General Information
This intensive MBA subject examines how managers create, measure, and sustain organisational value in an increasingly uncertain and complex environment. Students develop the financial knowledge and analytical capabilities required to evaluate performance, identify value drivers, assess risk, and make informed investment, financing, and valuation decisions. Emphasis is placed on evidence-based decision making, the strategic use of technology and AI-enabled tools, and the effective communication of financial insights across diverse stakeholder groups. Through cases and applied analyses, students explore how value creation and risk management interact within a sustainable finance framework to support robust decision making and long-term organisational success.
Details
| Academic unit: | Bond Business School |
|---|---|
| Subject code: | BMBA71-103 |
| Subject title: | Value, Risk and Sustainable Finance (January 2027) |
| Subject level: | Postgraduate |
| Semester/Year: | January 2027 |
| Credit points: | 10.000 |
Delivery & attendance
| Timetable: | https://bond.edu.au/timetable |
|---|---|
| Delivery mode: | Intensive |
| Workload items: |
|
| Attendance and learning activities: | Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. NOTE: BBS uses a self and peer-evaluation system to support students engaged in group-based assessments. Students are expected to provide this feedback in a timely fashion as part of their assessment. The information gathered is used by the educator as partial evidence of equitable contributions by all group members and helps to determine individual marks for group assessments. |
Resources
| Prescribed resources: | No Prescribed resources. After enrolment, students can check the Books and Tools area in iLearn for the full Resource List. |
|---|---|
| iLearn@Bond & Email: | |
| Class recordings: | The primary workload items for this subject will be recorded for the purpose of revision. These recordings are not a substitute for attending classes. Students are encouraged to attend all sessions as there may be instances where a session is not recorded due to the presence of a guest speaker, the inclusion of sensitive or protected content, or technical issues. Students are advised not to rely solely on these recordings for revision. See the Recording policy for further details. |
| Academic unit: | Bond Business School |
|---|---|
| Subject code: | BMBA71-103 |
| Subject title: | Value, Risk and Sustainable Finance (January 2027) |
| Subject level: | Postgraduate |
| Semester/Year: | January 2027 |
| Credit points: | 10.000 |
| Timetable: | https://bond.edu.au/timetable |
|---|---|
| Delivery mode: | Intensive |
| Workload items: |
|
| Attendance and learning activities: | Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. NOTE: BBS uses a self and peer-evaluation system to support students engaged in group-based assessments. Students are expected to provide this feedback in a timely fashion as part of their assessment. The information gathered is used by the educator as partial evidence of equitable contributions by all group members and helps to determine individual marks for group assessments. |
| Prescribed resources: | No Prescribed resources. After enrolment, students can check the Books and Tools area in iLearn for the full Resource List. |
|---|---|
| iLearn@Bond & Email: | |
| Class recordings: | The primary workload items for this subject will be recorded for the purpose of revision. These recordings are not a substitute for attending classes. Students are encouraged to attend all sessions as there may be instances where a session is not recorded due to the presence of a guest speaker, the inclusion of sensitive or protected content, or technical issues. Students are advised not to rely solely on these recordings for revision. See the Recording policy for further details. |
Enrolment requirements
| Requisites: |
Nil |
|---|---|
| Restrictions: |
Nil |
Assurance of learning
Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.
At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.
Program Learning Outcomes (PLOs)
Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.
Subject Learning Outcomes (SLOs)
On successful completion of this subject the learner will be able to:
- Critically evaluate financial statements, ratios, and other financial information to identify an organisation’s key value drivers and inform managerial decision-making.
- Use information technology and AI-enabled tools to source, acquire, evaluate, and analyse financial information, while exercising critical thinking, professional judgement, and other capabilities that complement artificial intelligence.
- Apply financial concepts, analytical frameworks and risk evaluation techniques to evidence-informed recommendations for complex investment, capital structure, and valuation decisions to support long-term value creation.
- Develop and defend evidence-based recommendations for investment, financing, and valuation decisions through persuasive written and oral arguments.
- Communicate complex financial analyses and recommendations effectively to managers and nonfinancial stakeholders while demonstrating ethical judgement.
