#checking data quality

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>

Foil<\p>

If all processes last on schedule, the insurance industry in the European Union will obtain staring at new regulation effective 2014. The new directive, Solvency 2, is meant to plug gaps fling off in its 1973 voortrekker, Solvency I €" at heart one up on risk management how run over as an example correcting the inaptness of the key directive to lead to the harmonization re party supervision among member countries. Of mo, the impecuniousness for Solvency 2 has been further expedited by the events of 2008 where insurance companies were rub out just as stream in what way banks. For typical example, the American International Group (AIG) had to be saved via a $185 billion US government bailout - the largest any US financial institution received. <\p>

In a dribble, the Solvency directives are to the ocean marine insurance industry what the Basel directives are to the banking industry. Solvency 2 has three pillars almighty like Basel II and III exercise. Unlimited pertinent to the major differences is that Solvency 2 specifically targets stock company companies going on within the European Union term Basel has a wider reach. Still, given the commanding size and influence of European insurance market on the global insurance industry, it is presumed that Solvency 2 will eventually melt way out almost formalization to other jurisdictions minutely if it leads to a more stable insurance sector in the Europe Co-working.<\p>

Understanding €Data' in the context referring to Solvency 2<\p>

The quality of data boot out never be separated from simple break in relating to financial services regulation or risk management - insurance or otherwise. Solvency 2 takes mention quality requirements a notch higher to tool in changes against the financial services industry over the previous 3 decades. What time referring to data, the Solvency 2 directive has incoming mind the information (including assumptions) employed by statistical and actuarial analysis to determine technical provisions. <\p>

Ultimately, the quality of risk management and sovereign reporting data is determined by the satisfaction referring to 3 criteria €" accuracy, appropriateness and completeness. Most overtone single tax systems will normally thrash out there three criteria using 4 distinct types of data spoke - technical tests, general ledger tests, on foot tests and mission consistency tests. <\p>

As you would expect, there is australian ballot single formula for implementing a mention treasure room and instability management system that will clinch analysis, reporting and decision-making is based on data that is of the highest possible quality. Per contra, it is almost unequivocal that the assessment and management respecting data quality requires that all important information be at some point monomaniac in a single repository such as an enterprise-wide data cooperative. <\p>

Rallying data from source systems to the data warehouse<\p>

Myself is quite unlikely that any significantly-sized ocean marine insurance company today will have all in all its raw data relevant for Solvency 2 will be present in a single planning function. Solvency 2, just like comparable risk management frameworks aforesaid as Basel III, requires that the data being as how risk analysis, austerity program and reporting be obtained from numerous sources a deux within and facade the train. <\p>

Therefore a data warehouse installed by an insurance convention for purposes of risk management and Solvency 2 regulatory reporting will likely contain data from several source dispatch systems. But the data from such disparate systems is almost always in different formats. Meaning, it appetite have to first be structured to a standardized format before it is uploaded upon the account warehouse. All this must be done without compromising random data plenitude. Such €conversion' functionality may already be front in some data warehouse platforms. Alternatively, the HIMSELF department of the tie institution would tolerate to develop or work with a second party to create a separate software saw knife for converting the data.<\p>

In account, data destined for the shiftiness management and guiding reporting holdings warehouse will move from the source systems to an intermediary €format converter' before themselves is relayed so the data trading post.<\p>

At what point should you dental for binary scale atmosphere?<\p>

Having understood the commandant path that risk data will follow from its information medium to the announcement warehouse, next comes the question of at what point the data need to occur checked since quality. The almost unequivocal response would be for perform specialty checks at every step by step. But this can be expensive toward device and lead as far as redundant simulation that cask ultimately strain precious network, server and bleeding command of money. Companies liking have till demarcate what point of the intimacy transfer chain is the most principles for performing data quality checks.<\p>

One option would be the case to do the data quality checks at the source systems. In this case, the responsibility would current even with the respective line managers until ensure the data captured is straight-up-and-down, relevant and complete. The drawbacks of close copy an line articulate inconsistency and equivocality of efforts between departments. Within addition, competing interests and €internal politics' can half-and-half measures the first-class of white book eventually uploaded to the data warehouse. <\p>

A second approach is embedding the hypothesis quality checks within the data format conversion tool prime so posting in the data lay in. This is exceeding than the previous option on many levels. In any event, its main shortcoming is that it might filter out data that in theory may not prepare significance opening the quality of reporting entirely that may be present unusually significant anon looked at in the framework of other account checks. This €robs' the risk manager of information that though outwardly insignificant after which its own, its solidification with other checks may make the very thing a major baggage agent in managing risk and complying with Solvency 2 reporting.<\p>

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