Tag Archives: Data Modeling

Legal form: a modelling journey, part II

If we want to understand more about how to model the entity legal form appropriately, we need to understand the stakeholders and various other aspects surrounding the legal form. There are several types of stakeholders involved in the administration of the legal form of an entity, and concerns for each may be different. These will be described here.

The company or legal entity itself

The first stakeholder for the legal form of a given legal entity, is the company/legal entity itself. The legal entity wants to have a very clear view of what its own legal form was at any given time. It also wants to communicate its current legal form to other stakeholders so they can estimate the risks attached to doing business and then proceed from there. Nobody wants to do business with a legal entity when you cannot tell if you have any recourse if you never get paid or if paid items are never delivered.

However, nobody will take the company’s word for their legal form, so you need an independent party, preferably embedded in a legal framework, to vouch for your current legal form. That party is called the registrar.

The registrar

The registrar of legal entities and legal forms for a given region is concerned with making sure that there is an official administration where you can examine the legal form of any given legal entity without having to rely on their word or examine the legal papers of their incorporation. Basically, the registrar wants businesses to be clear on each others legal form so they can do business with each other.

Registrars can be local, national or even international, such as the Global Legal Entity Identifier Foundation (GLEIF). The closer the registrar is located to the company, the more reliable will the registration be, in general. Often, the legal framework mandates a single registrar to be responsible for the registration of the company’s legal entity and legal form.

We enable smarter, less costly and more reliable decisions about who to do business with.
– Global Legal Entity Identifier Fondation

Banks and financial institutions

Banks and financial institutions are particularly interested in the legal form of any company that they are involved with, especially if they are providing a loan in any form to the legal entity. In the European Union, they have to report to the regulatory authorities on the loan, as well as on the counterparties, due to the fact that the bank now has a counterparty risk. Weighing those risks on a national and even systemwide level is the task of the central banks. The legal form is necessary if you want to estimate how much money you can recover in case of failure: can you recover from only the entity involved, or can you also recover money from the shareholders or owners?

Other vendors

Apart from financial services, a company may also contract other vendors for products or services. Most of the business of any company is done with these parties.

Vendors typically want to know the same thing as a bank, but are not usually required to report to regulatory authorities. They are mostly interested in the current legal form, because once the goods are delivered, the service is rendered or payments received, the interest in the legal form of the counterparty ends as well. Vendors are always other legal entities with their own legal form, and this means the company has an interest in their legal form as well.


Clients can be natural persons or legal entities. Natural persons are usually not overly concerned with the legal form of the company, as they are normally protected by consumer laws and the monetary amounts involved make it hard to recoup losses in court. However, clients can also be other large companies and they will certainly want to recoup any losses, for instance in case of malpractice or fraud. This means that they are very similar to a vendor in their interest in the current legal form of the company.

Tax authorities

Many legal forms have tax implications. When moving from one legal form to another, there can be tax implications as well. You can, for instance, have a “quiet” transfer from one form to another, or a “noisy” transition, where you pay everything off and basically start fresh. But even in setting up a company with a given legal form, there are often tax rules you have to follow. For instance, in the Netherlands the director of a limited liability company must have a certain minimum wage which must be approved by the tax authorities.

Other government agencies

While in many countries the legal forms are quite generic, there are also countries where certain professions or specific types of company have their own legal form. An example would be “trader” or “farm operator” in France (read more interesting details on French legal forms here). One can imagine that certain legal forms (like “chemical factory”) would come with a certain amount of paperwork and various stakeholders that would like to know more.

Local versus national versus international stakeholders

In a local environment (usually on the level of the ISO 3166-2 country subdivision such as a province or state), the legal form is known to both sides, as well as the approximate risks and rights that come with it. This usually (but perhaps not always) translates to the national legal framework in a way that makes a legal form in one area legally consistent with a similar legal form in another area, even if they have different names.

This does not always work however. The USA is well known for the way in which different states have set up legal forms with some very specific rights and obligations, such as in Delaware, which is known as a tax haven.

In any case, this translation breaks down whenever you cross national boundaries into other legal frameworks. To combat this inside the European Union, the EU has created a number of legal forms that are implemented exactly the same in any national legal framework, such as for instance the Societas Europaea (SE), the Societas Europaea Cooperativa (SCE) and the European Grouping of Territorial Cooperation (EGTC). They are defined in European law. But this mechanism does not extend to other legal frameworks, such as the one in the USA or China.

Note that it is possible to have a legal entity in one country with a given legal form, whih has a local company branch with a local legal form, that can be subtly different from the main one. The complexities of offices, branches and holdings are beyond the scope of this article however.

