Data Models for Banking, Finance, and Insurance

Data Models for Banking, Finance, and Insurance: Jumpstart Database Designs with Proven Patterns, by Claire L. Frankel

Jumpstart your financial application designs with proven conceptual and logical data models for banking, brokerage, and insurance.

Topics

One: Design Pattern Fundamentals

Introduction

Define the Business Needs

Do Not Promise to Boil the Ocean

About Data Modeling Tools

Middle and End User Expertise

From Conceptual, Logical, and Physical Models to First Cut DDL

Two: Conceptual Models for Financial Services

Model 1.0: The Fundamental Conceptual Model

Model 1.0: Customer <purchases> Product

Model 2.0: Conceptual Model for Financial Services: Retail and Commercial Banking

Model 3.0: Conceptual Model for Credit Cards

Model 4.0: Conceptual Model for Capital and Financial Markets

Model 5.0: Conceptual Model for Securities, Investments, and Brokerage

Model 6.0: Conceptual Model for Property, Casualty, and Life Insurance

Notes on Reference Entities

Three: Customer and Product Logical Models

Customer Logical Model

Model 7.0 Customer LDM

Model 7.01 Customer, left side of the model

Model 7.02 Customer, right side of the model

Model 7.03 Location Logical model

Product Logical Models

A Generic Product Logical ERD

Model 7.5 High-level Product Logical ERD

Four: The Logical Model Templates

Retail Banking

Model 8.0 Retail Banking Logical ERD

Model 8.01 Retail Banking (checking) the left side of the Logical ERD

Model 8.02 Retail Banking (checking), right side of Logical ERD

Model 8.03 Checking and Savings Accounts

Mortgage

Model 8.5 Mortgage High Level Logical Data Model

Model 8.5.01 Mortgage Detail LDM

Home Equity Loan

Personal and Business Loans

Model 9.0 Additional entity for Personal and Business Loans.

Model 9.01 Collateral entities added to support Loans – The ERD is on the next page.

Certificate of Deposit

Model 10.0 Retail Banking Logical ERD partial, with Certificate of Deposit entity added.

Commercial Banking

Commercial Lending

Accepting Commercial Deposits

Agent For

Model 11.0 ‘Agent For’ entities and attributes added to the Customer subject area

Credit Cards

Model 12.0 Credit Card data modeling lineage from entity Agreement―

Model 13.0 Credit Card Lineage from entity Product

Model 14.0 Agreement Logical ERD for Credit Cards:

Model 15.0 Product side of the Logical ERD for Credit Cards

Five: Stock Brokerage/Trade Processing/Investments

Model 16.0 High Level View of Investment Logical ERD

Model 16.01 Left side, showing the Investment Product Waterfall

Model 16.01a Equities, Options and Bonds

Model 16.02 Feature side of Investment Product

Model 16.03 Very Detailed Investment Logical ERD

Model 16.03a Equities and Options

Model 16.03b Bonds

Model 16.04 Investment Product section of the Investment Logical ERD

Model 16.05 Subtypes of Entity Investment Product

Model 16.06 Thirteen subtypes of Entity Investment Product

Model 16.07 Product and Product Feature of Investment Product subject area

Model 16.08 Feature side of the Investment Product subject area

Six: Property, Casualty and Life Insurance

Model 17.0 Insurance Logical ERD

Model 17.01 Left side of Insurance Logical ERD

Model 17.02 Right side of Insurance Logical ERD

Seven: Capital and Finance

Model 18.0 Capital and Finance Logical ERD for Journal and Chart of Accounts

Left side of Model 18.01 Journal and Chart of Accounts

Right side of Model 18.02 Journal and Chart of Accounts

Model 18.03 General Ledger in Capital and Finance

Eight: Physical Data Models

Model 19.0 Denormalized partial Customer Logical into a Physical ERD

Reporting / Data Warehouse / Star Schema

Model 20.0 High Level Data Warehouse Sample

From the beginnings of Western and Eastern civilizations, data has always driven our banking, stock trading, and insurance contracts, yet this data was collected and stored in hand ledgers. With the advent of digital technology in the 20th century, financial firms expanded exponentially. The key to this expansion has been relational databases, which enable us to store millions of detailed records about customers, products, and transactions.

This book contains Conceptual and Logical ‘starter’ data models for the three business areas of banking, stock trading or finance, and insurance. Banking Conceptual and Logical models here address checking, savings, mortgages/loans, and credit cards. A separate chapter addresses Customer and Product data models. Stock trading/finance models address investment product designs, including equity, bonds, options, and alternate investments. Subsequent sections of the book provide ‘starter’ models for insurance. Physical data modeling is addressed along with a discussion of Data Warehousing.

Whether you are a business specialist, analyst, regulator, or IT professional, this book provides a roadmap and set of patterns for the initial design and construction of fundamental data models for the most frequently used applications in the financial world.

About Claire Frankel

With a B.S. degree in Physics and Mathematics from SUNY Albany, Claire Frankel was hired by Digital Equipment Corporation (DEC). From DEC and a subsequent instrumentation engineering position with the Foxboro Company, she started her nuclear engineering IT position with Stone & Webster Engineering Corporation. After the Three Mile Island nuclear reactor incident, the Nuclear Regulatory Commission (NRC) issued its first directive to increase alarms and security in U.S. nuclear power plants. Ms. Frankel wrote the first Requirements Document in the U.S. based upon the NRC’s directive, and directed the installation of additional sensing devices at an Ohio nuclear reactor facility. A move to New York City precipitated a change in career to IT project management and then to a 40-year career in Data Modeling. Ms. Frankel has designed financial databases for NSCC, Goldman Sachs, Morgan Stanley, and JP Morgan Chase.

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