Curriculum & Courses

This course provides an overview of the traditional ERM frameworks used to identify, assess, manage, and disclose key organizational risks. The traditional ERM frameworks are those that are more commonly in use and include COSO ERM, ISO 31000, and the Basel Accords. This course also provides an understanding of the methods, tools, techniques, and terminology most organizations use to manage their key risks, presented in the context of the foundational elements of an ERM process. This will enable students to navigate the ERM landscape within most organizations, and, along with the second-semester course Value-Based ERM, evaluate opportunities to enhance the existing ERM practices and evolve their ERM programs over time.

Availability

• On Campus: Fall and Spring
• Online: Fall and Spring

Workshop-like course that addresses a variety of communication skills, including listening skills, presentation skills, leadership communications, conflict resolution, management interactions, and professional communication techniques.

(Students must take this course in the first semester.)

Availability

On Campus: Fall and Spring
Online: Fall and Spring

Foundational ERM course. Addresses all major ERM activities: risk framework; risk governance; risk identification; risk quantification; risk decision making; and risk messaging. Introduces an advanced yet practical ERM approach based on the integration of ERM and value-based management that supports integration of ERM into decision making. Provides a context to understand the differences between (a) value-based ERM; (b) traditional ERM; and (c) traditional "silo" risk management.

Availability

On Campus: Every term
Online: Every term

Provides a global review of ERM requirements of regulators, rating agencies, and shareholders. Addresses three industry sectors: (1) insurance; (2) banking; and (3) corporate.

(It is recommended but not required that students take Traditional ERM Practices as a prerequisite to this course.)  

Availability

On Campus: Every term
Online: Every term

Teams will work through a case assignment, demonstrating mastery of key learnings gained throughout the program on an integrated basis. A simulated case study is used: this is a combination of publicly-available information of an actual company and simulated ERM program details, based on a blend of current ERM programs and practices in the marketplace. Each team will assess the case study and recommend enhancements.

Availability

On Campus: Every term
Online: Every term

Review of the types of strategic risks, such as a flawed strategy, inability to execute the strategy, competitor risk, supply chain risk, governance risk, regulatory risk, M&A risk, international risk, etc. Includes case studies, research, and common mitigation techniques, such as strategic planning practices, management techniques, governance practices, supply-chain management, etc.

Availability

On Campus: Every term
Online: Every term

Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.

Availability

On Campus: Every term
Online: Every term

A survey of market, credit, liquidity, and systemic risk. Includes case studies, risk quantification methods, and common mitigation techniques using portfolio management, hedging, and derivatives. Also addresses traditional risk management practices at banking institutions.

Availability
On Campus: Every term
Online: Every term

Review of types of insurance risk, such as pricing risk, underwriting risk, reserving risk, etc. Includes case studies, risk quantification methods (e.g., market-consistent economic capital models, dynamic financial analysis (DFA) models, catastrophe models, etc.), and common mitigation techniques, such as asset-liability management (ALM), reinsurance, etc. Also addresses traditional risk management at insurance companies and ERM actuarial standards of practice (ASOPs).

Availability
On Campus: Fall and Spring
Online: Not offered

This elective is available to and highly recommended for students without a strong finance background. It introduces students to the fundamental financial issues of the modern corporation. By the end of this course, students will understand the basic concepts of financial planning, growth management, debt financing, equity valuation, and capital budgeting.  (This course is not automatically available for credit; students must contact their Advisor to determine eligibility to register.)

Availability

On Campus: Every term
Online: Every term

In this course, students will gain an overview of major concepts of management and organization theory, concentrating on understanding human behavior in organizational contexts, with a heavy emphasis on the application of concepts to solve managerial problems. Students will work in a combination of conceptual and experiential activities, including case studies, discussions, lectures, simulations, videos, and small group exercises.

By the end of this course students will:

• Develop the skills to motivate employees
• Establish professional interpersonal relationships
• Take a leadership role
• Conduct performance appraisals

Availability: 

On Campus: Every term
Online: Every term 

Students without a strong math background will require significant additional time and effort to achieve the learning objectives and work through the course assignments. This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python. This course is a required prerequisite for registering for the following courses: Financial Risk Management, Insurance Risk Management, ERM Modeling.

Availability

On Campus: Every term
Online: Every term

Equips students with the ability to adopt the programming culture typically present in the ERM/risk areas of most financial organizations. By studying Python, SQL, R, git, and AWS, students gain exposure to different syntaxes. Students apply these skills by coding up market risk and credit risk models. Students also gain familiarity with working in the cloud.