The next part

I hope you liked this part as well. In the next part, we are finally going to start modelling!

Legal form: a modelling journey, part I

Abstract vision of a legal form for a company, in a landscape of country and language.

The AnaCredit regulation is an interesting regulation. Having closely worked with the Dutch modeller who drafted the logical model for it at the DNB, it’s one of my favorite models to demonstrate. It compresses literally hundreds of pages of rules and regulations in a single model. To the dismay of most banks when they first saw it, but eventually to the benefit of all of its users.

However, one issue has always been a bit of a pain. And that is the concept of legal form. You are required to report it for the counterparties involved in loans. But at the time the regulation started, some banks had not used foreign legal forms but had mapped them onto their own home countries versions. Others had incomplete registrations. And most of them had issues with languages: in Belgium you can register a company in three different locations, with three different names for the legal form, but they are all the same. Even worse, you can potentially have the situation that you have the same code in different national languages but they mean something different. This means that using the legal form code without any other descriptive attributes is a problem.

Legal form is a bit of a weird duck in a way. Everyone knows it. Everyone uses it. But when asked to describe what it is, you get wildly varying answers. Obviously, the ECB doesn’t know what it is either, or they would not have made the list they use now (you can check out the ECB List of legal forms yourself).


On the internet it’s not that easy to find a definition of legal form. The ones I can find come close to the joke about an elephant, described by a number of blind people: they describe the visible attributes but not the core, the “ding an sich”. See for instance this definition: while it starts good with “the legal form (also known as legal status) is defined according to national legislation” it then goes on and on about its use.

So what is it then? The best I can come up with, is that the legal form under which a company operates, is defined in the national legislation. The name of the legal form and the abbreviation are sometimes given in that legislation, but not always. In the end, any legal form code or name is a shorthand for a referral to a particular paragraph in the national law of any given country or group of countries such as the EU.

For instance, in Dutch law we have a limited liability company. This is called a “besloten vennootschap” and abbreviated as “BV”. This is defined in het Burgerlijk Wetboek (civil law book), book nr. 2, article 175. This says that any BV is a legal person, with named shares, where the shareholders are not liable for any losses over the amount of capital they have put into the company. And that is the basic definition of this particular legal form (although there are more articles describing this legal form in more detail).

Do not make the mistake of assuming that this particular legal form is the same as the limited liability company in other countries: liabilities can be limited in very different ways and can be undone on very different grounds. That is why you really need to include the country when you define legal form.

A legal form is also unique not just by country but by official language in that country. In Belgium, as you can see in the ECB List of legal forms, they have a legal form that has three names (and corresponding acronyms):

  • Unité TVA – UTVA (French)
  • BTW-eenheid – BTWE (Dutch)
  • Mehrwertsteuereinheit – MWSE (German)

This particular legal form has a single surrogate key, meaning that to the ECB, it is just one single legal form. So far, so good though.


Now, so far things are relatively simple. But they’re getting a bit more difficult when you realize that some EU countries have no standardized set of legal forms. Try finding the ones for Portugal, for instance. On the official government website you can find nine legal forms. But the Anacredit list has twenty of them, and one even has no acronym. The thing the website does well, though, is that it refers you to the exact paragraph in the law that describes and regulates the legal form. Portugal is an example, but not an exception.

Things get funnier when you add the ISO standard into the mix. Yes, there is an official ISO standard (ISO 20275:2017 – Financial Services – Entity Legal Form) for legal form, because the mess has not escaped the attention of the standardization committee. The data model is described in the standard, but there is also a registrar for worldwide legal forms, the Global Legal Entity Identifier Foundation (GLEIF). I’ve described this standard in an older post.

Some of the differences between the lists are:

  • The GLEIF list contains legal forms on a country subdivision code level (ISO 3166-2), used in for instance the USA and Canada, where the ECB list does not. This becomes interesting in the case of Madeira, which is subdivided in the GLEIF list but part of Portugal in the ECB list. Where the GLEIF lists two legal forms for Madeira, none are mentioned in the ECB list;
  • The GLEIF list contains 31 legal forms for Portugal, the ECB list only has 20, and the Portuguese government lists 9. Have fun trying to find out which one is valid for your case. Portugal is just an example here, the deviations are similar for many countries;
  • The local name is nice, but do you also want it in the local script? This becomes a relevant question for cyrillic names in Europe, and for other non-Western scripts such as Chinese and Arabic that may not even be read from left to right. The GLEIF lists the local name in the local script and provides a transcription to the Western script as well. But the ECB list does not. If you are lucky you can get them from the GLEIF list, and otherwise, well, there’s always ChatGPT;
  • The GLEIF list sometimes lists an abbreviation, sometimes not. The abbreviations can be in the local script, in that case there are usually, but not always, transliterations into the Western script.
  • The GLEIF list sometimes lists multiple versions of abbreviations for the same legal form for the same language for the same country. The ECB list only does that for different languages in the same country. Good luck matching them up.

