Principle 1: Model Identification and Model Risk Classification – Enhancing Model Risk Management for UK Banks in Alignment with SS1/23


The use of models has become an integral part of decision-making processes within banks. However, with the increasing complexity and interconnectedness of financial systems, the Bank of England’s Prudential Regulation Authority (PRA) has recognized the need for effective model risk management (MRM) practices. The first principle outlined in the PRA’s Supervisory Statement (SS) 1/23 focuses on model identification and model risk classification. This blog post delves into the significance of this principle for banks in the United Kingdom, its dependencies, and the expectations placed on financial institutions to comply with this principle.

Understanding Model Identification and Model Risk Classification

Model identification refers to the process of accurately identifying and recognizing the various models employed within a bank’s operations. Models can range from simple spreadsheets to complex algorithms, and their identification is essential for managing associated risks effectively. Model risk classification involves categorizing models based on their purpose, complexity, and potential impact on the bank’s decision-making processes and financial stability.

Importance for Banks in the United Kingdom

Banks in the United Kingdom operate within a regulated environment overseen by the PRA. Adhering to the model identification and risk classification principle is crucial for these institutions due to several reasons:

  1. Enhanced Risk Management: Identifying and classifying models enables banks to understand the potential risks associated with their use. This knowledge is critical for developing appropriate risk management strategies and controls.
  2. Regulatory Compliance: Complying with the PRA’s principles is a requirement for regulated UK-incorporated banks, building societies, and PRA-designated investment firms. By aligning with the SS1/23, banks can demonstrate their commitment to robust risk management practices.
  3. Strengthened Decision-Making: Accurate model identification and classification allow banks to assess the strengths and limitations of each model. This knowledge empowers decision-makers to make informed judgments and allocate resources effectively.

Expectations for Compliance

To ensure effective model identification and model risk classification, financial institutions are expected to undertake the following actions:

  1. Comprehensive Documentation: Banks should maintain detailed documentation of all models used, including their purpose, underlying assumptions, limitations, and key inputs. This documentation facilitates better understanding and risk assessment.
  2. Inventory Management: Establishing a centralized inventory of models enables banks to have a holistic view of their model landscape. This inventory should capture essential details such as model owners, dependencies, and associated risks.
  3. Risk Classification Framework: Implementing a robust risk classification framework ensures consistent and standardized categorization of models. The framework should consider factors such as model complexity, potential impact on decision-making, and regulatory requirements.
  4. Resource Allocation: Banks must allocate appropriate resources, including personnel and technology, to manage and mitigate the risks associated with different models. Adequate resourcing supports effective risk oversight and control mechanisms.
  5. Ongoing Monitoring and Review: Regular monitoring and periodic reviews of models are essential. Banks should proactively assess model performance, identify changes in business environment, and adapt to evolving regulatory requirements. This process helps maintain model accuracy and effectiveness.

Benefits and Challenges

Complying with the model identification and model risk classification principle offers numerous benefits to banks:

  1. Improved Risk Governance: Accurate model identification and risk classification promote a robust risk governance framework. This framework ensures accountability, transparency, and oversight of models, leading to better risk management practices.
  2. Informed Decision-Making: Understanding the strengths and limitations of models facilitates informed decision-making across various business functions. It enables banks to assess potential risks accurately, supporting prudent risk-taking and strategic planning.
  3. Regulatory Alignment: Compliance with the PRA’s expectations enhances banks’ regulatory standing and demonstrates adherence to best practices in MRM instills confidence in regulators, investors, and stakeholders.

However, challenges may arise during the implementation process:

  1. Model Proliferation: Banks often employ a wide array of models, making their identification and risk classification a complex task. Proper coordination and documentation are necessary to manage a large number of models effectively.
  2. Data Availability and Quality: Model identification and risk classification heavily rely on accurate and reliable data. Banks need robust data management systems and processes to ensure data availability, quality, and integrity.
  3. Resource Constraints: Establishing and maintaining an effective model identification and risk classification framework requires dedicated resources. Banks must allocate sufficient budget, personnel, and technological infrastructure to support these initiatives.


Principle 1 of the Bank of England’s SS1/23 highlights the importance of model identification and model risk classification for banks in the United Kingdom. By complying with this principle, financial institutions can enhance their risk management practices, make informed decisions, and meet regulatory requirements. Accurate model identification and risk classification provide a foundation for effective risk oversight, transparency, and robust governance. While challenges may arise during implementation, the benefits of aligning with this principle far outweigh the obstacles, leading to stronger model risk management across the banking sector.

How We Can Help

Model Risk Management on Connected Risk is a robust platform that allows you to manage and meet all of the obligations set within SS1/23 from the PRA. If you’re looking to meet regulatory requirements and obligations, our solution is the standard for your financial institution. Get started today using the form below, or learn more on our SS1/23 information page.

Like this article?

Share on Facebook
Share on LinkedIn
Share on XING

Talk to an Expert

"*" indicates required fields

Are you looking for support?

If you're looking for product support, please login to our support center by clicking here.

First, what's your name?*
This field is for validation purposes and should be left unchanged.

Submit a Pricing Request

"*" indicates required fields

First, what's your name?*
This field is for validation purposes and should be left unchanged.

Submit an RFP Request

"*" indicates required fields

First, what's your name?*
Which solution does your RFP require a response on?*
Drop files here or
Accepted file types: pdf, doc, docx, Max. file size: 1 MB, Max. files: 4.
    This field is for validation purposes and should be left unchanged.

    GDPR Cookie Consent with Real Cookie Banner Skip to content