Generative Artificial Intelligence in Assessment
The University acknowledges that Generative Artificial Intelligence (Gen-AI) tools are an important facet of contemporary life. Their use in assessment is considered in line with students’ development of the skills and knowledge which demonstrate learning outcomes and underpin study and career success. Instructions on the use of Gen-AI are given for each assessment task; it is your responsibility to adhere to these instructions.
Assessment details
| Type | Task | % | Timing* | Outcomes assessed | AI category |
|---|---|---|---|---|---|
| Computer-aided Test (Open) | Covers material from the Pre-session readings and exercises on the Language of Business. Designed to equip students to read financial statements. | 10.00% | Week 11 | 1, 2 | |
| Analysis | Creation of a dynamic valuation spreadsheet model for a private company. | 20.00% | Week 12 | 1, 2, 3 | |
| Case Study | Professional Equity Research Report for initial public offering (IPO). | 40.00% | Week 14* | 1, 2, 3, 4, 5 | |
| Student Engagement | Classroom contribution is designed to encourage preparation and participation as determined by the instructors with feedback from the peer assessors. Mid-week tracking memo will be provided. | 30.00% | Ongoing | 1, 3, 4 |
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
Assessment criteria
Assessment criteria
| High Distinction | 85-100 | Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. |
|---|---|---|
| Distinction | 75-84 | Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. |
| Credit | 65-74 | Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. |
| Pass | 50-64 | Usually awarded to students whose performance meets the requirements set for work provided for assessment. |
| Fail | 0-49 | Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. |
Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
| Type | Task | % | Timing* | Outcomes assessed | AI category |
|---|---|---|---|---|---|
| Computer-aided Test (Open) | Covers material from the Pre-session readings and exercises on the Language of Business. Designed to equip students to read financial statements. | 10.00% | Week 11 | 1, 2 | |
| Analysis | Creation of a dynamic valuation spreadsheet model for a private company. | 20.00% | Week 12 | 1, 2, 3 | |
| Case Study | Professional Equity Research Report for initial public offering (IPO). | 40.00% | Week 14* | 1, 2, 3, 4, 5 | |
| Student Engagement | Classroom contribution is designed to encourage preparation and participation as determined by the instructors with feedback from the peer assessors. Mid-week tracking memo will be provided. | 30.00% | Ongoing | 1, 3, 4 |
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
Assessment criteria
| High Distinction | 85-100 | Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. |
|---|---|---|
| Distinction | 75-84 | Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. |
| Credit | 65-74 | Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. |
| Pass | 50-64 | Usually awarded to students whose performance meets the requirements set for work provided for assessment. |
| Fail | 0-49 | Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. |
Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Study Information
Policy on late submission and extensions
A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the subject coordinator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.
Additional subject information
As part of the requirements for Business School quality accreditation, the Bond Business School employs an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Subject curriculum
The Language of Business
Mechanics, measurement, and management of financial statements and ratios. The Anatomy of an annual report: where the real information lives.
Financial Fundamentals
How the three financial statements connect. Value maximisation versus profit maximisation. The market for introduction to capital markets and how different capital market securities satisfy investor’s risk preferences. stakeholder tensions and the market for corporate control.
Performance and Value Drivers
Moving from historical reporting to forward-looking, driver-based thinking: the shift from accountant to operator. How capital structure and investment choices drive value.
Judgment in an Augmented World
A durable mental model for working with AI in finance and accounting that framed around judgment, not perishable prompting tactics. Decision making using net present value (NPV), Internal Rate of Return (IRR) and real options. Stock market basics: risk, return, diversification, beta, and the CAPM.
Capital Allocation Under Uncertainty
The CEO's central question: where does the next dollar go: A strategic decision rather than a “calculation”. Cost of capital and optimal capital structure. Firm valuation using discounted cashflow valuation (DCF) and multiples. Forecasting, scenarios, and simulations.
Capital Raising Under Uncertainty A
Financing entrepreneurial ventures from early-stage funding through to initial public offerings. Microfinance. Governance, ESG, and Stakeholder Implications. Valuation Myths. Determining your walk-away price, and defending your assumptions.
Capital Raising Under Uncertainty B
Initial Public Offerings (IPOs). Triangulating across several valuation approaches to arrive at reasonable valuation range and then determine offer price. Understanding the importance of the Road Show in the price discovery process. Presenting and defending your offer.