So how do we get out of this mess? Well, we don’t 🙂 The mess will remain. But you need to understand for what purpose you need the legal form of a legal entity. The main purpose is to determine the amount of risk and exposure you are taking on if the legal entity in question is your counterparty. If you do business globally, this matter becomes more urgent. A secondary purpose is to report this to the relevant authorities, notably the ECB with the AnaCredit reporting requirement, who does the same but on a higher (aggregate) level, except that exact legal forms are limited to European counterparties, and for global ones you are allowed to approximate them.

We can create a data model that will enable us to fulfill most of these requirements. Given the data issues I doubt it is possible to get full coverage for all countries and all legal forms, but we can certainly do much better than just add the nearest acronym to a legal entity, and hope for the best. How to do this data model is a subject for the next post, however.

PowerDesigner do’s and don’ts

Many people consider PowerDesigner to be the de facto standard datamodelling tool. Many people are right. However, that does not mean the tool is perfect. As many users can testify, the version 16 release has been quite buggy in the beginning, only stabilizing a bit more with 16.5. And this is not exceptional. The repository is still buggy, projects are a recipe for pain, and let’s not start a discussion on license prices – we’d still be here next year.

However, if you avoid some practices and adopt others, using PowerDesigner is a breeze. Here is my take on things.

Do Not:

  • Use the repository
    The repository is a major cause of bugs. It looks nice, like a venus flytrap, and then it sucks you in and eats you for breakfast. Avoid it like the plague. You are better off spending some money on creating an extension to generate a model export to your own repository. You can buy this from I-Refact or other parties. The other functionality can be done better, cheaper and with less frustration and bugs by just using standard version control software (TFS, git, etc.). If you must compare models, you can do that from within PowerDesigner with very little effort – without losing parts of your model on the check-in/check-out.
    There is only one part of the repository that is actually semi-useful, which is the indication whether your model is out of date versus the repository version. As this functionality does not cooperate with replication or extensions that use that, there is little point in it once you evolve beyond the basics. Also, it is much better to split up your models so as to avoid getting in a situation with 10 people working on the same model. Even potentially. If this is a risk, appoint a designated datamodeller for such a model. The rest can get a read-only version.

  • Hide attributes on entities by hiding them
    Unless you use an extension to automate setting/un-setting this and also indicate this visually, it can create no end of trouble when the model shows tables and columns but leaves out certain columns that then get deployed anyway. It takes ages to debug that. If you must do this, make sure it’s an all or nothing proposition: either hide all standard attributes, or none.

  • Create shortcuts to other models
    While PowerDesigner does this automatically once you start creating mappings, there is no need to refer to models outside the scope of the folder, as this will render the models almost impossible to deploy without heaps of pop-ups asking about other models that you have not yet stored in the right location (and don’t even know where they should be located). Only consider this if you have an agreed-upon folder structure and even then I recommend you don’t do this.

  • Create Projects
    Sure, they’re good for having a dependency graph view. But you can create those anyway. And projects are buggy, especially when interacting with the repository. Half the bugs I found in PowerDesigner went away when I stopped using projects and moved to workspaces. No more disappearing models, or graphics. No more models that are impossible to check out or check in.

  • Work for long periods without saving
    The PowerDesigner auto-save function is nonexistent. After you work with PowerDesigner for a while, you will learn to save often. It becomes a reflex. Because it hurts when you lose hours of work through a crash. It’s not as bad as it was when you were still using version 16.5.0, with repository and projects, but still.

  • Use auto-layout without a current back-up
    Your gorgeous, handcrafted model could use a minor improvement and you used auto-layout. And then you pressed “save” automatically, because by now it’s a reflex. And when the screams died down, you realized you didn’t have a current backup. Ouch. Backup often. If you use Git: commit often.

  • Model the entire Logical Data Model as a hierarchy of subtypes
    I have seen them, with their entity types derived from the Object supertype and each other, six hierarchical layers deep. I dare you to try it with a non-trivial model and then generate a working physical model out of it. Go ahead, make my day…

  • Create a unique data domain for each attribute
    This sort of misses the point of data domains. Because while they are rather limited in PowerDesigner (no entity types or attribute groups), they are most useful when they provide a single point to change definitions of common attributes. Use them freely, but let the data architect decide which ones are available for use. It’s best to create a single model for this, that you can use as a template for the other models you create.

