Financial services companies are required by US authorities such as the FRB, SEC, and OCC to demonstrate that its risk governance framework takes laws, rules, and regulations (LRRs) into account. This monitoring aids in preserving a reliable and secure control environment that satisfies stricter regulations and the risk tolerance of the company.
But figuring out if banking rules apply to specific parts of a law can be a challenging and arbitrary procedure that requires professional judgment. Banks often rely on external vendors to assess LRRs and generic controls based on the bank's characteristics, such as being a Global Systemically Important Bank (GSIB) or offering specific products and services.
Additionally, LRRs are always evolving, much like other industry frameworks such as the National Institute of Standards and Technology (NIST), the Information Technology Infrastructure Library (ITIL), and the Control Objectives for Information and Related Technologies (COBIT).
To assist ensure that the organization's control environment is free of flaws, this continuous development calls for continual effort. Unfortunately, manually connecting LRRs to rules, standards, procedures, risk metrics, and controls is time-consuming and often results in delays. The organization's ability to demonstrate compliance with LRRs and regulatory expectations diverge as a result of this process.
For example, a bank might have a policy that mandates the protection of the personal data of its customers, and the standard might stipulate that this data must be encrypted. In that case, the procedure would outline the procedures to encrypt personal data, and the control would help ensure that it is encrypted. However, suppose the connections between LRRs and controls are not maintained promptly. In that case, the bank may not be able to demonstrate compliance with the encryption standard, putting them at risk of non-compliance.
The Watsonx Regulatory Compliance Platform minimizes manual labor for control owners, compliance, risk, and legal teams
IBM Watsonx can automate the identification of regulatory tasks and match legal and regulatory requirements to a risk governance framework. By analyzing governance documents and controls and linking them to pertinent LRRs, this solution makes it easier to verify compliance with existing duties. This solution greatly reduces the amount of human labor required to build and maintain LRR libraries for audit, compliance, risk, legal, IT, and business control owners.For example, Watson Discovery can actively search the internet for regulatory modifications for a certain group of LRRs to conduct an effect analysis. Watson Assistant can be used as an interactive Q&A tool to provide conversational answers to questions about the risk and control environment from regulators, auditors, and other parties. Large language models (LLM), which require little to no training, are being used more and more in risk and compliance programs.
LLMs contained in Watsonx supplement LRR and governance data to apply the various process, risk, and control taxonomies of the banks. A prompt uses a preprogrammed method to assess an obligation. To determine what applies, for example, each of the company's risk categories strategic, reputational, wholesale, interest rate, and liquidity risks would be analyzed. The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets.
The process is consistent and repeatable across regulations whether the content is publicly available, whether it is curated by the organization, or is available from third parties in an obligation's library. The mapping and coverage capabilities that are not unique to LRRs include IT and cybersecurity frameworks such as NIST, ITIL, COBIT, Cloud Security Alliance Control Matrix, Federal Financial Institutions Examination Council (FFIEC), and others.
For instance, if a bank wants to ensure compliance with the NIST cybersecurity framework, the solution might connect the relevant LRRs to the relevant NIST controls. This provides a comprehensive and unambiguous view of the bank's cybersecurity posture.
Watsonx.ai by IBM
How risk management is accelerated by the Watsonx Regulatory Compliance Platform
IBM Watsonx.ai, Watsonx.gov, and Watsonx.data are the platform's sophisticated artificial intelligence (AI) modules, which offer a range of state-of-the-art technical features catered to the specific needs of the industry. These components are built on IBM's state-of-the-art AI technology and may be deployed in any cloud or on-premises.Through the IBM Watsonx.ai platform, users can take part in the training, validation, tweaking, and deployment phases of generative AI (gen AI) solutions. By enabling the creation of additional language models using foundation models from IBM and other sources, Watsonx.ai enables a wide range of natural and programming language use cases.
The platform comes with the state-of-the-art Prompt Lab tool, designed specifically to speed up prompt engineering processes. Customers may confidently begin their regulatory and compliance initiatives quickly by using pre-written sample prompts. Successful prompts can be saved as reusable resources or notebook entries.
It's interesting to note that the prompt words, model references, and prompt engineering settings are all meticulously formatted as Python code inside notebooks, allowing for seamless programmable interaction. The Tuning Studio feature of IBM Watsonx.ai also allows users to iteratively guide foundation models toward outputs that better suit their specific requirements.
With the help of Watsonx.governance's extensive toolkit, clients can easily create accountable, transparent, and explicable AI processes that work with both generative and machine learning models. When implemented, watsonx.governance integrates OpenPages' Model Risk Governance capabilities with Watson OpenScale's and AI factsheets' features into a single service.
Additionally, Watsonx.governance adds generative AI assets to its governance functions. This platform allows users to assess foundation model prompts and machine learning models, create AI use cases for the systematic tracking of solutions addressing pertinent business issues, and create processes while closely observing lifecycle activities.
Scalable analytics and artificial intelligence projects are made possible by IBM Watsonx.data, which supports data from several sources and eliminates the need for transfer or cataloging through open standards. This approach permits centralized access and sharing while minimizing data duplication and extract, transform, and load (ETL) procedures. Integrated vectorized embedding capabilities facilitate data preparation for various applications, such as retrieval augmented generation (RAG) and other machine learning and generative AI use cases.
Gen AI-powered conversational interfaces facilitate data exploration, augmentation, and visualization without requiring SQL expertise. A seamless interface with existing databases, tools, and data stacks guarantees interoperability.
All things considered, employing Watsonx for regulatory compliance offers a ground-breaking approach to managing risk and AI initiatives in an open and responsible manner. By leveraging its entire spectrum of capabilities, organizations may effortlessly manage the complexities of regulatory obligations. This facilitates ensuring ethical AI practices across the board, from model training to data management. IBM Watsonx.ai facilitates regulatory compliance while encouraging innovation and confidence in AI-driven solutions by empowering users to confidently assess, monitor, and enhance AI workflows.
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