How to deliver a Single Customer View

How to deliver a Single Customer View

How to cost effectively deliver a Single Customer View

Many have tried, and many have failed to deliver a “Single Customer View”.  Well now it’s a regulatory requirement – at least for UK Deposit Takers (Banks, Building Societies, etc.).

The requirement to deliver a Single Customer View of eligible deposit holders indirectly affects every man, woman and child in the UK.  Their deposits, large or small, are covered by the UK Deposit Guarantee Scheme.  This scheme played a key role in maintaining confidence in the banking system during the dark days of the world financial crisis.

UK Deposit Takers must not only deliver the required Single Customer View data, they must provide clear evidence of the data quality processes and controls they use to deliver and verify the SCV data.

The deadline for compliance is challenging.  Plans must be submitted to the regulator by July 2010, and the SCV must be built and verified by Jan 2011.

To help UK Deposit Takers, I have written an E-book explaining how to cost effectively deliver a Single Customer View.  You may download this free from the Dataqualitypro website:

While the document specifically addresses the UK Financial Services Requirement for a Single Customer View, the process steps will help anyone planning a major data migration / data population project.

If you are in any doubt about the need for good data quality management processes to deliver any new system (e.g. Single Customer View, Solvency II, etc.), read the excellent Phil Simon interview on Dataqualitypro about why new systems fail.

Show me your Data Quality

Recently Marty Moseley explored how much data governance you should have in a thought provoking post called how taxing is your data governance.

I added the following comment “I agree with you – lightweight governance is the way to go – as you say “just formalized enough” Data Governance  framework, creating “good enough” deliverables to record your decisions, alternatives, precedents, drivers, policies, procedures/processes, business rules, enforcements and metrics – and find them later when you need to invariably make changes – OR WHEN THE REGULATOR asks to see your audit trail.

The fact is that regulators increasingly require evidence of the data quality of the underlying data on which you base your regulatory submissions.  Not just that they require evidence of your data quality management processes, i.e. your Data Governance.

The law now requires evidence of your data quality

For example, in the UK, Deposit Holders are required to build a Single Customer View (SCV) of depositors (UK FSA Single Customer View requirement)  They must not only build an SCV, the regulation states “We… would need to verify that the SCV information being collated and stored by a deposit taker was adequate and fit for purpose”.   Consultation Paper CP 09/3 about the SCV states “As part of their data cleansing, deposit-taking firms would be required to ensure the existence, completeness and accuracy of all data required for each depositor to facilitate fast payout”

A second example affects Insurance companies providing insurance in Europe (this also affects US Insurers operating in Europe).  EU Directive 2009/138/EC (Solvency II) – Article 82 states: “Member States shall ensure that insurance and reinsurance undertakings have internal processes and procedures in place to ensure the appropriateness, completeness and accuracy of the data used in the calculation of their technical provisions.” In other words – the regulator in each member state is required to review and approve the Data Governance processes of insurers.

Failure to comply with Regulatory requirements can prove expensive. Ask Standard Life.  It cost them over £100 million.  I presented details of the Standard Life case at the Information and Data Quality Seminar Series 2010 – Dublin. (For more details, see slides 11 and 12 in my presentation “Achieving Regulatory Compliance – The devil is in the data“.)

Shortly, working together with DataqualityPro, I will publish an E-Book on how to cost-effectively satisfy the (UK FSA Single Customer View requirement).  UK Deposit Holders must submit their SCV implementation plans to the FSA by the end of July 2010, and must complete their SCV by Jan 2011.  Time is running short.

Are you aware of other laws requiring evidence of Data Governance and Data Quality? If so, please share them.

Common Enterprise wide Data Governance Issues – #14. No Enterprise wide Data Model

I was reading David Loshin’s excellent post How Do You Know What Data is Master Data? and I thought “I know – I’ve covered that question in my blog” – but I hadn’t.  So here it is.

Your “Enterprise Wide Data Model” tells you what data is Master Data.

Unfortunately, most organisations lack an Enterprise Wide Data Model. Worse still, there is often little appreciation among senior management of the need for an Enterprise wide Data Model.

Impact:
The absence of a Enterprise wide Data Model makes it difficult for even technical experts to locate data.  The data model would distinguish between Master data and replicas, and would clarify whether the data in the model is currently in place, or planned for.  Without an Enterprise Wide Data Model, data dependent projects (e.g. BASEL II, Anti Money Laundering, Solvency II) must locate data (especially Master Data) from first principles, and face the risk of not finding the data, or identifying inappropriate sources.   New projects dependent on existing data take longer than necessary to complete, and face serious risk of failure.

Solution:
The CIO should define and implement the following Data policy:

An Enterprise wide Data Model will be developed covering critical Enterprise wide data, in accordance with industry best practice.

Time to sing from the same hymn sheet

One notable exception to the norm:
This is not a plug for IBM…. merely an observation based on my experience.

I worked in an IBM development lab in Dublin during the 90’s. At that time IBM developed a “Financial Services Data Model” (FSDM). Dublin was IBM’s “FSDM centre of excellence”. BASEL II turned FSDM into an “Overnight success”- TEN YEARS after it was developed. Organisations that had adopted IBM’s FSDM found it relatively easy to locate the data required by their BASEL II compliance programme.

I forsee a future in which all financial services organisations will use the same data model, including Financial Regulator(s).  “Singing from the same hymn sheet” will make communication far simpler, and less open to misinterpretation.

The lack of an Enterprise Wide Data Model is just one of the many data governance issues that affect organisations today.  Assess the status of this issue in your Enterprise by clicking here:  Data Governance Issue Assessment Process

Does your organisation have an “Enterprise wide Data Model” – if so, how did you achieve it?  Did you build it from scratch, or start with a vendor supplied model? Please share your experience.


Common Enterprise Wide Data Governance Issues: #3 No culture of Data as an ‘asset’, or ‘resource’

Some enterprises fail to recognise the true value of their data.  This post is one of a series dealing with common Enterprise Wide Data Governance Issues.  Assess the status of this issue in your Enterprise by clicking here:  Data Governance Issue Assessment Process

Impact:

  • There is little value attributed to capturing and maintaining high quality ‘informational’ or ‘Master data’.
  • The other Enterprise Wide Data Governance Issues in this series are all symptoms of the failure of the enterprise to treat Data as a corporate asset.  An Enterprise that treats Data as a valuable corporate asset understands the value of data, and is likely to have addressed the issues I have identified.

Solution:
Agree and implement the following policies:

  • Data must be treated as a valuable Enterprise asset, that can assist the Enterprise achieve its strategic objectives, and must be invested in proportionally to other Enterprise assets.
  • The CIO is responsible for ensuring that the quality of Master data is measured, target data quality levels are agreed, and measures are implemented to meet the defined targets.

Your experience:
Have you faced the above issue in your organisation, or while working with clients?  What did you do to resolve it?  Please share your experience by posting a comment – Thank you – Ken.