But Do:

  • Add metadata to your models
    Especially metadata that describes the following items: Title, Subject Area, Author, Version, Data (Model) Owner, Modified Date, Modifications, Validation Status

  • Add domains
    Create a list of standard attribute domains, then create a template model containing them. People can either copy the model file directly and use it as a template (this creates havoc in a repository though, because the internal model ID will be the same as that of the template model), or copy the attribute definitions into your own model. The definitions should be controlled by the data architect(s).

  • Add attribute groups
    If you create attribute groups of commonly grouped attributes in keyless entities, you can then inherit from multiple of these entities in order to combine them. Most useful when you have things like “firstname/lastname” pairs of attributes that you do not want to separate out to their own entity, for some reason. Use with caution.

  • Tie models together with separate workspaces for each project
    Workspaces are small files with zero overhead that tie different models together. They have no impact on the repository check-in/check-out, they are files that can be under source control, and they are pretty much bug-free. You can even edit them when necessary. Much better than projects.

  • Store your models in version control systems
    Seriously, I should NOT have to say this, but I keep meeting people who don’t seem to realize that MODELS ARE CODE. And with a VCS I do not mean that abortion they call the repository. I mean TFS, Git or even Subversion. Anything that works, basically.

  • Save often
    If you don’t, you’ll regret it.

  • Store backups
    Having version control is not the same as having backups, unless you commit often.

  • Create a folder structure that is the same for everyone and make it mandatory
    If you don’t, you’ll create unending pop-ups whenever someone opens a model they did not create themselves. If they check it in, it’s your turn the next time you open it from the repository.

Is data modeling the next job to be replaced by AI?

The more I read, the more I am convinced that data modeling is an activity that will be supported, perhaps even replaced, by deep learning AI like Watson real soon now and that the true focus of data governance should be the business conceptual model. All other models derive from there.

After posting this on LinkedIn I received some interesting feedback. The main question was of course “how so?”. Well, here are a number of the things I read and experienced that led me to this conclusion.

1. Data Modeling Essentials (Simsion/Witt, 3rd ed. 2005). It’s not very strict but very readable and has a nice division between the three layers: conceptual, logical, physical. This is where I started. It explained clearly that these different layers are distinct, but not exactly *how*. Or rather: I didn’t understand it at the time.

2. Applied Mathematics for Database Professionals (2007, Lex de Haan/Toon Koppelaars). This explains how the logical model is built and differs from the conceptual and physical models. It starts and ends with the math behind it all (predicate logic and set theory) yet is easy to understand for most data professionals. It made the distinction between the different layers MUCH clearer to me and especially how the logical model is a fully mathematical activity. That is a hard separation between the conceptual and the logical model, even though the semantic part of the logical model is still derived from the conceptual model. Because if you suddenly use different terms and verbs, it is obviously not a derivation but instead a different model.

3. The FCO-IM book by Bakema/Zwart/van der Lek, which explains how you can have a conceptual model that is fact-oriented and can then be transformed into a logical model. This means that when you can impose an ordering on the language of the conceptual model, you should be able to derive a logical model from it.

4. My own experience with fully verbalized data models, i.e. data models written down in sentences. Most data models have a small vocabulary: “One Client orders one or more Products. Our Company has a Relationship with a Party. A Client is a Party. A Legal Entity is a Party.” The amount is in fact unlimited if you so desire, but in practice can be boiled down so far there is even a standard for it: Semantics of Business Vocabulary and Rules (SBVR).

5. Very influential: The “ISO TR 9007 – Information processing systems – Concepts and terminology”. This defined the conceptual model and was created by a number of very well-known information modeling scientists. It influenced me heavily because it defines a conceptual model as essentially something that conveys semantic meaning, i.e.: words on paper. It starts, for instance, with the Helsinki principle.

6. Discussions with Martijn Evers (and numerous other colleagues at the Dutch Central Bank and outside it) about data modeling.

7. The sorry state of modeling tools in general. If PowerDesigner is the best we have, we’re in trouble. Sparx Enterprise Architect is actually pretty good, but you can’t program it so you have to make do with what it is. E/R Studio just crashed when trying to evaluate it last time round. And https://www.vertabelo.com/ looks nice and is webbased, but it just does the physical modeling. None of those tools do conceptual modeling anywhere near right. Colibra has the textual part down pat, but only relates business terms to other terms. An ontology, while nice, is the start of the process, not the end. Conceptual modeling is a text-based activity that encompasses the business glossary, the visualization, the business rules etcetera and it’s not just about creating lines and boxes on a canvas. There is currently no tool that does conceptual modeling as a text-based activity.

