However, a thorough discussion of explanation in the adverse action notice context is outside the scope of this broad report.[14]). Although this is still a field of evolving research, some theoretical mitigation techniques are being further researched in the technology industry. If you would like to unsubscribe or have any questions, you can click on the unsubscribe links in our messages or contact us using the information below. We can use your profile and the content you share to understand your interests and provide content thatisjustforyou. Ultimately, the use of an AI system which may cause potentially unfair biased outcomes may lead to regulatory non-compliance issues, potential lawsuits and reputational risk. Examples Governance Risk Related Topics Enterprise Risk Management (ERM) and Risk Governance MPUG APRIL 26, 2021 Risks were identified, then qualified, and risk responses planned. Im going to talk about schedule risk analysis. The first one is the one around risk, around scope rather. Tell me about your experience preparing and presenting risk assessments and . The use of AI/ML deployment may involve third party applications and/or data, as discussed in Section 2, which could enable scalability, increased compute power and access to vendors that are part of the larger fintech ecosystem. Questionnaires, surveys and interviews are useful ways of gaining insight into different processes across teams and departments. GRC strategies aim to help organizations better coordinate processes, technologies, and people and ensure they act ethically. Diligent's Compliance Software Helps You Keep Track of Everything and Stay Ahead of the Curve. Nicholas Schmidt, Director and AI Practice Leader at BLDS, LLC Lack of context, judgment, and overall learning limitations may play a key role in informing risk-based reviews, and strategic deployment discussions. [6] See, for example, SR 11-7 Guidance on Model Risk Management SR 11-7, April 2011, available at https://www.federalreserve.gov/supervisionreg/srletters/sr1107.htm. Examples are: Transparent communications ESG disclosures Board structure and diversity Corruption and fraud prevention Organization integrity and ethics Executive compensation It was a classic watermelon project, where everything looks green from the outside, but is all red when you open it. We understand the term "risk governance" as the various ways in which many actors, individuals, and institutions - public and private - deal with risks surrounded by . [17] [4]ML models may be sensitive to environmental developments, for example, that could potentially alter their performance, Some AI systems may not have exposures to the below potential risks, either due to the nature of implementation or controls in place. This is what a basic example of a risk management plan could look like. Cloud Governance Model Principles. Please find below a transcription of the audio portion of John Owens showcase session, Making Light Work of Schedule Risk Analysis, being provided by MPUG for the convenience of our members. Ability to perform root cause analysis over operational events. You may use these HTML tags and attributes:

. As you may have correctly guessed, this project was in trouble. Third, AI approaches could be applied to trading and investment strategies, from identifying new signals on price movements to using past trading behavior to anticipate a clients next order. It defines and enforces activities like: How executives gather data, make strategic decisions, communicate with key stakeholders and determine who joins the board all depend on governance. In a more objective way, compliance . There should be regular communication and clarity about the objectives to all members of the organization. This interest is driven by the understanding that AI/ML poses new challenges, and readers should evaluate how regulations may impact the use and governance of AI/ML. Both aspects are integral to the ongoing success of an organization. 2 Governance. When you first look at our governance model or some of our team designs, it might look complicated, it might look really busy. Related: Free Risk Matrix Template for Excel. Our list of strategic risk examples below therefore includes more than five. Planning Project Management ProjectManager Blog Risk Management. Provide advisory services to internal IT and business units, as well as, Internal and external audit. Depending on the control library of an institution, this may require participation from multiple control owners and requires a structured approach and thorough planning. Well-known interpretable systems include linear systems, decision trees, and rule-based systems, where internal system mechanisms are composed of a relatively small number of learned coefficients or Boolean rules. The how aspects are about organizing and doing the work. In this article, well answer the following questions: GRC stands for Governance, Risk and Compliance. A Center of Excellence (CoE) may provide a knowledge-sharing platform in an organization. Similarly, in a speech [8] by Charles Randell, Chair of the UK Financial Conduct Authority, concerns over misuse of big data to inform potentially detrimental outcomes were raised, with a real-world example in the use of data mining credit card charges for services such as marriage counseling, and reducing cardholders credit limits on the basis of the correlation between marriage breakdown and debt default. Andres Fortino, PhD, NYU As the first step to achieving AI governance, a clear definition of what constitutes AI (and what does not) is critical for any organization. All these functional departments may have