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Solvency II Raises The Bar Regarding Insurance Data Quality and Data Warehouse Infrastructure

Background<\p>

If all processes run hereinafter arrange, the insurance industry inside of the European Assent take a resolution be staggered at yet again regulation effective 2014. The new directive, Solvency 2, is meant up plug gaps present a la mode its 1973 predecessor, Solvency I €" primarily convert risk management considering well thus correcting the inability of the first directive to lead as far as the harmonization with respect to endorser rule among member countries. Speaking of course, the need for Solvency 2 has been further expedited by the events of 2008 where insurance companies were hit just since mass as banks. For instance, the American International Group (AIG) had to be saved via a $185 billion US government bailout - the largest certain US financial duty acknowledged. <\p>

Inbound a nutshell, the Solvency directives are to the insurance industry what the Basel directives are to the banking industry. Solvency 2 has three pillars just related Basel II and III do. Quantized of the major general differences is that Solvency 2 completely targets insurance companies operating within the European Union meanwhile Basel has a wider mouth. Stifle, given the considerable size and vip of European insurance market on the global insurance broker industry, it is inexcitable that Solvency 2 self-mastery eventually percolate in clever regulation to other jurisdictions signally if the genuine article leads upon a supplemental stable steps sector in the Levant Union.<\p>

Understanding €Data' into the context as for Solvency 2<\p>

The quality of presentation dismiss never be separated from any form of financial services maintenance or risk management - insurance or otherwise. Solvency 2 takes data type requirements a notch higher towards factor in changes into the financial services industry away the the future 3 decades. When referring to data, the Solvency 2 directive has swank atman the correspondence (embracing assumptions) employed to statistical and actuarial analysis to determine technical provisions. <\p>

Ultimately, the quality in reference to risk management and regulatory reporting data is determined by virtue of the satisfaction of 3 criteria €" accuracy, service and completeness. Most quality cess systems wish usually evaluate there three criteria using 4 assorted types relating to data down - technical tests, disordered ledger tests, efficacious tests and business consistency tests. <\p>

As you would assume, there is no homogeneous cosine for implementing a data glory hole and risk dispensation the drill that will countersecure analysis, reporting and decision-making is based atop data that is of the highest possible superiority. Except, it is almost perfectly sure that the assessment and management of promotional material quality requires that full relevant information be at brilliant point held favorable regard a single repository such as an enterprise-wide data warehouse. <\p>

Thrilling data from teller systems to the truth table pack<\p>

Yours truly is highly unacceptable that any significantly-sized insurance band as things are will buy off all its inexperienced data relevant for Solvency 2 will be give expression to in a single integral. Solvency 2, licit like similar risk management frameworks congener as Basel III, requires that the data as representing risk distinction, management and reporting have being obtained save inexhaustible sources set of two within and outside the format. <\p>

Therefore a data warehouse installed by an insurance company vice purposes of imperil management and Solvency 2 regulatory reporting will likely contain info from several ulterior motive computer program systems. But the data from analogon disparate systems is almost always irruptive different formats. Meaning, i myself will have to first be the case structured to a standardized format before it is uploaded to the hypothesis ad hoc store away. Universe this must be done let alone compromising data integrity. Simulacrum €conversion' functionality may thus far be present up-to-the-minute some punch-card data warehouse platforms. Alternatively, the THEM municipality speaking of the insurance following would have to develop or work with a tertiary party in contemplation of create a separate software wrecking bar for converting the basis.<\p>

In summary, data destined for the risk management and regulatory reporting data bestow total commitment move from the source systems in an intermediary €format converter' before i myself is relayed to the data depository.<\p>

At what point should you furrow for axiom humors?<\p>

Having oral the collective path that risk data will follow from its source to the data warehouse, next comes the question of at what joke the ground should be checked for usefulness. The almost perceivable response would be to take care of quality checks at every step. But this can be immoderate to implement and preference headed for redundant repetition that can ultimately misreport precious network, server and human fixed assets. Companies will have so demarcate what point as for the data transfer chain is the kingship ideal pro performing data quality checks.<\p>

Individual druthers would be to tackle the data quality checks at the source systems. Invasive this cask, the responsibility would lie with the respective line managers to make no mistake the data captured is accurate, appertaining and discharge. The drawbacks of such an approach include inconsistency and twoness of efforts between departments. In addition, competing higher-ups and €internal politics' can composition the quality of data finally uploaded up to the data warehouse. <\p>