8. The rapidly advancing state of the art in deep learning. I had artificial intelligence courses in the 90’s, but it wasn’t very advanced at the time. Nowadays, it’s much further. I’ve been looking into Watson (IBM) capabilities over the past week. See for instance https://www.ibm.com/watson/services/natural-language-understanding/ where it says that Watson can: “Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, relations and semantic roles.”

9. The experience of the Watson team that a combination of skilled human and decent AI will generally beat even a higher skilled AI and higher skilled human.

10. The fact that the conceptual model is verbalized, and that we now have Wikipedia and Facebook. I think we can have “social modeling media” now. This should increase the speed of modeling immensely. Example: suppose that DNB owns definitions in the Dutch part of the global Finance Business Glossary. And that we can derive logical models from that glossary. And physical models from that logical model. Then that would speed up the process of building reports and applications to conform to regulations enormously. It would also nail the nasty little business model of IBM and Teradata with its hide to the wall (and not by incident).

11. Finally, I can see as well as anyone the incredibly urgent need for data modeling and the serious and increasing lack of data modeling expertise in the labor market. We can either give up on modeling, or we can make it so easy everyone *can* do it. Therefore, the latter *will* be done. Example: the car market was once considered to be limited to the number of available professional chauffeurs. So, the need for professional chauffeurs was removed. Otherwise, Henry Ford wouldn’t have had a market.

I cannot say with certainty that AI will be able to fully automate the entire modeling process (especially not reverse engineering). But what I *can* say is that a large amount of what a modeler does can be automated even today. An even larger part can be done with AI, and the final part can be done together.

In the comments, one person said that AI deep learning and modeling are (mathematically speaking) fundamentally different activities and that therefore you cannot automate the modeling. I agree that they are different, but I do not think it matters for the end result. Playing Go is fundamentally different from translating text, but both can be handled by the same type of algorithm. I foresee this will be similar to modeling, for most cases. The fact that you cannot handle all cases is irrelevant: see item 9.

What about source models without meaning, that can be modeled today by humans, another comment asked. I do not think that that is a relevant issue: reverse engineering will remain difficult, but it’s not the issue I’m concerned with. Because reverse engineering means turning an illegible set of fields and tables into a conceptual, textual model. My point is that the reverse process of turning text into tables and fields is easy to automate, the other way round is inherently just as difficult as turning mayonaise into eggs: the arrow of time, entropy, just does not fly that way.

Martijn Evers stated that “given sufficient quality in models that represent semantic concerns, and sufficient quality in deriving logical models we can nowadays already generate all kinds of implementation models. No AI is needed here. This could change for very large and complex implementation models, but by and large we can do a lot without AI in this respect.” I agree. I just think that using AI reduces the necessary quality of the model to the point where even people with moderate amounts of training can handle this competently. Which is the point of item 11.

Most commenters agreed that a human-machine hybrid approach was in the works. One even pointed out an existing (and very good!) recent article about this topic: http://www.dataversity.net/artificial-intelligence-vs-human-intelligence-hey-robo-data-modeler/. The question thus is “when” and “how”, not “if”.

Please note: this article was also posted on Linked: https://www.linkedin.com/pulse/data-modeling-next-job-replaced-ai-ronald-kunenborg

Image credits: created by Alejandro Zorrilal Cruz [public domain], via Wikimedia Commons. Source: https://commons.wikimedia.org/wiki/File:Artificial.intelligence.jpg

ISO standards for Finance business data

When I define a business glossary to prepare for the high-level corporate data model, I try to incorporate as much of the relevant standards as I can. Because usually, knowing up front about a standard will make it much easier later on to integrate with other parties in the value chain, to report to regulatory authorities that use the same standards, and to apply Master Data Management. The more data that adheres to international standards, the less work you have in managing it.

Below, I have provided a list of ISO standards that can be used to aid in the governance of your business glossary and data models, standards that provide metadata specific to Finance and standards that provide identification schemes for key entities.

Note that there are more finance data and metadata standards than just the ISO standards. These will be listed in a different post that I will then link from here (and vice versa).

ISO standardAreaDescriptionID?
ISO 00639GeneralISO 639 defines language codes, as opposed to country codes. The standard consists of 6 parts, some more detailed than others. The preferred standard is ISO 639-3, which is the most comprehensive substandard. Usually, we restrict ourselves to a subset of supported languages.

