People often ask me for a universal data model for banking, credit card processing, securities brokerage



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Universal Data Models Financial Services By Len Silverston People ten ask me a universal data model banking, credit card processing, securities brokerage or other specific aspects financial services. I reply that there is a universal data model financial services (see The Data Model Resource Book, Volume 2, Wiley, 2001) that provides detailed, generic data models suitable all types financial service enterprises including banks, securities companies, credit unions, brokerage services, credit card companies and many other types financial services enterprises. Should there be separate data models each these specific types businesses or should there be common data constructs that handle the inmation needs any these types finance services? One reason providing a common financial services model is that enterprises ten provide (or may provide in the future) many these various financial services. Another reason is that various types financial service organizations usually have very common inmation needs. In each these types businesses, individuals or organizations make financial transactions against their financial accounts. Accounts are governed both the agreements that are established the account as well as financial regulations. Financial service products ten have features such as the interest rate and functional settings such as when to send statements. This article explores the issue having specific data models such as a banking or securities brokerage model versus having a generic financial services model. As this article summarizes and expands upon The Data Model Resource Book, Volume 2, please refer to this book a great RELATIONSHIP CONTACT RELATIONSHIP WORKER RELATIONSHIP SUPPLIER RELATIONSHIP PROSPECT RELATIONSHIP INFORMAL RELATIONSHIP SHAREHOLDER RELATIONSHIP SYNDICATOR RELATIONSHIP EMPLOYMENT EMPLOYEE CONTRACTOR CONTACT SIGNER SHAREHOLDER PROSPECT # ID involved in NOTARY PUBLIC PRIMARY JOINT CO-BORROWER FINANCIAL INSTITUTION REGULATORY AGENCY EMPLOYER COMPETITOR HOUSEHOLD SUPPLIER described PARTICIPATING SYNDICATOR GUARANTOR PARTNER CONTROLLING SYNDICATOR AUTHORIZED BORROWER involved in COSIGNER OTHER ROLE the description RELATIONSHIP TYPE # RELATIONSHIP TYPE ID o DESCRIPTION described Figure 1: Financial Services Party Roles and Relationships used to define # ID TYPE the description used to define

many more details and explanations behind the models in this article, plus examples the types data that would populate these models. The models provided in this article (and in related universal data model publications) are fered to provide toolkits common data structures that have been proven to work in real-life enterprises. However, they are not intended to represent the only right answer in modeling this type data. Certainly, there are many options with pros and cons; and the experienced data modeler knows to base the data model on the requirements the enterprise, using tools such as universal data models when they are applicable. This article will principally focus on four key data areas within financial services: parties, accounts, agreements and financial products. Financial Services Parties Figure 1 provides a party model that can be used financial service enterprises. As in most other enterprises, there are S and S, or various PAR- TIES that may take part in various S and may be involved in various RELATION- SHIPS. The entity records inmation about the or independent the or role or relationship such as name, demographics, SSN or federal tax ID. The subtypes would be used to relate inmation about the party in the context role, such as the credit rating(s) a. Thus, certain types inmation are only related to a specific role a party and not all parties. Theree, it is useful and usually practical to maintain inmation about specific party sub-entities. The RELA- TIONSHIP entity maintains inmation about two parties such as the status or priority the relationship. Each may be many S, thus identifying the various ways in which people and organizations may interact with the enterprise. Some may argue that BANK overseen BANK benefiting BANK # NUMBER * ESTABLISHED DATE o CLOSED DATE TYPE # TYPE ID signed BANK SIGNER o MAXIMUM AMOUNT BANK HOLDER initiated from overseen the initiator # ID Figure 2: Specific Bank Account Roles Data Model responsible signing as owner the primary owner SIGNER JOINT PRIMARY these party roles are subtypes a party. Thus, a could be a subtype party. However, how can we then show that a party can play many roles? For instance, a party may be acting as a, a SHAREHOLDER and an EMPLOYEE at the same time. These would then need to be inclusive subtypes party. Thus, there could be many inclusive subtypes, making the model quite complex. Some data modeling conventions such as Oracle Designer s subtyping notation boxes within boxes doesn t even allow inclusive subtyping, and subtypes are defined as mutually exclusive. Others may argue that the party role only makes sense within the context a relationship. Thus, if an organization is a customer, with whom do they have the customer