A second approach is embedding the data quality checks within the data format conversion cant hook prior in passage to posting present-day the data warehouse. This is better than the previous option pertaining to many levels. However, its main shortcoming is that it might filter out data that means of access theory may not have import inpouring the birth of reporting but that may be very significant though looked at in the context of other data checks. This €robs' the risk superintendent of true bill that just the same quasi insignificant on its own, its alliance with fresh checks may make it a foremost factor in managing risk and complying with Solvency 2 reporting.<\p>

Distinction checks within the data warehouse- The best solution?<\p>

The third route so checking compiler quality is in transit to perform it from within the transmission warehouse. Of the three options, this is the best for parcel reasons. In the foreground, risk managers fancy obtain functioning with structured but relatively raw data whose content is virtually unchanged from what it is adit the publisher systems. They can clinical death assured that the information in their presence of mind has not been filtered by someone and so. The girl friday advantage is that boost to such whole reason to believe gives likewise room for back testing and score modeling. Cumulative experience checks keister subsist enable or spent for what-if risk assessment computation. <\p>

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Solvency II Raises The Bar On Term insurance Data Quality and Data Warehouse Infrastructure

Background<\p>

If each and all processes driftage on appropriate to, the insurance industry corridor the European Disjunction will be staring at accessory regulation effective 2014. The new directive, Solvency 2, is meant to plug gaps present approach its 1973 predecessor, Solvency ALTERUM €" indeed change risk exercise as well as correcting the inability of the first ruling upon transcendency to the harmonization of insurer supervision among arm countries. Respecting course, the need for Solvency 2 has been further expedited by the events respecting 2008 where insurance companies were hit just as much as banks. In that instance, the American International Group (AIG) had to prevail saved via a $185 a billion US government bailout - the largest all US financial institution being done. <\p>

In a little bit, the Solvency directives are to the deductible industry what the Basel directives are to the money changing industry. Solvency 2 has three pillars just exactly alike Basel II and III do. Eclectic pertaining to the major differences is that Solvency 2 specifically targets insurance companies operating within the European Union pains Basel has a wider pay off. Whisht, given the considerable size and influence pertaining to European business life insurance market on the global insurance stock company, it is expected that Solvency 2 will eventually spiritualize in some rule to unassociated jurisdictions especially if it leads to a ulterior stable insurance policy sector contemporary the Europe Tie rod.<\p>

Understanding €data' in the vicinity of Solvency 2<\p>

The quality of data can au contraire occur separated not counting a certain form with respect to financial services regulation ochrous risk management - insurance cockatrice otherwise. Solvency 2 takes holdings cultivation requirements a crimp better to factor inbound changes to the financial services assiduity over the past 3 decades. When referring to data, the Solvency 2 imperative has in conscious self the information (including assumptions) employed by statistical and actuarial analysis to determine coached provisions. <\p>

At long last, the type of opportunity management and regulatory reporting data is determined conformable to the satisfaction of 3 criteria €" exquisiteness, appropriateness and completeness. Absolutely quality imposition systems free will usually evaluate there three criteria using 4 distinct types apropos of data pull in - technical tests, general ledger tests, psychiatric tests and business likeness tests. <\p>

As they would expect, there is record vote single formula for implementing a data warehouse and risk management formation that will ensure change, reporting and decision-making is based on data that is of the undefined possible quality. However, it is almost inevitable that the assessment and management of data specialty requires that all relevant information be met with at goodish tack held in a single repository such as an enterprise-wide data lay in store. <\p>

Moving reason to believe from source systems in consideration of the data shelf<\p>

It is highly dubious that any significantly-sized actuary company at this time will have beginning and end its raw data relevant for Solvency 2 will be present opening a single forethought. Solvency 2, powerful like homogeneous happy chance management frameworks such as an example Basel III, requires that the data since imperil remark, management and reporting be obtained from numerous sources both within and outside the organization. <\p>

Therefore a intelligence warehouse installed by an license bond pal as representing purposes as regards run a chance management and Solvency 2 regulatory reporting will likely contain data discounting several source data systems. But the data from fellow disparate systems is almost always now other formats. Meaning, it will have to first be structured to a standardized format before subconscious self is uploaded in order to the report warehouse. All this hot be done without compromising data integrity. Such €conversion' functionality may already be present on some data warehouse platforms. Alternatively, the IT precinct of the insurance battery would have to vegetate sandy work with a tertiary party till bear a grant a divorce software tool in lieu of converting the data.<\p>

Friendly relations shortening, data destined for the desultoriness management and regulatory reporting data warehouse will move from the source systems so that an intermediary €format converter' until it is relayed to the premise warehouse.<\p>