See for more information: https://en.wikipedia.org/wiki/ISO_639
ISO 03166GeneralISO 3166 is a standard published by the International Organization for Standardization (ISO) that defines codes for the names of countries, dependent territories, special areas of geographical interest, and their principal subdivisions (e.g. provinces or states). The official name of the standard is "Codes for the representation of names of countries and their subdivisions". It consists of three parts:

  • ISO 3166-1 contains all codes currently in use
  • ISO 3166-2 contains all codes for subdivisions
  • ISO 3166-3 contains all codes no longer in use

The three standards contain several codes: alpha-2, alpha-3 and alpha-4. The alpha-2 code is the recommended code for general use.

See for more information: https://www.iso.org/iso-3166-country-codes.html
ISO 04217GeneralISO 4217 is the standard that defines codes for currencies, as well as funds and minor currency units. The codes can be represented as a 3 letter code, or a numerical code with 3 positions, which is usually the same as the numerical country code from ISO 3166-1. The minor currency is given as an exponent for the division, by 10. I.e. if the minor currency is "3", the currency can be divided into 1000 minor units. The name of the minor unit is not part of this standard.

The current version of the standard is ISO 4217:2015.

See for more information: https://www.iso.org/iso-4217-currency-codes.html
ISO 06166FinanceThe ISO 6166 standard is called "Securities and related financial instruments -- International securities identification numbering system (ISIN)". This standard describes and defines the International Securities Identification Number. The number applies to fungible and non-fungible securities and financial instruments.

ISINs consist of two alphabetic characters, which are the ISO 3166-1 alpha-2 code for the issuing country, nine alpha-numeric digits (the National Securities Identifying Number, or NSIN, which identifies the security), and one numeric check digit. The NSIN is issued by a national numbering agency (NNA) for that country. Regional substitute NNAs have been allocated the task of functioning as NNAs in those countries where NNAs have not yet been established.

ISINs are slowly being introduced worldwide. At present, many countries have adopted ISINs as a secondary measure of identifying securities, but as yet only some of those countries have moved to using ISINs as their primary means of identifying securities.

The current version of the standard is ISO 6166:2013.

See for more information: https://www.iso.org/standard/44811.html
ISO 08601GeneralISO 8601 is about "Data elements and interchange formats - information interchange - representation of dates and times". It details how to represent dates and times when exchanging them with other systems in an unambiguous way.

The current version of the standard is ISO 8601:2014.

See for more information: https://www.iso.org/iso-8601-date-and-time-format.html
ISO 09362FinanceThis ISO standard defines the Business Identifier Code (BIC). BIC is an international standard for identification of institutions within the financial services industry. BICs are used in automated processing. They unambiguously identify a financial institution or a non-financial institution. The ISO 9362 standard specifies the elements and the structure of a BIC. A BIC consists of either eight or eleven contiguous characters. These characters comprise either the first three, or all four, of the following components: party prefix, country code, party suffix, and branch identifier. The ISO has designated SWIFT as the BIC registration authority.

The EU regulation 260/2012, also known as the IBAN only rule, requires financial institutions to add the BIC code to IBAN payments.

The rule has applied to any domestic EURO payment since February 2014, to any cross-border EURO payment between EU countries since February 2016, and to any cross-border EURO payment from non-euro countries since October 2016.

See for more information: https://www.iso.org/obp/ui/#iso:std:iso:9362:ed-4:v1:en
ISO 10383FinanceISO 10383 is called "Codes for exchanges and market identification (MIC)". It defines the Market Identifier Code (MIC).

This International Standard specifies a universal method of identifying exchanges, trading platforms, regulated or non-regulated markets and trade reporting facilities as sources of prices and related information in order to facilitate automated processing. Each such exchange, platform etc. receives a unique code from the registrar.

See for the current list: https://www.iso20022.org/10383/iso-10383-market-identifier-codes
ISO 10962FinanceISO 10962 defines the structure and format for classification of financial instruments approved by the International Organization for Standardization (ISO). There are many types of Financial Instruments used for saving, investing, trading, hedging and speculating. These instruments are generally organized in groups called "asset classifications." The most common asset classifications are generally described using terms like "Equities (Stocks)," "Debt (Bonds)," "Derivatives (Contracts)," "Currencies," and a few other generalized terms.

ISO 10962 provides a global standard for these classifications in the form of specific codes. Classification of financial instrument (CFI) Code is used to define and describe financial instruments as a uniform set of codes for all market participants. The code is issued by the members of ANNA, the Association of National Numbering Agencies. The group is currently working to simplify the structure so that it can be adopted more widely by non-governmental market participants.

