Posts Tagged ‘Cloud Computing’

« Older Entries

Investments – Moving Beyond IT and the Clouds

Tuesday, March 22nd, 2011

This article also appears at the National MBA at: http://www.mortgagebankers.org/tools/FullStory.aspx?ArticleId=21253

By Mark P. Dangelo

Innovative Relevance®

There is a quiet rebirth taking place across the banking and lending sectors using mass market innovations to reach out to and maintain relationships with the “best” homeowners.  Spurred on by a perceived bottoming of real estate prices, supply, and foreclosures, executive suites are once again marshalling their resources to tackle rapidly shifting obligation – and opportunities – using technology. 

However, in conforming to historical benchmarks, well over 80% of every new initiative will fail to deliver against three or more anticipated results and published benefit projections (i.e., key performance indicators, KPI’s).  Over 60% will be late.  More than 50% will exceed budgets by more than 35%.  Making matters worse, 45% to 60% of new initiatives will fail to gain consumer or homeowner acceptance, and 60% to 75% will experience service outages and disruptions lasting more than two hours – repeatedly. 

Complexity of Measuring Across the Opaque and Unfamiliar

Across the real estate markets, millions in capitalized investments will be written off in 2011 as the cycle-time for technology success becomes shorter and more problematic for delivery teams used to measuring benefits in years — NPV (net present value), IRR (internal rate of return), market share– not in months (i.e., < one year product life-cycle).  Nevertheless, to reach changing real estate browsing, buying, and borrowing habits of consumers, new investments must be made using unfamiliar technology to ensure adherence to cross-industry processes and burdensome regulatory compliance. 

With a fundamental shift rapidly occurring in computing infrastructures – tablet and smart device versus traditional PC’s – the parameters of software delivery and hardware provisioning have already been permanently altered.  Factoring in a number of new touch points – third-party data sources, untrusted  Wi-Fi and 3G connectivity options, analytical analysis, external application support – and the familiar cost of ownership projections can double in under half of the time (i.e., utilizing traditional projections of three years). 

Real estate innovation has a price especially during times of industry transformation.  As identified in 2004, the fifth stage of an industrial revolution is in full force with disposable technology and rapid changes in personal wealth underpinned by global struggles for economic supremacy. 

As the executives use emerging innovations to fight for and retain a shrinking consumer base (i.e., consistently under 60% domestic home ownership by 2015), how will investments in technology be made and deemed successful?  How can traditional baselines to analyze success be counted on to validate assumptions, predictions, and risks when there is no model to compare against?

Layering, Outsourcing, and Employment Shifts

Moreover, with many banking solutions and lenders rushing to offer housing solutions on thin, mobile tablet computers supported by ranges of cloud computing solutions (i.e., IaaS, PaaS, SaaS), what should the investment model look like? 

As RSA, a division of EMC, released last week, aspects of its non-repudiation systems and security offerings had been compromised (e.g., stolen “seed records”) potentially impacting thousands of banking operations and tens of millions of customers.  Why is this important?  As an example, with outsourcing of technology components more and more common (e.g., layering of solutions to achieve expedited, go-to-market results), the risk profiles associated with ROI attainment must be utilized as discounting factors – not multiplying factors.  

Looking forward, assessing the value of sustainable technology provisioning, security, communications connectivity, polar application interfaces, and BCP (business continuity planning) will cause many initiatives to be terminated within just 6 months after deployment. 

Additional forward looking factors include personnel and skills, loss and liability projections, media coverage and brand growth, and legacy system cannibalism and runoff.  Reinforcing just one of these aspects is that with a record of over 85% of all domestic employees looking to change jobs in the next 18 months, nearly 35% to 50% of their unique operational knowledge will exit with them.  For traditional valuation approaches, where is the discounting within the discrete technology investment model? 

Lessons learned can be found across prior failed justifications.  Just as rumors are surfacing that Microsoft is finally coming to grips with its Zune player, real estate executives are now recognizing that spending innovation capital should only take place where investment models are understood, risk attributed, and treated holistically moving from the consumer through the investment supply chain.  

Simply following the competitive crowd or using a one-off prototype or proof-of-concept effort for investment decision making can lead to substantial losses if not properly analyzed and discounted against multi-faceted success criteria. 

After all, how many copycat solutions will the housing market support before once celebrated technology solutions are forced to be written off (e.g., smart devices, tablets, data warehousing, CRM)?  How many investment failures will be tolerated before staffing changes are mandated as solutions are commoditized?  

