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Recasting Financial Services in the Era of Web 3.0 | by ANDREW NOBLE | Nov, 2020

Recasting Financial Services in the Era of Web 3.0

The financial services space is a labyrinth of arcane terminology used to describe the moving parts of a system that impacts all of us everyday.

In this labyrinth, traders and merchants use accounting tools and techniques to track their activities. Computers have proven to be extremely useful for aiding in this task.

Government regulators provide rules of engagement for a web of economic actors. The economic performance information captured by these actors allows them to secure debt and equity as well as report to regulators.

The whole system is lubricated with money supplied by banks and rolls on a creaky Web 2.0 software framework. Now that’s all changing as we transition to Web 3.0.

The Web 3.0 paradigm brings a veritable brew of new tools and techniques to make for a potentially, very powerful new financial services technology platform.

The features of this new Web 3.0 financial platform that makes it so powerful is that it’s not underpinned by any one proprietary technology or standard. Rather, it’s a robust mix of open-source standards and technologies with a focus on reusable logic.

Common logic is intended to facilitate the exchange and transmission of knowledge in computer-based systems.

Common technology standards and common logic go hand in hand. Especially when machines are ready to reason.

Machine-reasoning about financial activity is an emerging computer sciences domain where much of the groundwork was laid at the beginning of the Ai revolution with the development of expert systems. While this approach fell out of favour, research and development never stopped and today we are the beneficiaries of some powerful, open-source logic technologies like Prolog.

The goal of the Semantic Web is to make Internet data machine-readable. Synthetic reasoning requires machine-readable data and so we have a match made in heaven.

XML, RDF & XBRL are all open-source approaches to making machine-readable smart data. XBRL is a special flavour made specifically for tracking financial activities.

The Standard Business Reporting Model provides machine-readable semantics for expressing the business reporting domain. The model is built on a solid theoretical foundation — an open-source framework for implementing digital financial reporting.

EngineB open-sourced their Common Data Model for enterprises. This is really an extension of the Standard Business Reporting Model and provides more granularity.

Where there is financial data there is a need for proof that the financial data represents real-world economic events. Proof of events can be captured in digital handshakes between people and people, people and machines and machines and machines.

Encryption and blockchain technologies offer decentralised, trustless storage systems for privately recording economic events that impact the enterprise.

WEB 3.0 is going to deliver a financial system that is scalable, robust, redundant and intelligent.