The letters from the ISO basic Latin alphabet in each position of this 6 character code reflect specific characteristics intrinsic to the financial instruments that are defined at the issue of the instrument, and which in most cases remain unchanged during the lifetime of the instrument (or by the market on which the instrument trades).

See for more information: https://en.wikipedia.org/wiki/ISO_10962 or visit the registrar homepage
ISO 11179MetadataThe ISO/IEC 11179 Metadata Registry (MDR) standard) is an international standard for representing metadata for an organization in a metadata registry. ISO/IEC 11179 claims that it is (also) a standard for metadata-driven exchange of data in an heterogeneous environment, based on exact definitions of data.

The ISO/IEC 11179 model is a result of two principles of semantic theory, combined with basic principles of data modelling. The first principle from semantic theory is the thesaurus type relation between wider and more narrow (or specific) concepts, e.g. the wide concept "income" has a relation to the more narrow concept "net income". The second principle from semantic theory is the relation between a concept and its representation, e.g., "buy" and "purchase" are the same concept although different terms are used.

The standard consists of six parts:
ISO/IEC 11179-1:2015 Framework (referred to as ISO/IEC 11179-1)
ISO/IEC 11179-2:2005 Classification
ISO/IEC 11179-3:2013 Registry metamodel and basic attributes
ISO/IEC 11179-4:2004 Formulation of data definitions
ISO/IEC 11179-5:2015 Naming and identification principles
ISO/IEC 11179-6:2015 Registration

Part 1 explains the purpose of each part. Part 3 specifies the metamodel that defines the registry. The other parts specify various aspects of the use of the registry. An additional part, Part 7: Datasets is currently under development.

For use in the creation of data models, part 4 and especially part 5 provide common standards that could be used in data governance to govern the creation of data models.

See for more information: https://en.wikipedia.org/wiki/ISO/IEC_11179
ISO 13616FinanceThe International Bank Account Number (IBAN) is an internationally agreed system of identifying bank accounts across national borders to facilitate the communication and processing of cross border transactions with a reduced risk of transcription errors.

The ISO standard was split in two parts in 2007. ISO 13616-1:2007 "specifies the elements of an international bank account number (IBAN) used to facilitate the processing of data internationally in data interchange, in financial environments as well as within and between other industries" but "does not specify internal procedures, file organization techniques, storage media, languages, etc. to be used in its implementation". ISO 13616-2:2007 describes "the Registration Authority (RA) responsible for the registry of IBAN formats that are compliant with ISO 13616-1 [and] the procedures for registering ISO 13616-compliant IBAN formats".

The official IBAN registrar under ISO 13616-2:2007 is SWIFT.

The IBAN consists of up to 34 alphanumeric characters comprising: a country code; two check digits; and a number called the Basic Bank Account Number (BBAN) that includes the domestic bank account number, branch identifier, and potential routing information. The check digits enable a sanity check of the bank account number to confirm its integrity before submitting a transaction.

The current version of the standard is ISO 13616:2007

See for more information: https://en.wikipedia.org/wiki/International_Bank_Account_Number
ISO 15022Metadata - FinanceISO 15022 is the precursor to (and superseded by) ISO 20022.

See for more information: https://www.iso20022.org/15022/uhb
ISO 17442BusinessThe International Organization for Standardization (ISO) 17442 standard defines a set of attributes or legal entity reference data that are the most essential elements of identification. The Legal Entity Identifier (LEI) code itself is neutral, with no embedded intelligence or country codes that could create unnecessary complexity for users.

Four key principles underlie the LEI:

  • It is a global standard.
  • A single, unique identifier is assigned to each legal entity.
  • It is supported by high data quality.
  • It is a public good, available free of charge to all users.
Once a legal entity has obtained an LEI, it will be published together with the related LEI reference data by the organization that has issued the LEI. This means the full data on the entire LEI population is publicly available for unrestricted use by any interested party at all times, including the set of reference data for each LEI code.

The LEI code is structured as follows:

  • Characters 1-4: Prefix used to ensure the uniqueness among codes from LEI issuers (Local Operating Units or LOUs).
  • Characters 5-18: Entity-specific part of the code generated and assigned by LOUs according to transparent, sound and robust allocation policies. As required by ISO 17442, it contains no embedded intelligence.
  • Characters 19-20: Two check digits as described in the ISO 17442 standard.
The current version of the standard is ISO 17442:2012.

See for more information: https://www.iso.org/standard/59771.html or visit the homepage of the registrar
ISO 18774FinanceISO 18774 defines the Financial Instrument Short Name. The new standard for the Financial Instrument Short Name (ISO 18774) standardizes short names and descriptions for financial instruments. The standard was approved in September 2014.