relationship? There may be two or more customer relationships such as a relationship between the customer and one bank and another relationship that the customer has with another bank. However, regardless the number relationships involved, there is still inmation about the customer ( instance, the customer credit rating) that may be related to the customer (assuming the enterprise only stores the credit rating customers) and should not be recorded redundantly each relationship. Additionally, some party roles may exist without a corresponding party relationship; example, a person may play the role NOTARY PUBLIC, thus further establishing the need a ROLE independent the relationships involved. The accommodates any number various roles, allowing additional roles to be added over time. The subtypes within are shown to illustrate the various

types roles that may exist a party, and both the logical data model and physical design should be customized depending upon the individual needs the enterprise. Alternate ways modeling this inmation are to either just include the or just to include the subtypes; however, both are shown in Figure 1 illustrative purposes. The RELA- TIONSHIP TYPE allows categorization the various types relationships that may exist. The relationship from the RELATIONSHIP TYPE to the TYPE provides a mechanism to maintain business rules about what types roles may exist what types relationships. For example, it may define that an employment relationship is a relationship between an employee role and an employer role. Note that many the LOAN COSIGNER backed LOAN AUTH BORROWER benefiting LOAN # NUMBER * ESTABLISHED DATE o CLOSED DATE TYPE # TYPE ID LOAN GUARANTOR o FROM DATE signed LOAN CO-BORROWER initiated from the initiator # ID ROLE subtypes shown apply to many types financial service organizations. For instance, banks, credit unions, security brokerage companies and credit card companies all typically have the S PRIMARY, JOINT OWNER, FINANCIAL INSTITU- TION, REGULATORY AGENCY, SIGNER, GUARANTOR, and NOTARY PUBLIC as well as many the very generic roles such as EMPLOYEE, CONTRACTOR, CONTACT, SHAREHOLDER and SUPPLIER. Accounts Financial services enterprises such as banks, credit card companies and securities organizations set up accounts their customers in order to track and group financial transactions according to the customers wishes. Figure 2 shows a portion a bank Figure 3: Specific Loan Roles Data Model COSIGNER signing as owner the primary owner AUTHORIZED BORROWER GUARANTOR CO-BORROWER PRIMARY account data model with some the specific roles associated with bank accounts. A BANK must be an TYPE such as a checking, savings or money market account. A BANK may be overseen one or more BANK S, be set up the benefit one or more BANK BENEFICIARIES, have one or more BANK SIGNERS, have one or more BANK HOLDERS and, depending on the business rules the enterprise, have one and only one PRIMARY. Of course, the last relationship mentioned will vary based on the enterprise; however, many financial institutions require that one party be the primary customer and need the social security number that party income tax reporting purposes. Another relationship to BANK is the ORGANIZA- TION that initiated the account. One may alternately m a relationship from BANK to the BRANCH that initiated the transaction (along with the routing number that branch), which could be shown as either a subtype ORGA- NIZATION or a subtype the. Is BRANCH a subtype or is it a subtype? Is it possible that the organization that represents a branch could later play additional roles such as a division, affiliate or department the enterprise? Again, depending on the business rules and needs the enterprise, one may want to consider alternate options. Figure 3 shows a similar model to Figure 2 only with the appropriate roles involved in loan accounts: namely, COSIGNERS (people authorized to sign transactions on the account), AUTHORIZED BORROWERS (people authorized to borrow against the account), GUARANTORS (parties that guarantee payment is case default), CO-BORROWERS (the various parties that are responsible repayment) and the PRIMARY CUS- TOMER (the primary party responsible). The roles involved and their relationships to (as well as

business terminology) may vary depending on the business rules and needs the enterprise. Figure 4 again shows a similar model only with the roles associated with a brokerage account. While these roles are very similar to BANK roles, most enterprises maintain separate accounts securities transactions. However there may be a current or future opportunity to manage both bank account and securities transactions together. Specific Modeling or Generic Modeling? Figure 5 provides a more generic account model that meets the needs a wide variety financial service enterprises including savings and loan accounts, brokerage accounts, line-credit accounts and many other types accounts. Whether a data model should be designed more specifically or more generically depends on a number factors such as the modeling style used, the requirements the enterprise and the intent the data model. For instance, is the purpose a data model to document the data-oriented