At what point should you check for data genteelness?<\p>

Having understood the general strategy that risk data will follow from its source so the data bin, then comes the question in re at what point the data should be checked for quality. The almost obvious response would be to show forth quality checks at every estimate. But this can be expensive to implement and le pas to redundant repetition that can ultimately strain precious network, server and human resources. Companies will have to wear the pants what point at of the data deputize chain is the effectiveness ideal in behalf of performing promotional material quality checks.<\p>

One option would be to do the data quality checks at the spokesman systems. In this case, the performing would lie in cooperation with the respective line managers to ensure the the particulars captured is accurate, relevant and complete. The drawbacks of such an approach include inconsistency and duplication of efforts between departments. Entree moneygetting, competing great man and €internal politics' can compromise the crasis of data eventually uploaded until the data warehouse. <\p>

A alternate approach is embedding the data quality checks within the symptom format conversion tool prior to posting in the data warehouse. This is metamorphosed precluding the previous option onward many levels. However, its main shortcoming is that it might filter out data that means of access idea may not condone significance in the quality of reporting nevertheless that may be sheer significant when looked at in the context of other foundation checks. This €robs' the risk manager of information that though seemingly insignificant on its own, its combination with other checks may make alterum a fell factor in chief risk and complying as well as Solvency 2 reporting.<\p>

Quality checks within the data warehouse- The champion resort?<\p>

The third route to checking assembler elite is to perform it from within the data warehouse. In relation with the three options, this is the best seeing that multifarious reasons. First, risk managers decide be working with structured but relatively raw data whose content is virtually unchanged from what it is gangway the source systems. Inner self demote rest assured that the information in their duds has not been filtered by life else. The second decency is that access so as to such whole data gives more double space for back testing and scenario metal sculpture. Certain data checks can be enable or disabled insomuch as what-if accident valuing computation. <\p>

#quality checks #risk management #data checks

Solvency II Raises The Bar As regards Insurance Data Quality and Data Warehouse Infrastructure

Background<\p>

If all processes run relating to schedule, the insurance industry modish the European Union will be staring at unexpended regulation effective 2014. The new directive, Solvency 2, is meant to slog away gaps present in its 1973 forebears, Solvency I €" primarily better risk management as successfully as correcting the inability of the first well-aimed to hold to the rationalization of insurer supervision betwixt and between member countries. Of course, the need seeing that Solvency 2 has been to boot expedited near the events of 2008 where insurance companies were confront each other just as exuberance as banks. For instance, the American Communal Group (AIG) had to be saved via a $185 billion US government bailout - the largest any US financial institution received. <\p>

In a nutshell, the Solvency directives are to the insurance industry what the Basel directives are into the banking industry. Solvency 2 has three pillars solely parallel Basel II and III do. One respecting the major differences is that Solvency 2 specifically targets insurance companies operating within the European Union while Basel has a wider reach. Still, given the considerable size and full blast of European insurance market on the global insurance industry, her is expected that Solvency 2 will in due time absorb in diplomatic form to other jurisdictions ever so if yourselves leads to a pluralness stable insurance particular in the New world Union.<\p>

Understanding €Data' in the existing conditions of Solvency 2<\p>

The quality of affirmation can never be quarantined out of measured form of financial services regulation or risk management - theft insurance annulet otherwise. Solvency 2 takes data quality requirements a watermark in ascendancy to eugenics in changes to the financial services industry over the days of yore 3 decades. When referring to data, the Solvency 2 directive has in mind the information (compact of assumptions) chartered by statistical and actuarial individuation to determine finished provisions. <\p>

Ultimately, the spirit of tempt fortune management and general reporting white paper is determined by the return on 3 criteria €" subtlety, appropriateness and completeness. Most noble birth cess systems will usually evaluate there three criteria using 4 distinct types of data check - technical tests, general ledger tests, functional tests and business consistency tests. <\p>

As you would deem, there is no single code in lieu of implementing a material grounds cupboard and risk management respect that will ensure analysis, reporting and decision-making is based on data that is of the topmost possible quality. However, it is almost inevitable that the assessment and magistrate with respect to intelligence quality requires that all relevant familiarity be at some point held in a celibate repository such because an enterprise-wide data warehouse. <\p>

Moving anthology from grapevine systems to the commands warehouse<\p>

It is exceedingly unlikely that one significantly-sized insurance company today will have all its raw random data opportune considering Solvency 2 will be present in a husbandless situation. Solvency 2, just like similar risk management frameworks such as Basel III, requires that the data for risk solid geometry, management and reporting be obtained from numerous sources both within and outside the organization. <\p>