A Varying Picture

A device that continues to change the information consumption and channel usage is the tablet computer – iPad, Xoom, Slate, and over a hundred more all introduced in the last eight months. 

The average cost to develop a one-off real estate application ranges from hundreds of dollars in a week (e.g., programming books, registration with Apple, and an iPad) to hundreds of thousands of dollars spanning months of architectural design, development, certification, and deployment for enterprise application extensions (e.g., LOS, servicing, sales forces, investors, capital markets). 

As real estate professionals approach the new frontier of tablet computing for their homeowner prospects, best-practices can be adapted to improve the probability of achieving success.  Common ones include:

·         Identification of granular success criteria identified across all stages of the product or solution as it evolves (e.g., using ETCD3 for tablet computing, it uses eight taxonomies each with distinct KPI’s, 61 sub-groupings, and 14 behavioral multiplying and discounting attributes).

·         Tracking of life-cycle costs (using KPI’s) beyond the one-off approval for initiation linking them to performance criteria at personal, department, divisional, and enterprise levels.

·         Utilization of multi-disciplinary approaches to ensure not only delivery, but on-going efficient management (e.g., CMMI, Agile, ITIL, Six Sigma, e-SCM, ISO).

·         Determining where measuring (baseline and on-going) takes places – stages, starting points, and durations.  Returns will not be accurate if artificially isolated.  Costs will be understated if probabilities and assumptions (as discounting factors) are not assessed. 

·         Utilize third-party models and data to validate assumptions and projections – making sure its use is directly transferable to the initiative.  Where applicable, engage outside verifications for those efforts critical to enterprise success or politically volatile. 

·         Incorporate all benefits and costs into the budget life-cycle.  This promotes transparency and lasting accountability.

Historically, investments in technologies surround five common categorizations – revenue, cost, competition, consumers, and risks.  Moving forward, these areas will be augmented using aforementioned areas.  Justification for technology investment will be multiplied or discounted (or both) to obtain a complete analysis of investment – before, during and after implementation. 

Since 2007, the need to become relevant for evolving consumer, regulatory, and product markets is critically important.  However, the changing economic situations for the remainder of the decade are forcing new justifications surrounding the adoption of mass market technologies. 

Real estate and mortgage professionals will use whatever works to become successful.  For enterprises to positively leverage their skills and their market pulse, their technology investment approaches must move beyond traditional IT and emerging cloud principles to ensure business profits. 

 

Tags: , , , , , , , , , , , , , ,
Posted in Analytics | No Comments »

2011 – Uncertainty Yields New Spectrums of Modern Innovations

Monday, December 20th, 2010

By Mark P. Dangelo

www.Innovative-Relevance.com

As a New Year dawns 2010 is now firmly in the rearview mirror. Whereas, history produces apparitions of the time gone astray and haunting views of lost opportunities for an industry battered by lingering negative sentiments and poor volumes, now is not the time for a walk down memory lane.

The period of 2011 -2014 represents the creation of a new face for the housing and finance markets. Moreover, the spectrum of changes that are needed and desired will require widespread end-to-end innovations that will yield new leaders, while casting established players into forced M&A’s.

As we enter the fourth year of financial system modernization, 2011 will likely produce 5 to 8 unavoidable noteworthy industry mergers as margins continue to shrink and business models fail to change after three years of struggle – LOS, data aggregation, and of course, servicing.

Yet, while individuals and organizations focus on the allure of political actions to stem change, innovations are reshaping the need for regulations. Major modern financial innovations – data, modularity, asset grouping, cloud computing, and mobility — are fundamentally changing nearly every aspect of the financial value chain (e.g., homeowner, originator, broker, servicer, issuer, investor). The real “fight” resides within emerging non-traditional areas.

For 2011 – 2012, with volumes low and prices stagnant, the major trends will include:

1. Data is the new Coinage: 2011 will usher in the beginning of a new and growing class of investment data pioneers eager to aggregate and deliver multi-dimensional information demanded by regulators seeking transparency and liquidity (e.g., Thomson-Reuters, Moody’s). Utilizing strategic alliances and joined together with robust technology innovations, data will be accurately assembled and mined across five taxonomies (i.e., 1) Content and Repositories, 2) Integration and Standardization, 3) Manipulation and Filtering, 4) Value-Add and Discovery, and 5) Market and Security Analytics) to meet the price points of even the smallest broker, originator, or servicer.

