Insurance Technology Handbook

Jessica Keyes

• Publisher: CRC Press
• Year: 2018
• eBook ISBN: 9781351090643
• Topic: Informatik
• Subtopic: Informationstechnologie

This desk reference for IT professionals in the insurance industry provides information about the latest technologies to improve efficiency and prediction.
Topics include:

imaging

modeling

management systems

customer systems

Internet commerce

Issues affecting all financial service sectors, such as the year 2000 problem
The Insurance Technology Handbook is geared toward all levels of technology management and financial services management responsible for developing and implementing cutting-edge technology.

Section II
Technology Trends in Financial Services

In spite of the rapid pace of change, there are some things that must stay the same. One of these is the stringent standards of developing systems within the financial services community.

It might be because it’s so heavily regulated, or maybe it’s because the technologists that are attracted to it are so darn good, but the systems developed by financial services companies are some of the best in the world. Although quite complex (just try to figure out how to program a hedge fund), accountability and auditability are routinely programmed into financial services systems.

When I began working at the New York Stock Exchange in the early 1980s it was not uncommon to find extensive R&D technology departments up and down Wall Street. Here, the best and the brightest were experimenting with the tools that are routinely being used today. Using Dragon’s Naturally Speaking on your PC? Well back in the very early 1980s the Exchange was already experimenting with voice recognition on the Floor. Using Natural Language to structure a query to a database? Back in the early 1980s RAMIS, a 4GL, had a Natural Language interface that was routinely being used by regulators at the Exchange.

But these were primitive first implementations of technologies that have since grown up. As Henry Seiler explains in Chapter 12, business rules represent the codified policies and decision-making practices of an organization. Historically, business rules have been coded directly in the program logic of an application. Today, the terms business rules and knowledge management are used to describe the isolation of business policies and decisions from application logic. That the financial services community has endorsed the concept of codifying business rules is very much in evidence in Chapter 14. Here you’ll find out how the avant-garde of the industry created systems, known as expert systems, that were the precursors of most of the intelligent systems used on the Street today.

These systems permit those in banking, insurance, and securities to access such things as customer profiling, geographic information systems, personal financial appliances, and even computer systems that can build themselves. All of these topics are covered in this section.

Even though we’re moving squarely into the realm of Web-based interfaces to corporate information systems, these systems need to exhibit the same high standard of quality as conventionally developed systems. That’s something that most folks forget in this era of visual and easy-to-use development tools. Towards that end I’ve included a rather lengthy chapter on total quality (Chapter 6) that covers everything from the meaning of quality, to Deming’s 14 quality points, to a ton of techniques and formulas that you can use to improve both quality and productivity in your own shop.

Jody Lyon in Chapter 13 asserts that in order to stay ahead financial services companies are turning to decision support solutions to help identify and manage their customer relationships. Solutions such as data warehouses or data marts provide a solid foundation of accurate information upon which they can base their decisions. Accuracy is one of the biggest obstacles blocking the success of many data warehousing projects, hence Chapters 6 and 13 are “must-reads.”

Even if you’re using a Total Quality approach to system development it doesn’t mean that your systems are error free or even functioning properly. In this section I take the opportunity to promote one of the most novel methodologies to come along in a long time. “Development Before the Fact,” discussed at length in Chapter 24, is a radical departure from any of the techniques that have come before it. Born of the Apollo and Skylab missions where software is man-rated (meaning that its failure can cause human harm or even death), the “Development Before the Fact” methodology, in this era of distributed integration of systems, is something that financial services managers will be intrigued with.

Finally, given the preponderance of financial services companies that have moved onto the Web it’s wise to find out what’s legal and what’s not. Frederic M. Wilf, Esq., has graciously provided us with thousands of dollars worth of free legal advice (Chapter 26) — advice that every manager needs to take before embarking on a Web development project.

J. Keyes

Chapter 6
The “Must-Have” Guide to Total Quality for the Financial Services Manager
Jessica Keyes

In tracy kidder’s landmark book Soul of a New Machine, he details the riveting story of a project conducted at breakneck speed, and under incredible pressure. Driven by pure adrenaline, the team members soon became obsessed with trying to achieve the impossible. For more than a year, they gave up their nights and weekends — in the end logging nearly 100 hours a week each! Somewhere buried in the midst of Kidder’s prose we find that at the end of this project the entire staff quit. Not just one or two of them, but every single one!

The Financial Services field is rife with stories such as this one. Software development projects are usually complex and often mission-critical. As a result the pressure on staff to produce is great. And sometimes, as in the Kidder example, even with success comes failure.

Successful software development projects (i.e., get the product done on time — and not lose staff members) have something in common. Each of these projects, in some way, shape, or form, followed one or more principles of quality and productivity. Some of these principles are clearly intuitive. But most are learned or culled from vast experience over a number of years and projects.

In today’s competitive environment, Information Technology (IT) is a major partner with the business units. And because of this the push is on for enhanced software productivity and quality. In addition, the Y2K, Dow 1000, and Eurodollar crises has put a renewed emphasis on quality and productivity — often with the legal department looking over IT’s shoulder. Let’s face it, intuition just won’t cut the mustard any longer. Nor can an organization wait until software developers learn their quality lessons over so many projects in as many years.

