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Regulation Innovation SIG Demo Summaries

Below is a list of the solutions and use cases that have been proposed at Regulation Innovation SIG meetings.

If you presented at a Regulation Innovation SIG meeting and your demo is not included below, feel free to submit a PR to add it, and reach out to help@finos.org if you need assistance.

Morphir

Presented by Morgan Stanley at the November 24th 2020 Regulation Innovation SIG meeting

Overview

Morphir is a multi-language system built on a data format that captures an application’s domain model and business logic in a technology agnostic manner. Having all the business knowledge available as data allows you to process it programatically in various ways:

  • Translate it to move between languages and platforms effortlessly as technology evolves
  • Visualize it to turn black-box logic into insightful explanations for your business users
  • Share it across different departments or organizations for consistent interpretation
  • Store it to retrieve and explain earlier versions of the logic in seconds
  • and much more … Learn more at morphir.finos.org and check out the open source code at github.com/finos/morphir.

Opportunity for Open Source Collaboration

There are quite a few open-source and proprietary solutions that address the ontology (including rules and calculations) portion of this initiative. At their cores, they all function very similarly, though because they’ve evolved independently are not directly compatible. Most have advanced and mature features that we’d want to take advantage of. So rather than choosing one, we should aim to provide a standardized mechanism for interoperability that would allow us to take advantage of the full set of existing features while also enabling new tool developers to work efficiently on a common platform.

That’s where Morphir fits in; as that common structure (IR) that we can use to translate between the various solutions and focus new development on. There’s no shortage of options to try this on and ISDA and Regnosys being forward thinking and similarly aligned stepped up with a use case.

The first goal is to see how CDM/Rosetta concepts translate to Morphir. We’re looking at that by first writing a subset of CDM in Morphir by hand to serve as a template. With that established, we’ll look into automating the rest. We might want to look at translating Morphir back to Rosetta and use that round trip as a template for using Morphir as the lingua franca between the various solutions.

Another goal is to see how we would write the same regulations in more idiomatic Morphir in order to take advantage of the correctness guarantees, etc. That would allow us to study and compare the two approaches for managing complex regulations, especially with respect to correctness, transparency, and flexibility.

Rosetta CDM

Presented by Regnosys at the November 24th 2020 Regulation Innovation SIG meeting

Overview

Rosetta Core is a complete Software Development Kit (SDK or dev kit) for the Rosetta DSL. It consists of an integrated set of tools for adopting, editing and implementing any model built on the Rosetta DSL. The ISDA Common Domain Model (CDM) is the first live application of the Rosetta DSL and is currently provided as the underlying model in Rosetta Core.

This means that users of Rosetta Core do not need to start modelling “from scratch” and can leverage the existing ISDA CDM components. This also means that Rosetta Core provides an integrated set of tools for adopting, editing and implementing the ISDA CDM.

Opportunity for Open Source Collaboration

One of the applications of the Rosetta DSL is to facilitate the process of complying with, and supervising, financial regulation – in particular, the large body of data reporting obligations that industry participants are subject to.

The current industry processes to implement those rules are costly and inefficient. They involve translating pages of legal language, in which the rules are originally written, into business requirements which firms then have to code into their systems to support the regulatory data collection. This leads to a duplication of effort across a large number of industry participants and to inconsistencies in how each individual firm applies the rules, in turn generating data of poor quality and comparability for regulators.

By contrast, a domain-model for the business process or activity being regulated provides standardised, unambiguous definitions for business data at the source. In turn, these business data can be used as the basis for the reporting process, such that regulatory data become unambiguous views of the business data. The Rosetta DSL allows to express those reporting rules as functional components in the same language as the model of the business domain itself. Using code generators, those functional rules are then distributed as executable code, for all industry participants to use consistently in their compliance systems.

ISDA and REGnosys successfully collaborated in 2020 to demonstrate the applicability of these tools as part of G20 Techsprint. The winning solution in the Regulatory Reporting category demonstrating how the tooling could solve Derivatives reporting challenges through implementation of the MAS reporting rules.

RegExplorer

Presented by Deloitte at the November 24th 2020 Regulation Innovation SIG meeting

Orchestrate

Presented by ING at the December 8th 2020 Regulation Innovation SIG meeting

Overview

The potential of RegTech extends well beyond levels of compliance. Implemented correctly it can also become an embedded driver for transformation and a source of value creation.