2. Commonality for Commoditization, Distinction for Competitiveness: Why build it from scratch, when you can leverage or assemble it from existing solutions? Across the manufacturing world, this approach has become a standard practice. As finance and its markets seek out innovation, the use of and assembly with common platforms, data repositories, and technologies will provide a path for cost-efficient, timely solutions sought after by investors, homeowners, and financial consumers. Moving forward, and taking a page from the discipline of flexible manufacturing, financial innovation will be concentrated on the competitively distinctive, modular compartments (i.e., functionality, processes, “i” solutions), which create barriers to entry, while establishing loyalty and behavioral linkages with the most profitable homeowners and consumers.

3. Moving Beyond the GSE Safety Net: The on-going saga of receivership regarding the Government Sponsored Enterprises (GSE’s) has created market expectations and obligations which are unsustainable. Whereas, the Financial Reform of 2010 took aim at the dealings of Wall Street — ABS’s, MBS’s, derivatives, consumer protections, financial stability — the unlimited support for GSE’s (and the aforementioned reform’s failure to address) have displaced the critical urgency needed for their disposition and the lasting need for interconnected private capital markets. However, the 112th Congress may not be a passive investor in footing implicit and explicit debt guarantees now in excess of over $5 trillion. Look for new private ATS markets, enabled by REG AB, ready to pick up the GSE market share, while the politics of their taxpayer liabilities will drag out for most of 2011.

4. Regulations are Cosigned to a Different Priority: Regulatory guidance is traditionally equivocal and subject to interpretation – and it is ill-suited for rapid technology and data advances currently dominating operational systems. Technology and markets move much faster than regulatory guidance. So, rather than struggle against the markets, new regulations are once again focusing on the “spirit” of the rules in an attempt to remain relevant. This interpretation of regulatory behavior has precedence – it was and remains the guiding principle for SOX implementation and adherence since 2002. For the next three years, detailed guidance addressing historical deficiencies – REG AB, Basel, Article 122a, Topic 820, NRSRO’s, et al – will be implemented impacting billions of investors and consumers in conjunction with individual issuers, trustees, and market operations. With all good intentions sought to right a wrong or seek retribution, regulations can produce unintended consequences. These “gotcha’s” will crop up during 2011 – 2014, but their downside pain will not truly be known until the end of the next “super-cycle.” But like all regulations, they will feed into a new super-cycle starting in early 2012.

5. Mobility will be the “App” for Homeowners and Market Leaders: Whereas, personnel have selectively embraced the interfaces and features of mobility, their enthusiasm does not translate into direct organizational results – quite the contrary. Without a comprehensive understanding of the channel facing mobility and the market evolutions underway, misguided decisions will be made —likely contributing to a greater than 70% failure rate of mobility initiatives not meeting expected measurements and quality. For the early leaders of mobility, roughly 5%, their organizations embarked upon a dual competency series of programs – for personnel and the organization. 2011 will witness an explosion of applications and secure mobile data especially pre-LOS, LOS, and for servicing (in an effort to reach out to and maintain a link to disaffected homeowners). This technology taxonomy will witness a 30% to 55% increase in 2011 within the IT budget – as legacy investments are reduced.

For 2011, a few of the ancillary trends incorporate:

1. A Rebirth of Mortgage Bonds: Private mortgage bond markets are beginning a resurgence. In 2011, as the government tackles the GSE’s (and with “Plan B,” C, and D alternatives), the global risk to yield ratio will rise along with volumes. Underwriting, along with common data standardization from origination through securitization (and pool management), will produce confidence and aid in the disposition of government market interventions and assets.

2. Tablet computing unites with cloud computing: The rise of complex tablet computing operating environment along with the introduction of thousands of applications developed every month, will accelerate the use of cloud computing. The dual use of these devices will also force an examination of all policies and procedures regarding privacy, security, and data.

3. Return of the Investor: The investor will finally return in 2011 seeking out new opportunities for investment – that is risk attributed investment. New exchanges (e.g., DelphX, SunGard), underpinned by granular data discovery programs, will deliver transparency and liquidity desired by global regulators. “Junk will remain junk,” but quality assets will be sought after.

4. The obsolescence of the Chief Strategy Officer (CSO). The days of the CSO are numbered. As the need for innovation turns from a whim to a core competency, the Chief Innovation Officer will replace the CSO in many executive teams and boards. This 50 year ideal has run its course.

Finally, as these aforementioned trends gain success, and subscriptions to their DaaS (Data as a Service) underlying applications and repositories increase, look for an expansion of the housing markets with differentiation residing in the customization of reports, channels, intelligence, customer services, and interfaces.

