. Article “ Accelerated Bridge Construction: Best Practices and Techniques ”, Mohiuddin Ali Khan Elsevier, 2014 describes such program. 
     Management module  141  contains a cost estimation program  1412  that cooperates with building information model  134 . It is possible to develop detailed cost plans through linking a ‘5D Cost Library’ to BIM, which performs the function of an estimating database. A ‘master’ library can be formed, in addition to several project specific variation libraries, making the process highly productive and easily repeatable (VICO Software, 2012). This allows varying levels of detail to be applied to estimates, depending on the project stage (cf. “ Advantages and Challenges of Using BIM: a Cost Consultant&#39;s Perspective ”, Niraj Thurairajah and Dan Goucher, Associated Schools of Construction, 2013). For instance, if a disorder picture  1424  shows a stain on an outside wall, this program  1412  can deduct by image analysis the need for replacement of the wall coating in a rectangular area encompassing this stain. The program then estimates the amount required for repairing the damages and writes it into register  1432 . 
     Incident or damage records  142  allow operators to notify and follow up disorders. Each record  142  is characterized by a property identifier  1421 , an incident or damage type  1423  represented by a reference in list  171 , pictures  1424  of disorders, proofs  1425  of disorders, incident or damage diagnostic reports  1426 , a record validation button  1427  and insurance claim data  1428 . 
     Liability records  143  allow allocating the liability of a damage to a contractor or to split it between a plurality of contractors. Each record is characterized by a liability distribution  1431 , an estimate  1432  of the amount of damages connected to an incident or damage, and validation buttons  1433 - 1436  for validation by the various contractors and operators. 
     Insurance server  150  contains a management module  151  and a database  152  of damage claims. 
     Indicators server  160  contains a management module  161 , a time-stamping module  162  for time-stamping the claim declaration methods  300  or the claim handling methods  400 , contractor-specific indicator records  165  and insurance company-specific indicator records  169 . 
     A contractor record  165  is characterized by a contractor type  1652  (maintenance company, architect, tiler, mason, etc.), a database damage amounts  1653  and liability levels  1654 , ratios concerning the contractor performance (efficiency ratio  1655 , schedule compliance ratio  1656 ), ratios concerning incidents and insurance (damage risk  1657  and responsiveness  1658 ), and notes  1659 . 
     An insurance company record  169  contains indicators  1691 - 1699  of the company&#39;s activity. 
     Statistics server  170  contains a list  171  of damages, a database  172  of liability statistics by contractor type, a database  173  of liability statistics by damage type and a database  174  of liability statistics by insurance company. 
     Damages list  171  is a tree-structure of references with different accuracy levels, e.g. as follows:
           1711 —theft     1712 —fire     1713 —water damage     17131 —wall seepage     17132 —drain overflow or backflow     17133 —pipe leak or rupture     17134 —roof, terrace or upper floor seepage     171341 —roof     1713411 —gutter     171342 —upper floor     1713421 —sanitary facilities     17134211 —seals/gaskets       

     Database  172  of liability statistics by contractor type stores records  1721  of maintenance companies, records  1722 - 1724  of other contractor types and records  1729  of operators. 
     Database  173  of liability statistics by damage type contains statistics  1731  concerning a first reference (in this example  1713411  for a gutter) of damage list  171  and statistics  1732 - 1734  concerning other references (in this case three other references) of the list  171 . 
     Database  174  of insurance statistics, common to all insurance companies, contains a database  1741  of statistics concerning reference  1713411  of list  171  and databases  1742 - 1744  concerning in this case said three other references of the list  171 . 