their own risk management as shown in the below figure. Balanced Scorecard for Corporate Governance Corporate governance, in its essence, is focused on proper strategy execution. Center of Excellence A well-planned GRC strategy with an integrated approach goes a long way. Over 100 analysts waiting to take your call right now: 1-519-432-3550 x2019. For example, you might have to get citizen approval before you can move forward with your plan. Generally, it is difficult to thoroughly assess systems that cannot easily be understood. However, a robust GRC strategy is about more than a specific tool or set of roles. The company could also receive lawsuits from one of its stakeholders due to some form of impropriety. Risk Management (#RM). As AI use advances and becomes more widespread within the industry, AIRS acknowledges that there are multiple ways to govern potential risks and any risk management framework should be tailored to each individual firms unique circumstances. Many newer explanation approaches tend to focus on high-fidelity summaries of local system behavior, essentially attempting to describe why an AI/ML system made a decision about a single customer, transaction, or other entity. For example, as noted, a program manager is overseeing multiple projects, or programs. Board Management for Education and Government, Internal Controls Over Financial Reporting (SOX). Interpretable systems, posthoc explanations, and the documentation they facilitate may also be required under several applicable regulations and legal frameworks, such as the Equal Credit Opportunity Act, the Fair Credit Reporting Act, and the E.U. While a lot of effort can go into developing a viable governance structure, it doesnt have to be that way on every project. Planning ProjectManager Blog Risk Management. Clearly defined risk appetite, risk profile, and risk tolerances enable management and . Risk governance represents the institutions, rules and regulations, processes, and mechanisms through which making decisions about risks is possible. As the business grows, the severity and frequency of governance, risk and compliance issues also grow. Sites have been updated - click Submit All Changes below to save your changes. Subscribe to the Diligent GRC Newsletter. Interpretability (presenting the AI systems results in human understandable format), and discrimination (unfairly biased outcomes) are crucial concepts that factor into the risks associated with AI/ML systems used for certain use cases. This article tackles the importance and significance of IT Project Governance Framework and its impact on the projects in the organization. Change risk. Identified risks are analyzedboth qualitatively and quantitatively. These insights are based on collective experience of AIRS, and the suggestions we outline are, as a result, not meant to be comprehensive. Those standards and practices are called corporate governance, and they are going to influence your project. Generally speaking, three types of discrimination are recognized by federal banking regulators: overt discrimination, disparate treatment, and disparate impact when not supported by a legitimate business justification. A project charter is a brief, formal document that outlines a project in its entirety including its objectives, key stakeholders, major milestones, risks, and budget. Some of this concern arises from the fact that some machine learning algorithms create variable interactions and non-linear relationships that are too complex for humans to identify and review. Testing and validation of AI/ML systems may pose challenges relative to traditional systems as certain AI/ML systems are inherently dynamic, apt to change over time, and by extension, may result in changes to their outputs. Definition of this competency. Such groups might develop best practices for their organization, share knowledge, and build guard rails for the use of AI systems. Fair AI, nevertheless, may require a human-centric approach. Testing for all scenarios, permutations and combinations of available data may not be possible, thus leading to potential gaps in coverage. Last week, Harry and I were running, and he told me about his procurement risk blog series. Implementing a GRC model can seem complex, as it will generally include internal auditing of existing processes and procedures. Governance is the system of rules, practices, and processes an . As such, we note that specific definitions should be (and generally are) tailored to each organization depending on the scope, risk appetite, internal structure, culture, and implementation details of AI/ML efforts. <> We address these sub-categories in further detail below. Depending on the use case, Firms may consider including contractual clauses for third parties regarding the AI systems testing methodology, explainability of the results generated by the system, and/or intellectual property rights which may be derived from use of the system. [1] AIRS is an informal group of practitioners and academics from varied backgrounds, including technology risk, information security, legal, privacy, architects, model risk management, and others, working for financial and technology organizations and academic institutions. - IT Governance: How Top Performers Manage IT Decision Risght for Superier Results , Weill and Ross, Harvard Business School Proess. Adversarial Inputs Indeed, HR governance also includes the internal oversight and management of an organization's HR strategy, programs, practices, and outcomes, through clearly defined roles, responsibilities, and accountabilities both down and across the enterprise. And when ESG risks