Understanding the Financial Industry Through Linguistics

How Applied Linguistics Can Prevent Financial Crisis

Richard C. Robinson

• Editorial: Business Expert Press
• Año: 2021
• ISBN:
  9781637420591
• Categoría: Business
• Categoría: Finanza

This book is an essential read for any professional dealing with data and information challenges.

Imagine a collection of villages all beset upon by monsters. One village defeats their monsters using silver bullets. They convince all surrounding villages that their solution should be the only standard. The next village uses silver bullets to repel the monsters but fail! Why? Because the first village was fighting werewolves, the second village was fighting vampires.

This is our data challenge–recognizing not all problems are the same - and there are no single silver bullet solutions. There are many communities within financial services, each with nuanced needs that require slightly different solutions to address what may look like the same problem.

The financial services industry is unique for being based upon information and communication. It is the failure in understanding that multiple existing financial languages exist and pursuing interoperability that sits at the crux of financial crisis – not the lack of a single unified financial language. This book is an essential read for any professional dealing with data and information challenges.

The author presents a new, unique approach to broad industry issues, leveraging applied linguistics and discusses how to break barriers that exist between language and data; the aim to make it easier for the financial industry (including regulators) to communicate - for the benefit of all investors. Unconventional in the cross-disciplinary pairing of applied linguistics and financial services, it is practical and intuitive in pursuing solutions. While focused on financial services, the approach is relevant for other industries that have similar challenges.

CHAPTER 1

Introduction

A (Very) Brief History of Financial Services

While financial services would seem to have been around forever, modern banking systems were only established in the late 17th century, with international finance getting off the ground in the early 19th century. These new systems were based upon the practice of trade, lending, and commerce that had been around since before ancient Greece, typically linked to societies that had developed an agricultural base.

Historically, farmers and traders required funds in order to travel and carry their goods from field to market in different cities. Merchant lenders would give loans based on the grain and other commodities, and thus, enabled the expansion of such trade. Alternatively, loans would be comprised of seed, with repayment made from the profits of the resulting harvest.

Originally, trade occurred primarily on barter type systems (such as cattle and grain), with particular raw materials such as obsidian, becoming more central as trade expanded. As trade centers grew into population centers and cities, formal locations, typically based in temples or palaces, became centers for banking type commerce. Deposits could be made, and lending activities more centralized—as well as rules around the interest rates that could be charged. In Babylon, the Law of Hammurabi established formal laws, akin to similar rates and policies that had been developed in India under the Laws of Manu. Interestingly, both allowed charging of interest rates in the 20 to 30 percent range, according to clay tablets and other recording devices uncovered by archeologists.

Across different economies, rates would fluctuate in line with the prosperity (or not) of the society. In times of crisis, rates would rise, and would decline when times improved. One of the earliest debt crises occurred in Athens, resulting in reforms using the Laws of Solon. Prior to these reforms, debtors would become slaves, and during the crisis, the economy began to spiral. One of the most significant acts was to forgive all the debt, free all the debt-slaves, and forbid the future use of one’s person as collateral for loan.

During this time, empires began to establish taxes to fund their growth. As sophistication grew, coins came into play, firstly hewn as lumps from items with inherent value such as copper, obsidian, gold, and silver. Eventually, empires and merchant centers would formalize these into coins, with stamps of gods, emperors, or the merchant’s seal for authenticity. This further enabled an economic system of lending, as coins could be hoarded and stored more permanently than grain or livestock, as well as relent to others. Systems of exchange would be created based on the knowledge of the stamped minter and the value was tied to it in relation to its intrinsic value, as compared to the intrinsic value of something from a different mint. Interestingly, the Inca empire appears to be the only one to never establish a monetary system; all needs were met by the ruling system, based on the exchange of services in a communal work system known as mink’a.

Through Roman times, various empires would revise and evolve rules. In China, early banknotes would be created using leather squares, and later was home to the first known use of paper currency. Jewish, Christian, and Islam religions, all released interpretations condemning and prohibiting the use of interest, and soon after came ways of going around those prohibitions. Banking in the western world mainly ceased after the fall of Rome and the subsequent rise of religions and their restrictions. The exception was among Jews who were allowed to charge interest on loans to those not of the Jewish faith. Christians would take out those loans, and by paying interest, not charging it, the rules of both faiths were satisfied.

By the 11th century, legal fictions and other means were in common use to get around the ban against usury. The advent of the Crusades, and the need to fund these expensive campaigns was a major cause for the re-emergence of banking. Monarchs looked to tax trade to raise money for the Crusades and other empire building efforts, while religions looked to impose rules to control trade. Merchant banks in Italy, exemplified by the Medici Bank, began to flourish. These early merchant banks began nearly where the original seed lenders began—enabling funding of crops and trade. Banking systems formalized lending systems for borrowing money, to finance long trade journeys, or provide financing to merchants and farmers. Insurance also came into play, helping farmers or merchants in cases of crop failure.