     2) Maintenance Management Method 
     Referring to  FIG. 2 , terminal  110  is a smartphone allowing a maintenance agent to access maintenance server  130  via a user interface  1104 . Upon invitation from the visit schedule  1322 , the maintenance agent can take a picture of a QR-Code by means of smartphone camera  1103 . Pictures are taken before and after the maintenance operation, so that it can be deducted that dead leaves that partially or totally covered the QR-Code before the maintenance operation have been swept off. Geolocation and timestamp information as provided by GPS unit  1102  and clock of smartphone  110  are associated to picture  1326  before maintenance and picture  1327  after maintenance. The maintenance report completes itself progressively as the visit progresses, the duration  1333  of each task provided in the visit schedule information  1322  and a corresponding performance ratio  16552  being recorded into the report. 
     3) Incident or Damage Management Method 
     Now referring to  FIG. 3 , terminal  113  is in the present example a smartphone allowing a first agent of the operator to access the incident and damage server  140  via the Internet  120 . Interface  1134  allows the generation of an incident record  142 . 
     Through matching between the geolocation provided by the GPS unit  1132  of smartphone and the geolocation  1342  stored in the building information model  134 , management module  141  can pre-fill the property identifier  1421  by copying and pasting item  1341 . By means of camera  1133  of smartphone  113 , the agent can take pictures of the disorders  1424  for illustrating the incident, e.g. a stain on a wall which reveals water seepage. 
     By combining the geolocation provided by GPS unit  1132  and the  3 D orientation of the camera, provided in a manner known per se by a gyroscope unit  1135  of smartphone  113 , management module  141  can compute the locations  14261  of the disorder pictures  1424  and locate them on the building information model  134 . For this purpose, module  141  cooperates with the augmented reality component  1343  of building information model  134 . 
     By image analysis of the disorder pictures  1424 , the disorder recognition unit  1411  can determine the type  1423  of incident or damage. 
     Once an incident or damage type  1423  has been determined, e.g. a water damage, and based on information of proximity of these locations  14261  with water ducts as referenced in building information model  134 , management module  141  can compute the most probable origin  14262  of leak, in the present example a gutter. 
     By correspondence of this most probable origin  14262  with the property identifiers  1421  then  1311  in maintenance server  130 , management module  141  can retrieve the identifier  1321  of the maintenance company in charge of maintaining of the gutter, and this identifier is copied and pasted into the register  14263  identifying the allegedly liable company. 
     By correspondence between this probable origin  14262  with contractor identifier  1321 , management module  141  also copies and pastes into register  14264  the performance indicators  1655 ,  1656  and the insurance ratios  1657 ,  1658  concerning this contractor identifier  1321 , and generate therein a link to the maintenance reports  1331 . 
     It should be noted here that in addition or as a substitution of the computer-implemented disorder recognition, disorders can also be recognized by human inspection of data, esp. picture data, originating from agent&#39;s terminal  113 . 
     4) Liability Record Generation Method 
     Referring to  FIG. 4 , terminal  111  is in the present example an personal computer allowing a second agent of the operator to access incident record  142 . User interface  1114  displayed on screen  1111  of terminal  111  allows the agent to visualize a liability record  143 . This record is generated and pre-filled by management module  141 , which copies and pastes the identifier  14263  of the supposedly liable company (or several identifiers of several companies) into liability register(s)  1431 , establishes a damage proof  1425  by means of disorder recognition module  1411 , and estimates the cost  1432  of repair by means of module  1412 . This second agent of the operator can validate this liability record  143  by actuating validation button  1433  after having modified if needed the pre-filled data. 
     5) Operating Method 
       FIG. 5  shows an operating method  200  performed by a contractor agent. This operation comprises a set of building or maintenance actions in a property, as defined in predefined schedule  131 . In the present particular example, the operating method  200  is an operation of maintenance of gutters of a group of buildings. 
     The maintenance agent is equipped with a smartphone  110  which allows him to connect via the Internet  120  to maintenance server  130  and to the maintenance record  132  that corresponds to the date of his visit on site in the maintenance schedule  131 . 
     At step  210 , visit schedule  1322  is displayed on display screen  1101  of the maintenance agent smartphone  110 . This visit schedule  1322  indicates to agent on a map of the building the passage points  1323 , for instance the gutters or downpipes that he has to clean. To these passage points  1323  are associated on-site QR-Codes, e.g. painted inside each gutter of the building. 
