Governance Model

Governance frameworks are the structure of a government and reflect the interrelated relationships, factors, and other influences upon the institution. Governance structure is often used interchangeably with governance framework as they both refer to the structure of the governance of the organization. Governance frameworks structure and delineate power and the governing or management roles in an organization. They also set rules, procedures, and other informational guidelines. In addition, governance frameworks define, guide, and provide for enforcement of these processes. These frameworks are shaped by the goals, strategic mandates, financial incentives, and established power structures and processes of the organization.

Governance frameworks establish and perpetuate the efficiency or lack of efficiency in an organization or institution’s ability to meet its goals, and even their public relations and perception. The organization of the governance framework is important for the success of the organization meeting its goals. Sociologist John Child states that these are connected and, in a circular manner, belief that changes in governance frameworks will succeed positively impacts the chance that the framework will result in the desired changes. Additionally, Williamson suggests that the organization of a governance framework results in economic consequences for that organization.

Frequently, the term good governance framework references a preferred style of governance that the author believes to be better suited to that industry or organization, especially in relation to public relations, and organizational and financial transparency.

Applications

There are examples of the use of governance frameworks in a wide variety of industries, as well as in the government of nation states and the public sector.

In their application to specific industries, companies, and problems, governance frameworks appear differently and reflect the unique needs of the group or organization. In the governance structure of information technology (IT) organizations, multiple frameworks have been suggested by authors connecting IT issues to the underlying theoretical business, organizational sociology, and economic models. In marine ecology, governance framework suggestions proposed by Fanning et al. provide a guiding structure for the management and conservation of marine in the Wider Caribbean Region. Corporate governance frameworks are also well established and the theories behind how they are structured are discussed in academic papers, with different theoretical perspectives shaping how governance structures are used and influenced by the business. For example, Braganza and Lambert suggest that business leaders use an adaptable governance framework that they believe better addresses strategy as well as operation.

In the public sector’s governance frameworks, issues of public opinion and financial transparency tied to the concept of good governance frameworks are important, according to consulting firm Clayton Utz. The Charity Commission for England and Wales, a public commission responsible for ensuring trustworthiness of registered charities in the United Kingdom emphasizes its motives and mission, and accountability and transparency goals in its governance framework. It also uses the governance framework to make publicly available its internal organization and leadership structure. Loorbach suggests governance frameworks for nation state governments’ development which challenge current paradigms and that he suggests will lead to more sustainable development.

Important

Governance systems are complex and multi-faceted. By changing any part of a governance system, it has an effect on many other parts of the structure including the individuals and groups that make up the system and extend to it.

An organization’s mission, vision, and values comprise the primary parts of a governance system. The mission statement gives an organization direction and a purpose. It’s necessary for organizational leaders to share a common mission in order to ensure a strong foundation.

The risk side of model governance is especially important, since it ensures that models involved with finances stay clear of dangerous risks. Since models are programmed to continue learning as they run, they can accidentally learn biases if they are presented with data that creates a bias, which can affect the decisions the model makes from that point on.

Model governance allows models to be audited and tested for speed, accuracy, and drift while in production. This avoids any issues of model bias or inaccuracy, allowing models with risks involved to operate smoothly.

A key benefit of model governance is its ability to clearly identify who has ownership of a model while a company changes over time. For example, if someone worked on a project years ago but has left the company, model governance helps keep track of projects, how they run, and where you left off.

Credit sScoring

Credit scoring models help banks make informed decisions in the loan approval process by providing predictive analysis information concerning the potential for loan default or delinquency. This helps the bank determine the model risk pricing they should use for the loan.

Problem: This type of model involves risk for both parties: The bank and the loan applicant. If the model shows bias toward the bank, then the loan applicant cannot get the money they deserve. Or worse, if the model shows bias toward the loan applicant, they may take out a loan they cannot afford, causing a loss for the bank and financial trouble for the loan recipient.

Solution: Model governance solves this problem by auditing the model while it’s in production to make sure no biases are involved. Credit scoring models are more accurate and reliable than manual credit scoring, as long as they are governed.

Interest rate risk modelling

Interest rate risk models monitor earnings exposure to a range of potential market conditions and rate changes in order to measure risk. The purpose of this type of model is to give an overview of the potential risks of the account it is monitoring.

Problem: This model is directly related to risk, since risk is the output. If the model inaccurately judges the account as low risk, the account owner may lose money or miss out on potential gains by keeping the account where it is. If the model inaccurately judges the account as high risk, the account holder may move their money to other accounts and lose money or miss out on potential gains.

Solution: Model governance ensures that the model achieves its intended purpose. It is one thing to train a model in the development stages and get great results, and another thing to continue getting great results over time while that model is in production. With model management after deployment, you can be sure the models perform accurately over time.

Derivatives pricing

Derivatives pricing models estimate the value of assets by providing a methodology for determining the value of both new products and complex products without market observations readily available. This helps banks and investors determine if a business is worth investing in or not.

Problem: Investment banking is largely done by assessing the value of a company’s assets to determine the current value of the company. If this type of model includes inaccuracies, banks and investors may invest in companies that aren’t profitable investments.

Solution: This model needs to be governed and managed well into production and continuously throughout its lifespan in order to ensure investments are made with accurate information.