Governments and other organizations continued to create new products and services for customers, with the goal of creating investment in projects and businesses as the driver of their business models. Enabling banking within their countries or empires enabled trade with other countries and empires, and thus expanding their economies. As these systems matured, and expanded with colonialism, they also dealt with emerging regulation.

Investments were created to fund exploration and expansion in colonies and the New World. Companies were formed with the concept of private stock given to investors. These companies had a single purposes of discovery or trade, and upon completion of the mission, they would be dissolved and the money paid back to the investors—the stock holders. All the while, the data captured was mostly the recording of general accounting information. The data was confined and limited to the investor group, any banks or governments involved, and those executing the mission. Double sided accounting was in full use, and the ledgers were the central storage of record. Paper certificates, like bank notes, were given to investors or lenders as their record. Indeed, modern banking deposit systems evolved out of the Italian systems, which were developed to help avoid the frequent handling of cash. These private company arrangements simply took this concept one step further. The creation of the Dutch East India Company and the British East India Company caused this model to change again. Not only were stocks offered to anyone (as opposed to only a private few), via the newly created Amsterdam Stock Exchange, but the company was envisioned to continue to live on. Instead of just one ship and voyage, the company would fund multiple ships and voyages. This raised the likelihood of success, as well as creating profit for everyone, which could then be used to fund future ships and voyages.

This was not the whole of banking, as all the previous activities continued. Governments, emperors, and monarchs, all required money to wage wars and encourage trade, as well as to continue to live in style. (Spain would overborrow while trying to defend its dominance of the seas and colonies in the 16th to beginning of 17th century, the country would actually become bankrupt four times under Philip II and III up through 1607, and another five times under future rulers through 1666). Local merchants still required loans for expansion, or to cover materials and expenses. Governments continued to enact laws that limited certain practices that, much like the Laws of Hammurabi, Manu, and Solon, created rules on chartering, rates, and lending. Throughout this time, goldsmiths would store wealthy merchants’ gold, and then in turn would lend money by issuing paper certificates. These would eventually become banknotes. A number of other advances occurred, from publications like Adam Smith’s “An Inquiry in the Nature and Causes of the Wealth of Nations” in 1776, to the establishment of Central Banks such as the Bank of England. These were a means of managing monetary policy, interest rates, and overall money supply for a formal state or nation and were typically chartered by the government as a monopoly.

The variety of investments available, and types of trade, accelerated in the 20th century, leading to a proliferation of data being created for many different purposes. Until the mid to late 1900s, the main levers of economies focused around debt, currency strength, reserves, and the type of financial products easily relatable to the early days of ancient seed and livestock lenders. However, the 1960s saw the creation of new types of financial products not directly related to any actual activity— the repackaged loan that was offered to a new secondary marketplace. Essentially, a bank would make a loan, but it would not itself then hold on to the loan. It would repackage and sell the loan to an investor.¹ Still, there were no insights around the differences between very similar products and different kinds of loans.

During this time, banking and the financial systems were viewed mainly from an accounting, macroeconomic, and microeconomic viewpoint. In that way, any data recorded and collected was (and in many ways continues to be) in that vein, for those uses. The advent of computing enabled some data capture, but until storage and processing power limitations were made more trivial (arguably somewhere between mid 1990s and early 2000s), data was not particularly accessible. The recording of data was focused on accurate books and ledgers, as opposed to the trends. This changed in the 1990s, with the greater computer power and storage. This allowed for the growth of analytics, from a programming point of view and created an explosion of data as the Internet Age came to life. The introduction of alternative and nontraditional financial data into decision making shifted financial data from something to be simply recorded to more of an asset in and of itself.

To most people today (circa 2020), the rhetoric of Wall Street versus Main Street encompasses the entirety of what is considered to be the financial services industry. Movies, from the seminal Wall Street to Boiler Room and The Big Short—while accurate—have shaped perceptions into ones that ignore most of the hidden iceberg that actually exists. Additionally, while there may be a recognition of the complexity of the business, there is still a misperception that it could easily be made simpler and easier to understand and control through some basic changes. While I agree there are things to be done, and need to be done, I am trying to avoid direct answers and instead wish to provide a better foundation of understanding so that such decisions can be better informed—for policymakers, industry members, as well as the layman.

Here Comes Data (and Standards)

Until relatively recently, the focus on data (which I include information as part of) was purely a store-and-retrieve function. Relational databases came into use as a response to needing to organize rapidly growing (in size and variety) and changing data. Data was captured as it was, and depending on where it came from, often without much thought to its need or use outside the immediate function in which it resided.