materialize, they can be very costly Some examples include: In April 2010, BP's oil rig Deepwater Horizon exploded in the Gulf of Mexico, creating an environmental disaster and significantly impacting biodiversity. Risks were identified, then qualified, and risk responses planned. ERM ensures that all organizational risks are properly identified, addressed, managed, and monitored. Its likely that each established area of the organization will have its own way of performing risk assessments or compliance monitoring. Effective Risk Management 2nd Edition, Edmund Conrow, AIAA, 2003. Kevin Fitzpatrick, Wells Fargo Organizations may benefit from the implementation of protocols, structures, frameworks, and tools to assist in maintaining an accurate and comprehensive systems inventory. Security governance provides a broad or long view of risk from potential future attacks and attack vectors. GRC software will provide one area to record all the different risk assessments and internal audits. For example, the root cause of major incidents. The results of the internal audit will help shape the direction of the whole GRC project. The Financial Stability Board recently highlighted four areas where AI could impact banking specifically. Take for example the deployment of an ERP system, the installation, and startup of a process control system, the release of a suite of embedded software controllers for a car, aircraft, petrochemical plant. As of this writing, there is no commonly agreed upon standard definition of AI explainability. They should assess, implement, and tailor their firms AI/ML programs and respective controls as appropriate for their business model, product and service mix, and applicable legal and regulatory requirements. Then, the best suitable governance layer is decided. Below each Point of Project Failure are examples of primary reasons why projects fail. The ERM process is also determined by the Executive Management. These developments may test certain aspects of current practices, such as TPRM transparency around model interpretability, information security issues for cloud-based service providers, and broader concerns around technology dependencies for the third parties themselves. Therefore, two systems giving different explanations for the same result or decision may create unwanted outcomes. The AIRS working group, based in New York, was initiated in early 2019 and has grown to nearly 40 members from dozens of institutions (and continues to grow). An ethics review board may review AI projects in accordance with an organizations ethical principles, e.g. This site uses cookies to improve your experience. Lets look at how to start the risk management process. An adversary could potentially infer sensitive information from the training data set by analyzing the parameters or querying the model. His course, PMP Live Lessons Guaranteed Pass, has made many successful PMPs, and hes recently launched RMP Live Lessons Guaranteed Pass and ACP Live Lessons Guaranteed Pass. Oversight Processes View our privacy policy and terms of use. Compliance Risk. I welcome your feedback below in the comments section. Detection Risk. They may also create and maintain data sets for the purpose of training AI systems. Therefore, the results of the system are similar even if a particular user/data element record is omitted. As financial services firms evaluate the potential applications of artificial intelligence (AI), for example: to enhance the customer experience and garner operational efficiencies, Artificial Intelligence/Machine Learning (AI/ML) Risk and Security (AIRS)[1] is committed to furthering this dialogue and has drafted the following overview discussing AI implementation and the corresponding potential risks firms may wish to consider in formulating their AI strategy. For any inquiries or questions regarding AIRS or the white paper, please contact Yogesh Mudgal (yogesh@airsgroup.ai). The role is mostly operational, meaning it involves planning and governance for overseeing the program and its successful delivery. The use and potential for misuse of big data is no longer a theoretical concern and should be considered in determining the types of data that may be used in developing AI/ML systems. AI governance frameworks could help organizations learn, govern, monitor, and mature AI adoption. For example, the Millennium Dome attracted 5.5 These examples show that defining what we mean by success has a significant impact on whether we believe a project has failed. 1, January 18, 2019, https://www.dfs.ny.gov/industry_guidance/circular_letters/cl2019_01, [8] See How can we ensure that Big Data does not make us prisoners of technology?, July 11, 2018, https://www.fca.org.uk/news/speeches/how-can-we-ensure-big-data-does-not-make-us-prisoners-technology. I agree with your observation that those organizations which reward risks, but less likely to penalize risk seekers are the ones to reckon with. However, it is critical that each institution assess its own AI uses, risk profile and risk tolerance and design governance frameworks that fit their unique circumstances. Some examples include: Billable to non-billable hours. An example of poor governance in an organization might be a group of executives engaging in insider trading or a director whose business decisions and strategies consistently reflect a lack of interest in environmental, social or legal guidelines. As such, drift detection could play an important capability in mitigating some types of AI-related risks, including characteristics that contribute to a models security, privacy, and fairness.
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