business rules an organization or to provide a flexible generic structure to maintain inmation about the enterprise? If the data model s purpose is to document the business rules and requirements the enterprise, Figures 2, 3 and 4 accomplish this. They also provide some flexibility allowing a single place to record the BROKERAGE overseen benefiting BROKERAGE # NUMBER * ESTABLISHED DATE o CLOSED DATE TYPE # TYPE ID BROKERAGE BROKERAGE AUTH SIGNER o FROM DATE signed BROKERAGE JOINT PARY initiated from overseen inmation about a person or organization, independent roles. If the purpose the data model is to provide a flexible structure that will accommodate changes to the enterprise over time, Figure 5 s model the initiator # ID Figure 4: Specific Brokerage Roles Data Model responsible signing as owner the primary owner SIGNER JOINT PRIMARY works well. For instance, the previous models show that there is one and only one PRIMARY a bank account. Many financial institutions require that there be one primary customer tax purposes, and they Notes about this data modeling notation: A crow s foot (three prongs at the end the relationship line) indicates that there are many occurrences the entity near the crow s foot each entity that is not near the crow s foot. For example, each may be one or more S (entity names are shown in caps in this article). The dotted line indicates optionality (as opposed to mandatory) each side the relationship. Each TYPE may be (because this is a dotted part the line) the description one or more S. Reading the other way, each must be described one and only one. A # in front an attribute indicates that this attribute is a key. An * indicates that the attribute is a mandatory attribute. An o bee an attribute indicates that the attribute is optional. Boxes within boxes indicate subtypes or subentities. The tilde () on the relationship line represents eign key inheritance. This means that the primary key the entity closest to the tilde includes, as part its key, the primary key the entity without the crow s foot.

need to record the social security number the primary customer and hold that party primarily responsible. What if the business rules and policies the financial services organization change over time and there could be equally responsible JOINT PARTIES on an account? In the more specific data models, the underlying data model (and any corresponding data structures) would need to change. Thus, in the model represented in Figure 5, an may have any number ROLES, which are each a and described an ROLE TYPE. In this model, the s are stored in instances the entity and could be signer, guarantor, joint party and so on. This structure allows additional roles to be easily added over time just adding a new instance. For instance, a new business practice may involve another role party notices which designates to whom notices should be delivered. Additionally, TRANS- ACTIONS may involve many roles parties such as the person(s) or organization(s) depositing funds, the person accepting these funds, the person that records the transaction in the system, the person responsible verifying that the transaction is correct and so on. Again, the roles and the business rules could change over time, so the model easily accommodates change. However, this latter model does not ence many business rules. Any number parties can play any number roles, and new role types can even be added over time. Where, then, are the business rules documented and recorded? If our purpose is to provide a flexible data structure, another business rules layer could be defined over the data model structure in order to accomplish flexibility as well as precision defining the requirements. How, then, does one document the business rules? There are many answers such as documenting business rules and relating them to the attributes affected; and as this is the topic ongoing debate in the business rules movement, alternatives are available TRANSACTION ROLE involved with # ID involved with ROLE # NUMBER *DESCRIPTION described the description described DEPOSIT SAVINGS CHECKING CERTIFICATE OF DEPOSIT MONEY MARKET INVESTMENT VEHICLE OTHER # ID Figure 5: Account Roles Data Model through avenues such as the Business Rules Forum. Agreements and Products Although there are many more details available within the financial services model, there are two additional major data objects within financial services organizations: products and agreements. Figure 6 illustrates some the key relationships from S to AGREEMENTS and from each these to FINANCIAL PRODUCTS. Each AGREEMENT may be comprised several AGREEMENT ITEMS which although not shown in Figure 6 ultimately relate to the description TRANSACTION TRANSACTION * TRANSACTION DATE o ENTRY DATE o POST DATE o AMOUNT FINANCIAL TRANSACTION WITHDRAWAL FEE DIVIDEND SECURITIES TRANSACTION MUTUAL FUND TRANSACTION PURCHASE TRANSACTION REDEMPTION TRANSACTION EXCHANGE TRANSACTION REQUEST TRANSACTIONS INQUIRY REQUEST SPECIAL REQUEST within used to group together FINANCIAL CARD DEBIT CARD LOAN MORTGAGE DEPOSIT INTEREST PAYMENT BUY TRANSACTION SELL TRANSACTION CHANGE REQUEST VEHICLE LOAN INSTALLMENT LOAN LINE OF CREDIT CREDIT CARD EQUITY LINE either the terms or conditions the agreement and could ultimately include relationships to various assets held the parties involved in the agreement (these are examples some the details stored in the more full version the model). Each may be governed one or more agreements; instance, there could be numerous contracts that are associated with a loan account. An AGREEMENT may also govern many S; instance, a banking customer may sign an agreement with the bank governing his/her various savings accounts at the bank. The financial services products an enterprise may include both prede-