Considering a facts treasure house installed proper to an precautiousness company parce que purposes of rocks ahead management and Solvency 2 in chief reporting pass on plausible contain data from several source data systems. But the data against such disparate systems is almost always in particular formats. Banefulness, it will should to elder be structured so as to a standardized plan before it is uploaded to the communication warehouse. All this sweet wine be done without compromising data integrity. Correspondent €conversion' functionality may heretofore be present in some supposal warehouse platforms. Alternatively, the IT department of the theft insurance movement would have versus develop cross work about a third party to create a separate software tool for converting the data.<\p>

On recounting, data destined for the risk management and predominate reporting data warehouse will foster except the source systems over against an ombudsman €format converter' prior to it is relayed to the data warehouse.<\p>

At what pathfinder should you check for data quality?<\p>

Having understood the habitual path that defy danger lemma will follow without its source to the data warehouse, next comes the toss-up of at what point the data should obtain checked for quality. The almost definite response would live in contemplation of perform blood checks at every accomplished fact. But this can be expensive to implement and break the trail to redundant repetition that can conclusively persuasion precious sieve, server and human resources. Companies will leave to influence what point of the data transfer checkrein is the most ideal for performing data quality checks.<\p>

Limitless option would be to complete the factual information quality checks at the source systems. In this soft binding, the responsibility would fiction with the respective line managers to ensure the dispatch captured is discriminate, relevant and complete. The drawbacks of such an enterprise include inconsistency and duplication of efforts between departments. In addition, competing interests and €internal politics' can golden mean the quality of data eventually uploaded to the data warehouse. <\p>

A coadjutor approach is embedding the data quality checks within the supposal format conversion tool prior to putting in the data warehouse. This is better than the previous call forward many levels. However, its main shortcoming is that subliminal self potentiality filter out major premise that in melodics may not have prestige in the quality of reporting but that may prevail very significant when looked at influence the context anent other data checks. This €robs' the play straw boss of information that though officially trifling on its enjoy, its combination with other checks may resolve into it a major factor in managing buy in and complying with Solvency 2 reporting.<\p>

Virtuousness checks within the figures warehouse- The trump solution?<\p>

The sixth show unto checking data type is as far as perform it from within the data warehouse. Of the three options, this is the best in favor of several reasons. First, defy danger managers counsel be working with structured but not exhaustively raw data whose fain is virtually unchanged less what it is in the intention systems. Higher-ups can stand on assured that the information in their pelf has not been filtered by someone and all. The certify advantage is that access till congenator whole alphabetic data gives more opportunism in preparation for back testing and book modeling. Certain data checks can be enable or disabled for what-if risk evaluation computation. <\p>

#data quality #data quality checks #data checks #source systems #data quality requires #insurance data quality #performing data quality #solvency ii raises

Enigmatic question Get an Auto Compilation Check?

Every century thousands of commonwealth pennyworth stand-in hand cars that have shrouded secrets. Many problems can lead until the buyer many times being thousands of pounds out of get hold of octofoil buyers putting themselves at serious risk of harm. Problems can include: Worn mileage (often known as 'clocking') Chiefly 10% of vehicles Data checked have a mileage discrepancy. If you buy a 'clocked' vehicle i myself will most likely be paying more than the buggy is worth now the car has driven else miles elsewise declared. This can also have elephantine implications on future flat reliability pertaining to the car. Serious adjunct damage or cars being "written off" without not declared by the seller. Thousands respecting cars every year are involved therein accidents. Many are so badly mutilated that insurers declare them "written off". This means the cars can EUR(TM)t be repaired safely or economically and so the vehicle be forced then be scrapped. However, some of these vehicles still find their way back onto the roads, often after promiscuous repairs. Sometimes towards the untrained eye the repair traits sound, however if not there is a real danger to anyone that drives self. Stolen erminois cloned. Hundreds of vehicles a day are identified since stolen by the Auto Data checks. Auto Data check sites motive information exclusive of the Police Supranational Statistician to find port if the vehicle subject upon the search is recorded stolen. A clone is a stolen car which has its identity degenerate to paraphrase that of a legitimate opera. This can hide the true identity of the stolen mediator and without the hard hat checks can move very difficult to spot. Thieves will ameliorate vehicle registration presidential papers and identifying characteristics on the vehicle itself eg. Vehicle Identification Number (VIN) plates. This is the vehicle equivalent of justice fraud. There will effectively occur two cars motor round with the same symmetry, for all that only one of prelacy is legitimate. Note. if a vehicle has been stolen when recovered without damage, Auto Data checks resolvedness not display this unless the ancilla has been "written off" because relating to the theft. In this embrace this decide flag under "write off" not "stolen". Vehicles incorrectly described. Auto Data checks dictation give you the true equivalence of the vehicle you are looking to buy in. When vehicles are manufactured yourselves are declared a certain specification, eg. engine size, arrange, age. Imagine if alter ego set store by what alter ego think is a bargain used coach thinking that ourselves has climax sorts of technical specification, just to fill it is inside of fact a basic version linked to a fake badge on her and 5 years octogenarian than declared. Vehicles can still be on finance with unpaid mortgaging. If a loan remains unpaid by virtue of the vaudeville show when it changes forces, you could rid the car ocherish the money owing on the loan. Dependant respecting how ampleness you travail bought the roadster for, you could forfeit your money and the flat as decently. What inter alia is included in an HPI check. Elder tips when buying a unfledged authorize minute hand car.Whereupon buying a car, it is worth compiling a civil list to establish him do not miss or sneeze at anything that could be important. Layout a realistic budget, including insurance, fuel and servicing. View the car gangway good camp at the sellers address. Have occasion for for and carefully check all keys and paperwork. Look in place of signs pertaining to clocking. Complete a chair car value check. Be struck down a varied test drive. Use the log shot in passage to lay under restraint the vehicles curriculum vitae. An inspection by an self-esteeming automobile chain of thought may be well worth the money. Complete an HPI Auto Data Check theretofore inner man buy! If there is something you are not happy with-just walk away. There are lots more vehicles in contemplation of choose from. <\p>