Availability

On Campus: Every term
Online: Every term

Provides the opportunity to learn how business units operate at an investment bank. Several industry practitioners each spend one to two sessions providing a hands-on experience that recreates the operations and decision-making of front, middle, and back offices work at a bank. Students typically learn the common activities, the data inputs, the analytics, and the applications of the insights.

(Students must complete ERMC PS5360: Financial Risk Management prior to registering for this course.)

Availability

On Campus: Summer and Fall 
Online: Not offered

Credit Risk Management requires business acumen, the monitoring of internal and external data, disciplined execution, and organizational intelligence. A solid understanding of this enables a credit risk manager to help organizations achieve their objectives. Through readings, case studies, and modeling projects, students learn how risk managers decide on credit risk management strategy applied throughout the client lifecycle.

Availability

On Campus: Every term
Online: Every term

This course provides the tools to measure and manage market risk in the context of large financial institutions. The volume and complexity of the data itself, at large institutions, makes it a challenge to generate actionable information. We will take on this challenge to master the path from data to decisions.

We cover the essential inputs to the engines of financial risk management: VaR, Expected Exposure, Potential Exposure, Expected Shortfall, backtesting, and stress testing as they apply to asset management and trading. We explore the strengths and weaknesses of these different metrics and the tradeoffs between them. We also cover how regulatory frameworks impact both the details and the strategy of building these engines. Lastly, we cover counterparty-credit methodologies, mainly as they apply to Trading Book risk.

Availability
On Campus: Every term (starting Fall 2022)
Online: Not offered

The field of credit risk management is undergoing a quiet revolution as subjective and manually-intensive methods give way to digitization, algorithmic management, and decision-making. This course provides a practical overview and hands-on experience with different methods, and it also provides a view of future technologies and discussions of potential future directions. Participants in this course should be well-positioned to take entry-level analytic positions and help drive strategic decisions.

The first half of the course explores analytics used today for credit risk management. You will learn to create rating and scoring models and a macro scenario-based stress testing model. In the second half of the course, we explore more advanced tools used by the more prominent organizations and fintech firms, including neural net and XGBoost decision tree models.

Availability

On Campus: Every term (starting Fall 2022)

Online: Not offered

Examination of areas critical to an organization’s success from strategic, operational, financial, and insurance perspectives, and examines why many companies fail in spite of the vast knowledge of factors driving success. Several case studies examined in depth.

Availability

On Campus: Every term
Online: Every term

With an orientation more towards practical application, the intent of this course is to provide a strategic framework with which students can evaluate and understand the global financial services industry of both today and tomorrow. In this course we are defining global financial services as encompassing central banks, commercial and investment banks, asset/wealth management institutions and financial regulators. Via case studies, proprietary materials, class based problem solving exercises, and guest lectures, we will examine and discuss the i) current and future role of the major financial service participants, (ii) key drivers influencing an industry that has always been characterized by significant change (e.g., regulatory, technology, risk, globalization, and client needs), and (iii) challenges and opportunities facing today's financial services' CEOs post the 2008/09 financial crisis. Furthermore, this course is designed for students who want to be financial “architects and leaders”, not financial “technicians”.

Availability:

Online: Spring
 

This course examines post-financial crisis regulations including Basel III, Fundamental Review of the Trading Book (FRTB), Dodd-Frank Act, Supervision and Regulation Letter 11-7 (SR 11-7), and others.  Case studies will explore the technical details of these new rules; and guest lectures from industry experts will bring the material to life.  Areas of focus include: model risk management, stress testing, derivatives, and insurance.  By the end of this course students will be able to:

• Evaluate the purpose and limitations of risk regulations in finance.
• Identify and communicate weaknesses in a financial firm.
• Communicate with regulators.
• Understand Recovery and Resolution Plans or “Living Wills” for a financial firm.

Availability

• On Campus: Every term
• Online: Every term

This course explores financial derivatives across different asset classes with in-depth analysis of several popular trades including block trades, program trades, vanilla options, digital options, and variance swaps. Their dynamics and risks are explored through Monte Carlo simulation using Excel and Python. The daily decisions and tasks of a frontline risk manager are recreated and students have the opportunity to see which trades they would approve or reject. Students will gain a working knowledge of financial derivatives and acquire technical skills to answer complex questions on the trading floor.

Availability

On Campus: Every term
Online: Not offered

Tools for Risk Management examines how risk technology platforms assess risks. These platforms gather, store, and analyze data; and transform that data to actionable information. This course explores how the platforms are implemented, customized, and evaluated. Topics include business requirements specification, data modeling, risk analytics and reporting, systems integration, regulatory issues, visualization, and change processes. Hands-on exercises using selected vendor tools will give students the opportunity to see what these tools can offer.