As we prepare for a new year, it has been said, “We don’t fear death – we fear being forgotten.” For some, this fear will be realized as they cling to traditional ideals and principles in the hope for a renaissance – the” same old lang syne” particularly as rates gravitate to normal. For other providers and vendors, the pain of adoption and adaption to new consumer and financial modernization trends will result in industry leadership.

So, as the economic recovery sputters and job recovery is a full two years away, the spectrum of innovational changes will take place across a broad range of solutions. So put the eggnog away.

2011 still holds a great deal of pain for those in traditional housing roles, but it holds vast opportunities within and across the six structural areas of growth and innovation for financial system modernization – 1) Data and Discovery, 2) Modularity and Compartmentalization, 3) Technology Innovation, 4) Capital Markets, 5) Government Regulations, and 6) Situational Uncertainty.

Tags: , , , , , , , , , , , , ,
Posted in Analytics | No Comments »

Data Integrity – The “Movable” Pillar of Discovery and Substantiation

Wednesday, April 21st, 2010

By Mark P. Dangelo

www.Innovative-Relevance.com

Integrity.  A character defining word that ranks with ethics, morals, and principles.  Its denotation affirms exceptional personal conduct, while its business implications suggest repeat customers, market status, and brand durability. 

More to the point, who can argue with the need for integrity, authentication, and chain of custody when it comes to financial and personal data that must be examined under scrutiny, forensics (e.g., fraud, transactional), or penalty of law? 

Whereas integrity principles are accepted as beneficial, it is in the achievement of these goals where money is lost and legal cases won – or lost.  There are cascading and hidden risks within, which are only surfaced when misfortune (e.g., delinquencies, foreclosures, class-actions, securitization failures) is internally recognized. 

Yet, for many individuals and organizations, the realization of integrity for data is something more mysterious.  It is commonly pushed deep into the enterprise — to the technologists in the back office.  Data integrity has little relevancy or correlation with today’s corporate strategies, operations, quality conformance, and profits.  Right? 

Fallacy and Reality

It seems every five to seven years, industry specialists and business leaders declare victory over the “hydra” of data integrity – classically defined as having three components of entity, referential, and domain.  With “victory” achieved, the organization and its focus shifts to the next problem or market challenge vexing its bottom line.  The data integrity requirements and regulatory mandates (e.g., business rules, data life-cycle, fail-safe controls) fade into the realm of IT myth and folklore.

However, with the steady advancement of technologies and practices (e.g., guaranteeing of data integrity in public cloud computing environments), the acceptance of demise for data integrity requirements creates false security – and lurking liabilities.  Like the hydra of mythology, the requirements compound and grow back (like the heads of the legendary beast gaining ferocity), becoming a menace to operational sustainability and business viability. 

With litigation and due diligence surrounding the data elementals of handling, storage, authenticity, durability, touchpoints, and isolation on the rise, it appears that hydra of integrity has found new life.  Some common data integrity misconceptions are frequently voiced as:

·         “Since our organization has structured application systems for our FMG (finance and mortgage group) operations, isn’t it a given that we  have the data integrity we are required to have for regulatory compliance?”

·         “We have standards for data entry fields, so why should we be concerned about the elements within the data repositories, marts, applications, and storage farms?  Isn’t data integrity really just about standards and field capture?”

·         “Data integrity is only about old application systems and approaches (e.g., flat files, VSAM, spreadsheets, point-based systems).  We have a commercial database and have spent years creating robust functionality in our origination and servicing systems.  Data integrity was taken care of years ago in our organization.  Sounds like much to do about nothing– like the IT department looking for a budget increase.”

Some of you reading this are probably just about ready to find another article that is more “edgy” or “important” to your organization.  Some would argue, this topic is old and stale and has very little to do with 3-years of housing’s turmoil and the current challenges facing FMG survival?  Let’s take a quick look at just a few of the realities documented by various organizations.

·         Annual price tag for bad loan data in the U.S. financial markets was as high as 7.3% of revenue – QAS Research, a unit of Experian,

·         FDIC reported that over 83% of the mortgages they audited contained violations,

·         Over 50% of the data corruption and integrity issues reside outside of technology – IBM, “Transforming Enterprise Information Integrity,” and

·         With over 90% of all records stored electronically (or scanned into electronic formats), the ability to maintain integrity over the life of the financial product (and for compliance) is material.