Regulation matters, it affects every one of our employees, our customers and our shareholders. If we can therefore ‘make things better’ using ‘RegTech’ as a fundamental driver for change within our ‘digital’ or ‘agile’ transformation journeys then we believe that this will result in positive outcomes for financial institutions and for the industry at large.

At the heart of our ‘Orchestrate’ journey is a strong belief in ‘collaboration’, ‘trust’ and ‘innovation’. All efforts and successes to date have focused around these core tenets. Regulators do not set regulations with single institutions in mind, they set them for the industry – Our approach to ‘RegTech’ is therefore industry led.

We recognise the considerable complexities involved within the ‘Regulatory’ domain which is why we engage with the industry and domain experts, and work closely alongside global regulators to help us on our journey. Our relationships with global RegTech ecosystem enables enables us to rapidly evaluate the marketplace and opportunities effectively.

We remain emerging technology agnostic, however the thesis for ‘Orchestrate’ is built on containerization. Container Technology allows development to move fast and enables software to be deployed consistently at scale. Containers offer logical packaging and provide a clean separation of concerns for the new RegTech market place.

We are excited about the potential of this initiative as well as our vision for the Orchestrate platform.

Opportunity for Open Source Collaboration

Better outcomes through:

  • Connected Ecosystems: Providing the ability to test, validate and adopt emerging technologies together to solve real business challenges and reduce the barriers
  • RegTech App Store: A RegTech application store containing ‘Trusted and proven’ RegTechs that can be easily accessed on the desktop by all levels and delivering different levels of detail
  • Advanced Solutions: From oversight of a bank level dashboard to evidencing a case. This is through a platform that stiches together a variety of RegTech Solutions, relevant data can evidence and drive action

RegTech Taxonomy

Presented by Apiax at the December 8th 2020 Regulation Innovation SIG meeting

Overview

Apiax uses an internally developed RegTech taxonomy to create the vocabulary for regulatory rule execution. One main requirement for our solution was to support diverse vocabularies and rule interpretations of our partners and clients. Our approach is inspired by ideas in Semantic Web research and existing ontologies (FIBO and its OWL-based implementation), our goal is to create a taxonomy that is expressive and flexible enough to support our use cases, while being simple enough to not require a team of ontology experts for maintenance. We are currently looking into NLP methods how to semi-automatically populate our taxonomy and support the creation of rules from legal documents.

Opportunity for Open Source Collaboration

We see that open source and open data is an opportunity to increase interoperability of our and other RegTech solutions. We agree, as discussed in the group, that a common RegTech vocabulary (e.g. published as an open ontology) would simplify the integration with our clients and partners. We would propose to start with an analysis of a selection of regulations, implement a vocabulary/ontology for those and develop a proof of concept how such an ontology might be linked to proprietary solutions or other open ontologies like FIBO/FIRO, and how this helps in terms of interoperability.

In addition we think that an open RegTech text corpus and open RegTech language models would help to standardize further (semi-)automated text extraction approaches to populate ontologies or extract logic from regulatory documents.

Crypto Tech Sprint

Presented by AIR at the January 19th 2021 Regulation Innovation SIG meeting

Overview

Cryptocurrency has become a dominant payment method for CSAM, and in the past five years there has been proliferation in the creation of cryptocurrency paywalls to gain access to the material. Unlike cash, crypto is traceable, but traditional anti-money laundering technology and current law enforcement techniques are often ineffective in detecting and intercepting it. AIR held a virtual TechSprint in October 2020 to surface new models of traceability and explore technological solutions to combat and apprehend perpetrators of these heinous crimes.

Opportunity for Open Source Collaboration

The TechSprint brought together technologists and subject matter experts from regulatory agencies, fintechs and crypto firms, banks, consultancies and academia. Participants collaborated on a FINOS hosted GitHub repo to build solutions aimed at curtailing CSAM by detecting users through their cryptocurrency payment activities, without compromising the privacy and data security of innocent people. All the teams were invited to present their solutions to the senior leadership team at FinCEN.

Federated AML Knowledge Base

Presented by Tookitaki at the January 19th 2021 Regulation Innovation SIG meeting

Overview

Detection of financial crime has become extremely difficult due to massive digitalization and increased use of digital payment/transaction channels. As criminals are able to conduct transactions almost anonymously and at high speed, it is vital to keep AML investigators abreast of the latest techniques criminals and terrorists employ to launder money.