Availability

On Campus: Every term
Online: Not offered

Given the ever growing reliance on models, Model risk affects financial institutions at almost every level of their organization including pricing, risk, finance, and marketing. Model risk management (MRM) is now one of the primary focuses of operational risk management at modern financial institutions. In this class, the ERM skill sets of risk identification, risk quantification, and risk decision making are applied to the kinds of models seen in large, complex financial institutions. Through readings, lecture, assignments, and in-class discussions, students learn the principles and concepts that a robust MRM function uses to manage model risk. 

Availability

On Campus: Every term
Online: Not offered

Equips students with the basics of risk measurement and simulation using a hands-on approach to ERM modeling. Using industry-standard simulation software, students build systems of risk drivers for finance and insurance companies. Topics include risk correlations, VaR and TVaR, capital modeling, capital allocation, and parameter, process, and model Risk. Students acquire both quantitative experience building models and qualitative appreciation for model weaknesses.

Availability

On Campus: Every term
Online: Every term

The exponentially increasing availability of data and the rapid development of information technology and computing power have inevitably made Machine Learning part of the risk manager’s toolkit. But, what are these tools? This class provides the driving intuitions for machine learning. Students will see how many of the algorithms are extensions of what we already do with our human minds. These algorithms include regularized regression, cluster analysis, naive bayes, apriori algorithm, decision trees, random forests, and boosted ensembles.

Through practical and real-life applications of ML to Risk Management, students will learn to identify the best technique to apply to a particular risk management problem, from credit risk measurement, fraud detection, portfolio selection to climate change, and ESG applications.

Availability

On Campus: Every term
Online: Not offered

A study of financial, economic, and engineering disasters from a common systems engineering perspective, to better understand and model risk in complex process systems. Course topics will introduce process systems engineering concepts and tools such as digraphs, fault trees, probabilistic risk assessment, HAZOP, FMEA, etc., for modeling enterprise-wide risk. We will develop risk models and analyze them for real-life inspired examples and case studies. Several disaster case studies will also be discussed.

Availability

On Campus: Fall and Spring
Online: Fall  

Students will learn how to better identify and manage a wide range of IT risks as well as better inform IT investment decisions that support the business strategy. Students will develop an instinct for where to look for technological risks, and how IT risks may be contributing factors toward key business risks. This course includes a review of IT risks, including those related to governance, general controls, compliance, cybersecurity, data privacy, and project management. Students will learn how to use a risk-based approach to identify and mitigate cybersecurity and privacy related risks and vulnerabilities. No prior experience or technical skills required to successfully complete this course.

Availability

On Campus: Every term
Online: Every term

Explores key concepts of behavioral economics and cognitive psychology, how to identify key cognitive biases in ERM activities, and how to apply techniques to address these, enhancing the quality and integrity of an ERM program. The course also includes best practices in leveraging analytic models to improve decision making.

Availability

On Campus: Every term
Online: Fall and Summer

The Internship in Industry course offers students the preparation to excel in the marketplace with hands-on experience within an organization. The ideal internship will provide students an opportunity to gain tangible and practical knowledge in their chosen field by taking on a position that is closely aligned with their coursework and professional interests.

This course is structured around the internship experience. In the first assignment, students will author learning objectives to complete in their internship and review these learning objectives with their site supervisor. Students should also expect that after completing this course they will be able to:

• Discuss the application of program content and theory in a professional context (LO1)
• Define a plan for assessing and building their professional competencies (LO2)
• Describe an organization’s culture and assess their cultural “fit” (LO3)
• Make recommendations for the types of behaviors, structure, and culture they would want to see in a future workplace setting (LO4)

Before registering for this course, students must secure an appropriate graduate-level internship, complete the Internship Application Form and receive approval from the academic program. It is highly recommended that domestic students complete at least 12 points (credits) prior to completing an internship. International students must have completed at least two terms before completing an internship and apply for & receive CPT approval through the ISSO Office unless they completed their undergraduate degree in the U.S. and enrolled in graduate school immediately after obtaining their undergraduate degree.

To receive approval, the internship must:

• Provide an appropriate opportunity for students to apply course concepts
• Fit into the planned future program-related career path of the student
• Provide a minimum of 210 hours over the semester
• Internship dates must coincide with the start and end of the term you are enrolling in the course. You may not complete this course for a previous internship or for an internship you plan to take in the future. The internship and course must be done at the same time. 

Availability

On Campus: Fall and Spring
Online: Summer