     At step  220 , in response to guidance from visit schedule  1322 , the maintenance agent takes pictures  1326  before the maintenance operation and pictures  1327  after the maintenance operation, of the QR-Code at the passage point by means of the camera  1103  of his smartphone  110 . CMM module  133  generates or supplements maintenance report  1331  with the passage proof data  1332  using the geolocation  1324 , the task duration  1333  obtained by the time-stamping  1325 , and the encumbrance levels  1335 ,  1336  of the gutters before and after maintenance. Management module  161  computes a work quality  16551  by difference between encumbrance levels  1335 ,  1336 . CMM module  133  computes a performance ratio  16552  by means of the following formula: 
       performance 16552=gutter encumbrance level 1335×work quality 16551/task duration 1333.
 
     At step  230 , management module  161  computes indicators  16561 - 16562  concerning the set of maintenance records  132  of the maintenance company, as follows: 
       visit ratio 16561=number of proofs 1332 of visits/number 1312 of 
       intended visits in maintenance schedule 131 
       average performance ratio 16562=mean value of performance ratios 
       16552 
     At step  240 , management module  161  computes a rate  1656  of compliance with the maintenance schedule  131  according to the formula: 
       compliance rate 1656=visit ratio 16561×average performance ratio
 
       16562. 
     6) Damage Handling Method 
       FIG. 6  shows a method  300  for handling an incident or damage. 
     At step  310 , a first agent of the operating company, equipped with a smartphone  113 , generates an incident record  142  by means of user interface  1134  and takes pictures  1424  of the disorders by means of the smartphone camera. Management module  141  pre-fills the fields  1421  identifying the property, computes the locations  14261  of the disorder pictures  1424 , locates them on the building information model  134 , establishes the incident or damage type  1423  and the proof  1425  of the disorders from the geolocated pictures as described above. 
     At same step  310 , management module  141  generates a diagnostic report  1426 . For this purpose, it determines the e most probable origin  14262  of the disorders by using the disorders location  14261  and the proof  1425 , and determines therefrom the enterprise(s) (contractor(s)) which is/are supposed to be responsible, the identifier thereof being stored at  14263 , copies and pastes into register  14264  the performance indicators  1655 - 1656  and the insurance ratios  16572 - 1658  of this contractor or these contractors  14263 . The incident record  142 , as validated by this first agent by actuating validation button  1427 , is sent e.g. via email to the predefined terminal  111  of a second agent. 
     At step  320 , terminal  111  of the second operating company agent receives said notification. Management module  141  generates and pre-fills a liability record  143  and more particularly a liability item  1431  and a damage estimation item  1432 . Module  141  further copies and pastes into register  14264  performance indicators  1655 - 1656  and insurance ratios  16572 - 1658  of contractor(s)  14263 . The second agent validates the liability record  143  by actuating a validation button  1433  on the terminal display. Module  141  notifies the validation of this record to the predefined terminal  112  of contractor  14263 , e.g. via email transmission. 
     At step  330 , an agent of contractor  14263  is equipped with a terminal such as a PC and accesses via the Internet  120  to an incident and damage server  140  and reads the incident record data  142  and the liability record data  143 . Contractor agent validates the damages assessment data  1432  and liability data  1431  by actuating a validation button  1434 . This time-stamped validation is also notified to the to management module  161  of server  160 , which copies and pastes the damages estimation  1432  into register  1653  of contractor record  165  and its liability level  1431  into register  1654 . Management module  161  updates the average damages amount  16571  by computing the average of damages  1653  and updates the average liability  16572  by computing the average of liabilities  1654 . 
     Steps  331  and  441  are triggered if the liability register splits the liabilities between a plurality of contractors. In such case, the additional contractors are invited to validate the damages assessment data  1432  and the liability level data  1431  by actuating respective validation buttons  1435 - 1436 . 