As of July 1 2017, the FISN will be globally assigned concurrently with the ISIN (ISO 6166) and CFI (ISO 10962) at the time of issuance of a new financial instrument.

The ISO 18774 standard incorporates the issuer short name and the abbreviated characteristics for the financial instrument. It has a maximum length of 35 alphanumeric characters.

Unlike other ISO-standard financial instrument identification codes, the FISN is not meant to be machine-readable, but to provide a short format for essential information about a security for human use.

See for more information: http://www.anna-web.org/standards/fisn-iso-18774/
ISO 19773MetadataThis International Standard specifies small modules of data that can be used or reused in applications. These modules have been extracted from ISO/IEC 11179-3, ISO/IEC 19763, and OASIS EBXML, and have been refined further. These modules are intended to harmonize with current and future versions of the ISO/IEC 11179 series and the ISO/IEC 19763 series.

Part of the standard are, amongst others:

  • a data structure for UPU postal data
  • a data structure for ITU T E.164 phone number data
The current version of the standard is ISO/IEC 19773:2011.

See for more information: https://www.iso.org/standard/41769.html
ISO 20022Metadata - FinanceISO 20022 is an ISO standard for electronic data interchange between financial institutions. It describes a metadata repository containing descriptions of messages and business processes, and a maintenance process for the repository content. The standard covers financial information transferred between financial institutions that includes payment transactions, securities trading and settlement information, credit and debit card transactions and other financial information.

The repository contains a huge amount of financial services metadata that has been shared and standardized across the industry. The metadata is stored in UML models with a special ISO 20022 UML Profile. Underlying all of this is the ISO 20022 meta-model - a model of the models. The UML profile is the meta-model transformed into UML. The metadata is transformed into the syntax of messages used in financial networks. The first syntax supported for messages was XML Schema.

The standard contains a number of external reference code lists, that are available on the website in the form of spreadsheets and documentation. The data dictionary present in ISO 15022 is no longer available as a spreadsheet, but can be downloaded as a 96MB xml-file.

See for more information: https://www.iso20022.org/
ISO 20275FinanceThe ISO 20275 standard defines Entity Legal Form (ELF) worldwide. The latest (and first) version is ISO 20275:2017 (en). It covers the legal forms available per country (or country grouping), as long as that country has an ISO 3166-1 alpha-2 code.

The standard can be obtained from the ISO but the codelist itself is maintained by the Global Legal Entity Identifier Foundation (GLEIF) and can be obtained here.

Interesting to note is that where the AnaCredit list goes slightly off the rails with the European Legal Form "Societas Europaea", this list solves it in a nicer way by repeating the SE legal form for all countries involved. Although using EU is actually allowed by ISO 3166-1 standards as it is an alpha-2 code reserved for the special use of the EU, this way is cleaner as you now only deal with countries. Since the AnaCredit list goes off the rails in more ways than this, you may want to use this ISO standard as your main reference data set and add a mapping to the ECB's rather ragtag list of legal forms.

Currently there are legal forms for 55 countries in the list so locations that are currently missing need to be added through a feedback form.

The ELF for companies in the LEI register has been made public as of March 1st, 2018.

Certified Anchor Modeler

As of today, I am certified as Anchor Modeler. My thanks go to Lars Rönnbäck (UpToChange.com), the best teacher you could have, as well as Juan-José van der Linden for inviting me and to Essent for hosting the course.

While the community of Anchor Modelers is still quite small, it will likely expand as the concurrent-reliance-temporal model is extremely interesting. The notion of positors and reliance combined with the positing and changing time is quite advanced. I’m looking forward to combining this with Martijn Evers’ notions about timeline choices with respect to Consistency/Accuracy/Availability.

Presentation: history of DWH modeling

Dear readers, on june 6th I held a keynote presentation in front of 300 people, summarizing the state of DWH modeling. The conference proceedings of the day are available at BI-Podium .

My own presentation is available here as well: Next Generation DWH Modeling 2013 conference keynote speech

The Anchor Modeling folks also wrote a summary: Next Generation DWH Modeling

Anchor Modeling

Anchor Modeling is a new method of modeling a domain in a database. The method splits up all the attributes in their own table. This seems complex, but this actually simplifies maintenance. Furthermore, the method is flexible, quite resilient to change over time, does not need updates and is highly scalable.

These are good properties for a data warehouse model. In the article I explain how Anchor Modeling works and why you should at least take a look at it.
The article appeared in november 2009 in Database Magazine, Dutch magazine for database professionals. However, the magazine is now defunct and superseded by Business Information Magazine.

Download the PDF