In trying to deal with this complexity in process and data, there is a natural resulting drive toward creating and utilizing standards to enforce some sense or baseline for common understanding. In manufacturing, the Industrial Revolution was fueled by standards in interchangeable parts. Disciplines like engineering demanded clear standards for tools and machinery to work properly. In the information age, data is viewed as the nuts and bolts, the interchangeable parts, required to drive the information economy. It would make sense, then, to explore standardization of data, and the systems and processes that use data.

With the increased scrutiny of data from every perspective, whether the media, regulators, or clients, the ability to get a handle on the information and drive standards that can be embraced by all has become both increasingly important and difficult. As we try to bring the same data from multiple, different sources together to get a single, unified view, it has begun to be a question if that similar seeming data really is the same. The advent of modern data management (and the Chief Data Officer) brought new scrutiny on data, and by association, standards. Suddenly, new questions were being asked. How do we create data, understand its context and lineage, and ultimate meaning? How do we share data and communicate effectively, yet ensure we have common understanding and agreement? Many point to standards to solve a bulk of these problems, but this simply shifts the problem. Who is creating the standards? Does the resulting standard reflect the understanding of the group it was intended for? Can it work for a group it was not intended for? Doesn’t the virtue of something being a standard mean that it should apply to everyone, regardless of what they are doing?

Further, there is a standing debate on the impact of standardization on innovation and flexibility. I hope to help inform this discussion. There is a nuance that tends to be forgotten, or not understood, when this debate is had at an aggregate level. Again, our hidden iceberg shows itself here. There are multiple standards organizations that may or may not work well together, and have varying level of prestige and power among policy makers that may differ from user perceptions.

Standards work tends to be an esoteric exercise that is somewhat opaque to the everyday user. However, it influences data, perception, and interpretation in ways that may not have been intended. There are often disconnects between the standards community and the communities their work influences—usually not through any fault or intention—but that aspect cannot be ignored. These disconnects have an impact on essential data that is relied upon by the industry and those that regulate or follow it.

Data pulled from one source typically carries some inherent bias, inferred meaning, or other context that makes it different from seemingly like data from a different source. Data are like words in a language. And like words in a language, without the included context of its source, its community, words (i.e., data and standards) can be misinterpreted. This has an impact on standards—both in the creation of standards, as well as their use and implementation.

For example, the word jumper in Queen’s English means sweater, which is a far cry from American English, where (depending on region) the same word will usually be interpreted as a person physically jumping or the cords needed for charging a dead car battery. Different communities—even if they have a common base for their language—will continuously evolve and diverge from each other in use and meaning. In the same way, data and how it is defined will evolve and diverge in different communities, even if they interact with each other.

Over the past 50 years, technology has rapidly evolved and changed. Approaches on how to store and classify even the simplest data point, such as a date, have multiple standard methods. Changes and differences vary due to influences as diverse as technology or culture, but continue to evolve. This is due to new abilities and understanding in technology and data, as well as how globalization and culture change how certain data is viewed.

The tech craze and the hot tools of the month continue to confuse the average business professional in finding the best way to focus on their data. In The History of Databases, it is said “The history of databases is a tale of experts at different times attempting to make sense of complexity.” ² We have gone from punch cards and flat file data storage, to hierarchical and network modeled database management systems (DMBS), to the relational database. How we structured and stored data is what drove us how to define it—and we are now in another revolution as relational databases are rejected and redefined with the advent of NoSQL and NewSQL. Yet, all of this tends to come from the technical disciplines. Data practitioners are familiar with words like ontologies and semantics, but many do not appreciate that these concepts have existed for decades (and sometimes centuries!) within the discipline of linguistics. Further, technologists generally do not have formal native training in linguistics an...

Índice

• Cover
• Half-Title Page
• Title Page
• Copyright
• Dedication
• Description
• Contents
• Foreword
• Acknowledgments
• Chapter 1 Introduction
• Chapter 2 Defining Financial Services: Roles and Interactions
• Chapter 3 An Introduction to Applied Linguistics
• Chapter 4 Intermission
• Chapter 5 Firm Type: Perspectives, Roles, and Languages
• Chapter 6 Front/Middle/Back Office/Enterprise (Silo Versus Cross-Silo)
• Chapter 7 Asset Class CoPs
• Chapter 8 The Investment Roadmap
• Chapter 9 Cross Border and Domestic Communities
• Chapter 10 Standards: Background
• Chapter 11 Standards in 2020 Financial Services
• Chapter 12 The Regulatory Community
• Chapter 13 Applying Communities of Practice
• Chapter 14 The Modest Proposal
• Appendix A
• References
• About the Author
• Index
• Backcover