     At steps  320 ,  330 ,  331  and  332 , management module  161  stores into time-stamp register  162  the duration of the steps of method  300 . 
     At step  340 , management module  161  computes a responsiveness value  1658  for the various contractors. For this purpose, module  161  determines the time difference between the time stamps stored in register  162 , thus determining the duration  1621  of each step of method  300 ; module  161  computes the average  1622  of durations  1621  operator by operator, and the average  1623  of durations for all operators, and determines therefrom a responsiveness value  1658  by taking into account a contractor type data  1652 , according to the following formulae: 
       operator&#39;s responsiveness 1658=average of processing durations 1622 of 
       step 320 for this operator/average of the processing durations 1623 of step 
       320 for all operators 
       contractor&#39;s responsiveness 1658=average of processing durations 1622 
       of step 330 for this contractor/average of the processing durations 1623 of 
       steps 330, 331 and 332 for all contractors. 
     Management module  161  further updates the average responsivenesses  17216 - 17226 - 17296  by contractor and operator type. 
     7) Damage Claim Handling Method 
       FIG. 7  illustrates a method  400  for handing a damage claim made to insurance company. 
     At step  410 , an agent of operator is provided with a terminal  111  such as a PC. By means of a user interface  1114  and a validation button thereof  1428 , a diagnostic report  1426 , which is pre-stored in server  140 , is declared to the insurance company of operator. Management module  151  copies and pastes this report into register  1521 , the estimated damages  1432  into register  15221  and the liability level  1431  into register  15231 . Actuating validation button  1428  causes the transmission of an email notifying this declaration  1426  to a predefined terminal  114  such as a PC of insurance company. 
     At step  420 , an insurance company agent, by means of said terminal  114 , uses interface  1144  of said terminal to access the diagnostic report  1521 , the estimated damages  15221  and the liabilities  15231 . By actuating validation button  1527 , insurance company agent validates the diagnostic, which causes the copying and pasting of the content of register  15221  into the insurance company&#39;s register  15222  of estimated damages and the content of register  15231  into the insurance company&#39;s register  15232  of estimated liabilities. The insurance company&#39;s agent can alternatively input different values into registers  15222  and  15232  before actuating validation button  1527 . This validation causes the transmission of an email notifying this action  15232  to contractor(s). 
     Step  421  is triggered in case of unsolved disagreement between the parties, giving rise to a dispute. At the end of this step, an agent of the operator, equipped with a terminal  111 , inputs the figures from the court decision into the registers  15223  and  15233  of the damages estimate an liabilities, and validates the inputs by actuating button  1528 . This validation causes the transmission of an email notifying this action  15233  to insurance company and to contractor(s). 
     At step  430 , contractor validates the estimations  15222 ,  15232  by insurance company or the amounts  15223 ,  15233  decided by court, by actuating validation button  1524 . This validation causes the transmission of an email notifying this action to the other stakeholders. This transmission is time-stamped and also notified to management module  161  of server  160 , which copies and pastes the estimated or decided damages  1432  into register  1653  corresponding to the considered contractor, and its liability level  1431  into register  1654 . 
     Steps  431  and  432  are triggered if the liability registers  15232 ,  15233  splits the liability between two or more contractors. In such case, the other allegedly liable contractors are invited to validate the estimated damages and liabilities by actuating the respective validation buttons  1525  and  1526 . 
     At steps  410  to  432 , management module  161  stores into time-stamping register  162  the duration of each step of method  400 . 
