These are
Investment Banking Data Models
that we have created based on our experience at Credit Suisse and other Banks.
Here are some useful links :-
Data Architecture with 3 Layers
Data Architecture with 5 Layers
SOA Data Governance
Links to external Web Sites :-
Financial Products Markup Language(FpML)
Progress offering on FpML
Wikipedia on FpML
Wikipedia on Financial Instruments
Wikipedia on Futures Contracts
Wikipedia on Securities
Here are some
Subject Area Data Models
:-
Accounts
A key building-block.
Assets
Including Assets and Asset Types
Brokers
Including Addresses and Contacts.
Clients (Customers)
Including Addresses and Facilities.
Deals with Financial Instruments
Deals and Financial Instruments.
Deals - FX
Shows details of FX Deals.
Deals - General
A starting-point for Deals in general.
Deals - Simple & Open-Ended
Shows a simple starting-point which is open-ended.
Enterprise Data Model
Top-Level starting-point with Subject Areas.
Financial Instruments
Description
of Financial instruments which can be either cash instruments or derivative instruments.
Financial Instruments Data Model
Data Model
for Financial instruments showing Sub-Types.
Financial Services Authority
The FSA regulates Banks and Financial Institutions.
FpML - What is it ?
Good Introduction.
FpML Products
Shows different Products with an Inheritance relationship.
FpML Products Data Model
Shows FpML Products as an ERD Data Model.
Global Custody
Involves processing cross-border securities trades, keeping financial assets safe and servicing portfolios.
Life Cycle of a Deal
Description
of the Stages in the Life Cycle of a typical Deal - Buy, Monitor, Sell.
Life Cycle of a Product
Life Cycle of a Product thru Front, Middle and Back Office
Market Quotes
Data Feeds provided by Bloomberg or Reuters for Exchange-Traded Derivatives
Middle Office
Middle Office is responsible for execution of a Trade
Settlements
Involves settling Trades.
Staff
Dealers, Traders and more.
Transactions
Tracking Share Transactions
Data Warehouse / Marts Models ...
Data Mart for Position and Risk Mgt
Shows Conformed Dimensions but needs work to remove P and L data
Data Warehouse (1)
Before Facilitated Workshop.
Data Warehouse (2)
After Facilitated Workshop.
Discussion with Users identified that analysis by Trader was required.
Therefore Trader replaced a Dimension. Similarly for Currencies.
Data Warehouse (3)
After all Facilitated Workshop.
This Final Version includes all the data that will meet the business requirements.
Federated Data Marts
Third-party Data Models ...
IBM Banking Data Warehouse
This is a useful reference.