This chapter has condensed several decades worth of quality studies into a few brief pages. Here you’ll find everything from formulas to measure productivity to measures to take to enforce stringent quality goals. Putting some of these guidelines and techniques into your bag of tricks will improve not only the quality of your software, the productivity of your staff, but the company’s bottom well too.

The Meaning of Quality

Although quality and productivity are foremost on the minds of management, few truly understand how to correlate the tenets of quality to the process of information technology.

Total Quality Management, or TQM as it has come to be known, was actually born as a result of a loss of competitive edge to countries such as Japan. In fact, the father of TQM, W. E. Deming, finding no forum for his radical new ideas on quality in the U.S., found eager listeners in Japan. Today, Deming’s 14 points on quality, listed in the next section, are considered the basis for all work on quality in this country as well as Japan.

But Deming’s studies were only the start of a flood of research in the field. For example, Y. K. Shetty, a professor of management at Utah State University’s College of Business and the co-editor of The Quest for Competitiveness (Quorum Books, 1991), suggests that even though most corporate executives believe that quality and productivity are the most critical issues facing American business, many do not know how to achieve it. Shetty lists 16 organizations that have vigorously attacked this challenge: Catepillar, Dana Corp., Delta, Dow Chemical, General Electric, Hewlett-Packard, IBM, Intel, Johnson & Johnson, Marriott, Maytag, McDonald’s, Procter and Gamble, Texas Instruments, 3M, and Xerox.

What Shetty found was that these organizations shared some characteristics in common. He refers to these as the Seven Principles of Quality.¹

Principle 1 — Quality improvement requires the firm commitment of top management. All top management, including the CEO, must be personally committed to quality. The keyword here is personally. Many CEOs pay only lip service to this particular edit. Therefore, top management must be consistent and reflect its commitment through the company’s philosophy, goals, policies, priorities, and executive behavior. Steps management can take to accomplish this end include: establish and communicate a clear vision of corporate philosophy, principles, and objectives relevant to product and service quality; channel resources toward these objectives and define roles and responsibilities in this endeavor; invest time to learn about quality issues and monitor the progress of any initiatives; encourage communication between management and employees, among departments, and among various units of the firm and customers; and be a good role model in communication and action.

Principle 2 — Quality is a strategic issue. It must be a part of a company’s goals and strategies and be consistent with and reinforce a company’s other strategic objectives. It must also be integrated into budgets and plans and be a corporate mission with planned goals and strategies. Finally, quality should be at the heart of every action.

Principle 3 — Employees are the key to consistent quality. The organization must have a people-oriented philosophy. Poorly managed people convey their disdain for quality and service when they work. It is important to pay special attention to employee recruitment, selection, and socialization and to reinforce the socialization and quality process with continuous training and education. It is also a good idea to incorporate quality into performance appraisal and reward systems and to encourage employee participation and involvement. Effective communication throughout the department, between department, and throughout the organization is required to reinforce the deep commitment of management and creates an awareness and understanding of the role of quality and customer service.

Principle 4 — Quality standards and measurements must be customer driven. It can be measured by:

• Formal customer surveys
• Focus groups
• Customer complaints
• Quality audits
• Testing panels
• Statistical quality controls
• Interaction with customers

Principle 5 — Many programs and techniques can be used to improve quality, such as:

• Statistical quality control
• Quality circles
• Suggestion systems
• Quality-of-work-life projects
• Competitive benchmarking

Principle 6 — All company activities have potential for improving product quality; therefore teamwork is vital. Quality improvement requires close cooperation between managers and employees and among departments. Total quality management involves preventing errors at the point where work is performed, and ultimately every employee and department is responsible for quality.

Principle 7 — Quality is a never-ending process.

• Quality must be planned
• Quality must be organized
• Quality must be monitored
• Quality must be continuously revitalized

Tqm Methodologies

Since early TQM programs were largely manufacturing oriented, IT researchers, academicians, and consulting firms were required to interpret and extrapolate TQM tenets and create quality paradigms that could be used to significant advantage. As a result, there is no single TQM methodology in use today that has garnered wholesale industry acceptance. All of these methodologies, however, are based on TQM tenets and all, if used properly, will provide organizations with a clear path towards better quality in their systems.

Be warned though, one size does not fit all. In a report by the New York City think tank, American Quality Foundation, the notion was challenged that quality programs were universally beneficial for all organizations. Based on a study of 584 firms in North America, Japan, and Germany, the report noted that TQM practices are not generic. What works for some organizations may well turn out to be detrimental to the performance of others.

The Problem with Quality

Information technologists have long realized that there was som...

Table of contents

• Cover
• Title Page
• Copyright Page
• Contents
• PREFACE
• SECTION I INSURANCE TRENDS IN TECHNOLOGY
• SECTION II TECHNOLOGY TRENDS IN FINANCIAL SERVICES
• SECTION III Appendix
• Selected Products Briefs
• ABOUT THE EDITOR
• INDEX