     At step  440 , insurance company initiates a bank transfer with amount  1697  for covering damages. Management module  161  establishes the responsivenesses  1658 - 1698  of the different stakeholders according to the method described at step  340 , as well as:
         the gap  1691  between the damages estimated by the operator and by the insurance expert by computing the difference between values in registers  15222  and  15221  of the damage claim database  152     the gap  1692  between the damages estimated by the insurance expert and by the court expert by computing the difference between values in registers  15223  and  15333  of the damage claim database  152     the gap  1693  between the liabilities estimated by the operator and by the insurance expert by computing the difference between values in registers  15232  and  15231  of the damage claim database  152     the gap  1694  between the liabilities estimated by the insurance expert and by the court expert by computing the difference between values in registers  15233  and  15232  of the damage claim database  152     the reserve ratio  1695  by computing the quotient of the paid amount  1697  by the amount  15221  of damages estimated by the operator   the dispute ratio  1696  by computing the quotient of the number of triggered steps  421  by the number of methods  400  run, as stored in historical data.       

     8) Rating Method 
       FIG. 8  illustrates a method  500  for rating stakeholders. 
     At step  510 , method  500  is waiting for the activation of one of the three methods  200 ,  300  or  400 . 
     At step  520 , management module  161  computes the performance indicators  1655 ,  1656  of the contractors as detailed in the description of method  200 . 
     At step  530 , management module  161  computes the insurance indicators  1657 ,  1658  of the contractors as detailed in the description of method  300 . 
     At step  540 , management module  161  computes responsiveness indicators  1658 - 1698  for contractors and insurance companies, as well as other indicators concerning the insurance companies, as detailed in the description of method  400 . 
     At step  550 , management module  161  updates the database  173  of liability statistics by damage type. For this purpose, module  161  looks up in the damage list  171  the reference ( 1713411  in the present species, for a gutter damage) that corresponds to the incident or damage type  1423 . Module  161  then opens the record  1731  corresponding to reference  1713411  and updates the different fields  17311  et seq. as a function of the contractor type  1652  and the following formulae: 
       total damages(post) 17311=total damages(pre) 17311+estimated 
       damage 1653 
       maintenance liability(post) 17312=((maintenance liability(pre) 17312×
 
       total damages(pre) 17311)+(maintenance liability 1654×damages 1653))/total
 
       damages(pre) 17311+damages 1653)         the liability values  17313 - 17316  for the other contractors are computed using the same formula.       
     At the same step  550 , management module  161  updates the database  172  of liability statistics by contractor type, e.g. the maintenance contractor type  1721 , using the following formulae: 
       number of damages(post) 17211=number of damages(pre)+1 
       average amount of damages(post) 17212=average amount of damages 
       (pre)×number of damages(pre)+maintenance liability 1654×damages
 
       1653/number of damages(post) 17211         average percentage  17213  of liabilities for all damage types=mean value of (R17312; R17322; R17332; . . . )   average performance ratio  17214 =mean value of the average performance ratios  16562  of all maintenance companies   average compliance rate  17215 =mean value of the compliance rates  1656  of all maintenance companies.       
     At same step  550 , management module  161  opens record  1741  of insurance statistics database  174  that corresponds to the above-mentioned particular reference  1713411  (gutter disorder). Management module  161  computes the statistical values and updates the different fields  17411  et seq. by establishing the mean values between all items  1691  et seq. corresponding to this same reference  1713411 , as follows:
         average gap  17411  between the damages estimated by operator and by insurance expert=mean value of the equivalent gaps  1691  among all insurance companies   average gap  17412  between the damages estimated by insurance expert and by court expert=mean value of the equivalent gaps  1692  among all insurance companies   average gap  17413  between the liabilities estimated by operator and by insurance expert=mean value of the equivalent gaps  1693  among all insurance companies   average gap  17414  between the liabilities estimated by insurance expert and by court expert=mean value of the equivalent gaps  1694  among all insurance companies   average reserve ratio  17415 =mean value of the equivalent ratios  1695  among all insurance companies   average dispute rate  17416 =mean value of the dispute rates  1696  among all insurance companies   average payment amount  17417 =mean value of the equivalent amounts  1697  among all insurance companies   average responsiveness  17418 =mean value of the equivalent responsivenesses  1698  among all insurance companies.       