Moreover, with existing and pending legislation, additional concerns arise for the integrity of historical data stores and for future databases.  A very small snippet of these include (depending upon your business and model):

·         Consumer protection agency and its proposed charter,

·         Rule 803(6), U.S. Federal Rules of Evidence (see Info Law Group, “Privacy, Security, and Intellectual Property Law,” January 29, 2010),

·         “Skin-in-the-game” implications of Congressional financial bills (i.e., consequences of “cradle to grave” data life-cycle demands for definition, discovery, and defense), and

·         Existing and proposed state sponsored “breech” legislation – and consequences.

To believe that the guarantee of data integrity has been “met” across financial markets that are redefining rules of operation and conduct is fraught with peril.

A Principle-Driven Data Integrity Approach

For experienced enterprise architects, the utilization of principle-driven approaches is familiar – and represents stability and consistency for ever-increasing technological options.  Made famous in the “IT Paradigm Shift” by Don Tapscott and Art Caston, the use of the PRI (i.e., principle, rationale, and implication) architectural framework has gained global acceptance especially with the deployment of specialized technologies, layered outsourcing arrangements, and application compartmentalization. 

With estimates currently ranging from 4% to 9% of an IT’s budget directly or indirectly being consumed by information discovery, due diligence, and defense, the life-cycle challenge of data integrity cannot be left to chance. 

Table 1 provides an illustrative example for IT and business leaders of the granular and interdependent PRI’s, which are needed for the next decade.  So before you purchase the next origination system, sign up with a servicer, or restart private securitization efforts, ask yourself, “How are we addressing these areas, at what cost, and with what exposure?”

Table 1 – Illustrative PRI for Data Integrity / Data Architectures

Principle

Rationale

Implication

To guarantee adherence to organizational values, data custody and authentication must be able to be verified and certified by an objective and qualified third-party.

·          With the rapid adoption of cloud computing solution sets, data routing and its transmission cannot be assumed to be tamper proof.

·          Sequencing of data segments, since they may come from multiple sources and technology platforms, must involve the full acceptance of the data record or demand a complete rollback of all elements.

·          More than ensuring data and time stamps.

·          Demands more than standard hashing algorithms.

·          All data transmitted across public networks and from layered applications will be subject to predetermined certification tests.

·          Best practices will be adopted / modified to ensure data integrity of the highest quality.

·          On-going / continuous monitoring.

The validity of data and its consistency of capture, storage, and usage must conform to all published enterprise standards and applicable in-country regulations (e.g., privacy, confidentiality, et al).

·          Enterprise data demands must recognize disparate requirements, laws, and compliance demands when crossing local, state, federal, and international borders.

·          Within pending regulations, new implications of handling, storage, and usage will be demanded, with the “old” practices requiring a different set of data integrity “release” parameters.

·          If data is shipped in a cloud, its route should not violate laws on its path to corporate systems (a current challenge for network data routing in a cloud).

·          Compartmentalization of data management elements, schemas, and logical representations (along with all the rules and validation edits), should be maintained and able to be reconstructed for the life of the data.

Unless explicitly exempted by data owner, all data, rules, and manipulation must be implemented utilizing “data isolation modules” (DIM’s).

·          Identify and ensure fail-safe controls.

·          Ability to reconstruct “versioning” of data evolution at a discrete or elemental level.

·          Minimize reoccurring expenses associated with development and application segmentation.

·          DIM’s will have been validated and certified by custodian of record.

·          Taxonomies of data must be developed and maintained.

·          Any exception must be documented and sanctioned by corporate officer.

·          Use of (n)XML standards for data interchange and portability.

·          Common data models.

Data must be classified by both durability and risk to uphold usage, archival, and retirement.

·          With changes in technology solutions (i.e., technology is the least stable part of an architectural solution), portability and availability of data must be guaranteed.

·          A comprehensive data life-cycle approach for ensuring data integrity goes beyond application and database systems.

·          Part of a robust master data management (MDM) approach.

·          Years after the original transaction, due diligence demands will require a comprehensive review of all touchpoints including the outside review of litigants.

·          Workflows must reflect data requirements.

·          Rules engines do not singularly satisfy data integrity demands.

Data, and the transactional streams used during their life-cycle, must adhere to / exceed all auditing, logging, and compliance requirements.

·          With litigation on the rise, the “states” of data, its manipulation, and its usage must be captured across all its forms / transition states.

·          To support processes and regulatory demands, the data underlying the organizational certifications must be managed according to generally accepted practices that have been proven trustworthy in a court of law (i.e., they should be accepted by corporate legal advisors and auditors).

·          Use of robust WORM solutions according to performance, regulatory, and cost constraints.