Tookitaki’s Federated AML Knowledgebase collates intelligence gathered from AML experts, regulators, financial institutions and industry partners from across the globe. The ready-to-use database is searchable and interactive to allow AML investigators and analysts to consult and conduct their research.

Tookitaki has classified the typologies according to the industry, business line and theme to aid accessibility. Privacy is protected at all times, removing a major concern preoccupying compliance officers over disclosure breaches of customers’ personal or commercial sensitive information. Tookitaki’s ‘Hub and Spoke model’ provides access to the latest and emerging money laundering patterns and scenarios across the globe, thereby scaling one financial institution to a community of financial institutions across stateliness and jurisdictions. As soon as a new money laundering typology is identified, Tookitaki technology provides regular updates for sharing across the user base of Tookitaki’s suite of AI-powered AML software to promote crime prevention. Users have the ability to ingest specific money laundering patterns and automatically create thousands of relevant risk indicators, when overlaid on their dataset. These risk indicators are then auto picked by pre-defined machine learning models to detect suspicious cases.

Opportunity for Open Source Collaboration

Federated AML knowledgebase can make a vital contribution to the banking system’s efforts to address the global scourge of money laundering. If it is to be successful, it needs to be a collective effort through centralized intelligence-gathering.

We are building the largest database of ready to use money laundering patterns which is powered by a community of AML experts. Tookitaki has created a user interface for the public, specifically AML practitioners and experts, to create machine-readable typologies with ease. The framework allows the public to share their vital information on financial crime patterns and techniques for the use of financial institutions, helping effectively safeguard financial systems and societies. Collaborators will have access to a growing library of AML patterns and scenarios and will have the ability to create private federated networks and define the AML industry’s federate learning standards and protocols.

AML

Presented by Matt van Buskirk (Hummingbird Regtech) at the January 19th 2021 Regulation Innovation SIG meeting

Regulatory Taxonomy and Ontology Development

Presented by James Nicholls (Braithwate) at the April 6th 2021 Regulation Innovation SIG meeting.

Watch James Nicholls and Sarah Sinclair's presentation at the May 4th 2021 Regulation Innovation SIG meeting.

Overview

With an ever increasing volume of regulation, manual processes for managing firms’ regulatory obligations no longer suffice, from a practical perspective and in the eyes of many supervisors. In response, the RegTech industry has developed dozens of tools to keep track of regulatory updates and provide firms with an electronic inventory of their obligations.

These tools largely follow a common approach:

  • gather content from regulators;
  • store it in a proprietary structured data format;
  • apply some degree of tagging to classify the regulatory obligations in the text (with or without the use of AI and ML);
  • present the content to users via a searchable interface.

While this structured, tool-based approach is vastly superior to the spreadsheets used by many firms, two key issues remain:

RegTech tools classify the regulatory text in an inconsistent manner and the RegTech vendor’s algorithm is largely proprietary and often black-box => this creates potential regulatory risk as Compliance professionals are often unsure what interpretation of the regulation is taking place in the tool; Firms deploy teams of legal, compliance and consultancy resource to codify the profile of their business (e.g. Products, Services, Customers, Jurisdictions etc.). This incurs high costs and produces inconsistent and duplicative outputs, as this is done ad-hoc each time a RegTech tool is implemented at a firm => this is wasteful and creates a risk of inconsistent interpretation across firms.

Opportunity for open source collaboration

The proposal is three-fold:

  1. A set of open-source taxonomies to categorise regulatory obligations;
  2. An open-source ontology to provide a semantic layer on top of the taxonomic concepts;
  3. An open-source standard [taxonomy] for profiling a financial services business.

By making these standards open source and creating a utility tools to deploy them, the industry will benefit from:

A significant reduction in wasted development effort; Improved transparency and lineage regarding the regulatory interpretation; Increased interoperability of RegTech solutions – enabling plug and play choices for firms and vendors.

Commercial enterprises may leverage these open standards to ensure that their solutions can improve firms’ compliance management with a greater level of integrity and efficiency.

These provide multiple opportunities to reduce cost and risk for firms, vendors and regulators – thereby improving the end-to-end ecosystem of regulatory change.