Revolutionizing Regulator-Institution Relationships: The Impact of Machine-Readable Regulations
As industries evolve with technology, the question arises: can machine-readable regulations truly enhance the relationship between regulators and institutions? This innovative approach has the potential to foster faster compliance, clearer expectations, and more efficient oversight.
Machine-Readable Regulations: The Future of Compliance
According to Emil Kongelys, CTO of Muinmos, a leading RegTech company, machine-readable regulations are set to revolutionize the compliance landscape. He states, “The days of interpretation will be over, and there will no longer be an ‘excuse’ for non-compliance.”
The Promise of API Integration
Kongelys advocates for a unified protocol that allows all regulators to expose their regulations similarly to an API integration. He describes this as “an FIX protocol for the regulators.” However, he notes a significant hurdle: most regulators currently lack the necessary IT infrastructure to implement such a project.
Trusting AI-Driven Compliance Systems
One pressing question is whether regulators are prepared to trust AI-driven compliance systems. Kongelys emphasizes the importance of explainability in the results generated by these systems. He states, “If the results can be explained 100%, regulators will have to trust the outcome.”
- Regulators face challenges from AI systems that operate on probabilities rather than certainties.
- Fuzzy logic may be used in screening processes, where matches are determined by percentages.
- AI can assist in detecting forged documents, requiring human review of probabilistic outcomes.
Real-Time Data Sharing and Accountability
Real-time data sharing holds the potential to redefine accountability in regulatory frameworks. Kongelys argues that while different regulators may have unique requirements, a common protocol can set clear expectations for accountability.
Reducing Reliance on Intermediaries
According to Alex Mercer, head of the Innovation Lab at Zeidler Group, machine-readable regulations could diminish reliance on intermediaries for compliance reporting. This shift could lead to:
- A significant reduction in errors.
- Enhanced conformity to the underlying rules.
Mercer identifies two main challenges to widespread adoption:
- Lack of clear standards for drafting machine-readable rules.
- The precision required in legal language, where even a comma can alter meanings.
The Future of AI in Regulatory Compliance
The exploratory phase for regulators in understanding AI-driven compliance systems is crucial. Mercer notes that while enthusiasm for AI tools is growing among regulators, there’s no definitive timeline for achieving trust in these technologies.
A Game Changer: The Role of Machine-Readable Rules
Madhu Nadig, co-founder of Flagright, believes that machine-readable rules could be transformative, leading to:
- Faster reporting.
- Real-time adaptations.
- Less manual oversight.
However, he points out ongoing challenges, such as a lack of standardization and outdated legacy systems that inhibit rapid integration.
The Importance of Data in Compliance
According to Darragh Hayes, CEO of LEI, the success of machine-readable regulations hinges on standardized and reliable data. He cites the Digital Operational Resilience Act (DORA) in the EU as an example where the Legal Entity Identifier (LEI) was proposed as a primary identifier.
Hayes warns that introducing multiple identifiers, such as the European Unique Identifier (EUID), complicates processes and may lead to inefficiencies in compliance efforts, potentially diluting the objectives of DORA.
He concludes, “For the regulator-institution relationship to work effectively, regulations must be compatible with suitable technology.”
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