·          All DIM’s and associated API’s must be certified.

·          Off-the-shelf certified solutions that incorporate industry standards, will be given preference during system “ever-greening” (to reduce capital costs, custom tailoring, while ensuring repeatability across multiple locations).

·          Monitoring and benchmarking of adherence will be done every (xxx).

Data sourcing, sequencing, and trustworthiness (SST), must be identified and maintained over the life-cycle of the data in adherence to corporate data standards and practices.

·          A clear system of record must be defined and maintained to guarantee efficacy and integrity.

·          With the data sourcing chain now firmly linked across origination, servicing, and securitization, access to the original data source (and the guarantee of its integrity) will be a top 5 corporate responsibility (and potential expense) during the next decade.

·          The use of “ACID” properties should be part of the certification process.

·          Use of existing and evolving data standards will be favored over internal, one-off solutions (to reduce costs, risks, and ETL requirements).

·          Developing and delivering data intelligence (DI) as part of standard operating procedures.

·          Strong and enforceable (with consequences) data polices.

NOTE: Illustrative and abbreviated for presentation purposes

 

After reviewing this lengthy table, some will ask, “Where’s the technology?  Where are the explicit standards?”  How can you have a data integrity architecture without solutions?” 

If we could add additional columns to the right, we would then add in the technology and discrete solution sets needed to deliver the principle-driven architecture that has been rationalized with its interdependencies.  So far, we’ve aligned organizational need, identified processes, and touched on the need for personnel and skills.

Perhaps the questions that make more sense for business personnel using this approach include, “What technologies are required to satisfy the business needs and operational requirements (inherent in the business and operational needs of the first three columns)?  What solutions best fit our ‘As-Is,’ ‘To-Be,’ and gap implementation programs of work for minimal capital costs and maximum return ensuring data integrity rigor / discipline?”

So yes, data technology and standards are very important – but only after the operating parameters have been articulated and approved.  They will vary for nearly every FMG driven by their management team, markets, and current challenges.  The interesting aspect of this proven approach is that once defined and maintained, it works in concert with numerous development or provisioning methods, applications needed, or outsourcer selected. 

In summary, the data integrity principles outlast the technologies, promote non-linear decision making, and “hold up” under the scrutiny of review.  For business leaders signing the checks of new solutions, it gives tremendous business case justification to “why IT does matter.”  And, when it comes to legal and regulatory challenges, preparation and anticipation are always cheaper than intrusive discovery and evidence gathering.

Challenges within Cloud Computing and Virtual Data Provisioning

Last, but not least, are the data integrity challenges materializing within cloud solution sets.  Since cloud computing and associated data storage options are one of the fastest growing offerings (e.g., Amazon, IBM, Dell) we cannot neglect the evolving issues of data integrity within the clouds.  (For an extensive discussion of cloud computing challenges and deployments, see The Alchemy of Creating Intelligence in “The Cloud”, by Mark Dangelo, October 2009). 

Data routing and storage within the cloud is one of the leading concerns facing publically provisioned cloud computing environments.  As the data is routed via a host of third-party, and country controlled telecommunication services, it can be exposed to fraud, corruption, sequencing challenges, and of course, privacy constraints. 

Additionally, given the types of interfaces and security mechanisms deployed across disparate computing platforms, the ability to introduce error and fraud has also increased when the flexibility of “pay-as-you-go” cloud computing is added.  Bottom line, there are exceptional benefits and values with cloud computing – but for today, organizations must consider exposure, risks, and consequences before placing mission critical or financial transactions over them.

The good news is that there are standards and practices that are being developed, which should be mentioned.  These include multiple standards from Object Management Group (OMG), Storage Network Industry Association (SNIA), Organization for the Advancement of Structured Information Standards (OASIS), and many others (for a comprehensive list see http://cloud-standards.org/wiki/index.php?title=Main_Page).

 

* * * * * * * *

 

As you can see, data integrity is a complex discussion that incorporates many horizontal and vertical disciplines in FMG’s, within computer science, auditing, and legal professions.  The final question that has yet to be asked is “How do I know if my organization has a data integrity problem?”  Well, if this is the first time you have asked that question for your enterprise….

 

For additional information and discussion on data integrity, please attend the “How Much Is Data Integrity Costing You?” conference session on April 26, 2010, 3:00 p.m., at the MBA’s National Technology in Mortgage Banking Conference.  For a complete list of session panelists and topic discussions see www.mbaa.org.

 

Tags: , , , , , , ,
Posted in Analytics | No Comments »

« Older Entries