     At step  560 , management module  161  updates the ratings  1659 - 1699  of the different stakeholders by applying the following formulae:
         insurance company rating  16991  for damage type  1713411 =mean value of the set of following ratios:
           average gap  17411  between damages estimated by the operator and by the insurance expert/gap  1691  between damages estimated by the operator and by the insurance expert   gap  1692  between damages estimated by the insurance expert and by the court expert/average gap  17412  between damages estimated by the insurance expert and by the court expert   average gap  17413  between damages estimated by the insurance expert and by the court expert/gap  1693  between damages estimated by the insurance expert and by the court expert   gap  1694  between damages estimated by the insurance expert and by the court expert/average gap  17414  between damages estimated by the insurance expert and by the court expert   reserve ratio  1695 /average reserve ratio  17415     average dispute ratio  17416 /dispute ratio  1696     payment amount  1697 /average payment amount  17417     responsiveness  1698 /average responsiveness  17418     
           rating  1699  of insurance company on all damage types=mean value of all ratings (rating  16991  on damage type  1713411 , rating  16991  on a second damage type; rating  16993  on a third damage type; . . . )   contractor rating  1659 =mean value of all the following ratios:
           average damages amount  17212  for the considered contractor type/average contractor damages level  16571     average liability level  17213  for the considered contractor type/average contractor liability  16572     performance ratio  16552 /average performance ratio  17214  for the considered contractor type   compliance ratio  1656 /average compliance ratio  17215     responsiveness  1658 /average responsiveness  17216  for the considered contractor type.   
               

     Variations of the Present Invention 
     a) Ratings  1659 - 1699  can be computed with different mathematical formulae and can use additional or different indicators. For instance, contractor rating  1659  can be a function of the average damages amount  16571 , of the average liability  15572 , of the responsiveness rating  1658 , or the schedule compliance  1656 , of an evolution of the risks, of a frequency of delays over contractual deadlines, of an insurance damage claim declaration rate, of an average number of amendments to declarations, of a frequency of damage claims per surface area unit of the property, etc. 
     Similarly:
         insurance rating  1699  can be a function of payment, risk, responsiveness, coverage, fidelity, permanence,   payment rating can be a function of amount, payment schedule, late payment penalties,   risk rating can be a function of contractor rating, use, property type, Risque=f(note locateur, usage, type de lieu)   responsiveness rating can be a function of administrative reaction time, average,   coverage rating can be a function of damages amount, amount covered, average,   fidelity rating can be a function of the number of insurance claims and contract renewal data,   permanence rating can be a function of first estimate of the amount to be covered and final covered amount,   use can be one among office use, health service use, housing, hotel, etc.   location type can be one among mountain area, seaside area, floodable area, etc.       

     b) Ratings  1659 - 1699  can be detailed component by component (average damages amount, average liability, responsiveness, etc.), segment by segment (contractor type, geographical area, etc.) or detail level by detail level (property program, damage type, expert, etc.). 
     c) Management module  161  can establish rankings of insurance companies, of contractors, of operating companies in decreasing order of their ratings, according to the various categories  1652 ,  1711 ,  1712 ,  1713 . 
     d) In building maintenance applications, the visit locations  1323  can be materialized by QR-Codes affixed to technical cabinets and other equipment, by NFC tags capable of communicating with smartphones, by pictures of disorder and their curing (e.g. an obstructed and de-obstructed siphon), and appropriate image recognition programs for identifying said disorders and their curing. 
     e) The generation of an incident record  142  at step  310  can be performed automatically in response to detection by a connected equipment (monitoring camera, intrusion sensor, etc.) 
     f) The proof data  1425  of disorders and their evolution can be generated from a series of pictures of a same location (e.g. propagation of a crack or development of rust over a long period of time), or by interpreting alerts from connected equipment (e.g. frequent boiler failure, unusual temperature variations, etc.). 
     g) The present invention can be applied to other fields than building construction and maintenance, and in particular:
         insurance in construction and maintenance of transportation equipment,   liability insurance in company operation (hidden defects, compliance to standards, personnel safety, pollution, etc.).