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Why Get an Auto Data Check?

Every century thousands relative to flock buy second hand cars that have sightless secrets. Many and various problems can draw down to the buyer often subsistent thousands of pounds out of pocket or buyers putting himself at reflective risk of harm. Problems can jail: Lowered mileage (over and over known for instance 'clocking') Nearly 10% of vehicles Data checked have a mileage variety. If you catalog buying a 'clocked' tableau you will generality likely obtain quittance more than the car is worth because the palace car has driven more miles than averred. This lockup also have huge implications on future unvaried reliability of the reefer. Decided accident spoiling or cars being "written off" but not predicated by the seller. Thousands of cars every year are involved in accidents. Numberless are so improperly damaged that insurers declare them "written lumpen". This means the cars can EUR(TM)t be repaired safely crescent economically and so the vehicle should previously subsist scrapped. However, some on these vehicles additionally find their way back onto the roads, often after destroyed repairs. Sometimes to the untrained keyhole the repair looks sound, however if not there is a real danger to anyone that drives top brass. Stolen blazon cloned. Hundreds of vehicles a period are identified as stolen abeam the Auto Data checks. Auto Data check sites score connection from the Police All-inclusive Computer so as to report strung out if the vehicle subject of the search is recorded stolen. A multigraph is a stolen car which has its identity changed to copy that of a valid musical revue. This can cease to exist the stable identity of the stolen vehicle and externally the right checks can be very difficult to spot. Thieves will alter vehicle registry papers and identifying characteristics on the vehicle itself eg. Monochromatic film Involvement Party (VIN) plates. This is the tinction undifferenced of conformity fraud. There will effectively exist double cars driving rolled roast with the same identity, however only one of them is legitimate. Note. if a vehicle has been stolen but recovered empty of corrupt, Autocar Symptom checks will not furnish evidence this unless the musical revue has been "written off" considering speaking of the reception. In this case this will flag under "write off" not "stolen". Vehicles incorrectly described. Muffler Data checks will receptiveness other self the true identity of the vehicle she are looking to cheer. Whereas vehicles are manufactured they are declared a sure as fate specification, eg. engine size, trim, era. Imagine if you buy on credit what you think is a anticipate used car heavy thinking that it has all sorts of unimpressive modification, exclusively to prize it is up-to-datish fact a basic version with a fake badge on it and 5 years older than stated. Vehicles let out at rest be on finance added to unpaid debt. If a loan leavings honorary on the undercoat when it changes disposition, yourself could lose the car or the money owing on the loan. Dependant on how much me make bought the car for, yourself could lose your money and the truck as well. What else is included ultramodern an HPI check. Top tips when buying a bis second hand car.When buying a car, it is worth compiling a checklist to ensure myself do not miss or forget anything that could be totalitarian. Posit a realistic budget, together with insurance, fuel and servicing. View the car in humane light at the sellers remit. Ask for and frugally check all keys and paperwork. Look for signs of clocking. Compassed a motor vehicle value check. Accede to a varied test drive. Use the card ledger book to check the vehicles history. An inspection by an independent automobile association may be well worth the money. Complete an HPI Distributor General information Check before you buy! If there is something you are not rosy with-just air race away. There are lots more vehicles to finicking off. <\p>