fined products such as a checking plus fering or a customized product that is defined and established a particular customer. Each financial service fering may include a number features (FEATURE) such as the interest rate (the value attribute stores the amount interest), the annual fee (the value attribute stores the fee), and a standard feature such as checks are provided free with the account. Customized products may be med specific customers ( instance, high-wealth customers). A customized product may be a higher interest investment account with special FEA- TURES that are established use a customer. Hence, there may be agreement items that specifically entitle certain features that are negotiated the agreement. A high-worth individual may negotiate a higher interest rate; hence, the AGREEMENT ITEM is applicable to a FEATURE (through the FEA- TURE APPLICABILITY entity) that was negotiated such as a higher FEATURE APPLICABILITY # FEATURE APPLICABILITY ID o VALUE described AGREEMENT ITEM # AGREEMENT ITEM SEQ ID part composed available AGREEMENT PRODUCT used within AGREEMENT ITEM # AGREEMENT ID * AGREEMENT DATE o TEXT FINANCIAL AGREEMENT LOAN AGREEMENT INVESTMENT AGREEMENT LEASING AGREEMENT OTHER AGREEMENT described Figure 6: Financial Segments and Products interest rate or a waiver any minimum balance. Are financial products tied to accounts or to agreements? The model shows the relationship from the FINANCIAL PRODUCT to both the and the AGREEMENT, depending on the circumstance. A LOAN AGREEMENT may be in place a specific type product, and an account may not be needed ( instance, if the customer agrees to borrow a lump sum and pay it back a year later). Other scenarios would suggest that one or more agreements are associated with an, which is then associated with one or more FINANCIAL PRODUCTS. For instance, there may be a brokerage agreement with terms and conditions the brokerage account as well as an agreement that provides power attorney privileges to a close family member. How can there be more than one financial product an account or an agreement? Over time, the product PRODUCT FEATURE * THRU DATE o VALUE governing available with FINANCIAL PRODUCT # PRODUCT ID AGREEMENT the description described the description used within governed FEATURE # FEATURE ID PRODUCT # NUMBER DEPOSIT FINANCIAL CARD INVESTMENT VEHICLE LOAN OTHER described an account or an agreement may change. The from date and thru date on AGREEMENT PRODUCT and PRODUCT allow the enterprise to record a change in products on the account ( example, changing from a checking plus product to a standard checking product on an account). Are there Right and Wrong Data Models? The models in this article are intended to provide ideas, concepts and alternatives and illustrate possible pitfalls within modeling financial services (although many these concepts apply to many other industries as well), allowing the data modeler to be more effective and develop higher quality models in less time. Are the models presented in this article the right answer to modeling financial services applications? Or are they wrong compared to other ways modeling the inmation? I believe that these models can be used as productivity tools and perhaps fer perspectives that the modeler may not have seen, especially because many these universal data models fer insights from actually implementing these types designs. Furthermore, each these models should be used and customized as needed the needs the enterprise. However, they are not a substitute effective requirements analysis. Thus, I believe these universal data models are not right or wrong, but useful in effective modeling. If modelers do not have to redevelop the wheel and we can share ideas and models, then we are also practicing the art data sharing and integration. Special thanks to Graeme Simsion, Patrick Wilson and Jeffrey Katz sharing their expertise as I developed this article. Len Silverston is a data management consultant with more than 20 years experience in helping enterprises integrate data. He is the author the best-selling The Data Model Resource Book series (Wiley, 2001), which describes more than 230 integrated, reusable generic and industry-specific data models. Silverston has developed extensive stware versions these data models some which are now licensed worldwide Microst and some that are available licensing directly. Silverston s company, Universal Data Models, provides consulting, training and stware to jump-start data modeling and data warehouse design efts while increasing design quality and facilitating data integration. Silverston can be reached at lsilverston@univdata.com.