Exploring the Ethical Implications of Earnings Management in Financial Reporting.

Earnings management is a widely debated topic in accounting and finance, concerning the use of accounting techniques to influence reported earnings. While some consider it a legitimate tool within the flexibility of accounting standards, others argue that it undermines the ethical foundation of financial reporting. This explores the ethical implications of earnings management, distinguishing between legal discretion and manipulative intent. It discusses motivations, techniques, consequences, stakeholder impact, and regulatory responses, and provides ethical frameworks for understanding and addressing the issue.

Financial reporting is a cornerstone of transparency and accountability in modern economies. Investors, regulators, creditors, and other stakeholders rely heavily on financial statements to make informed decisions. However, when corporate management manipulates earnings to present a more favorable image of a company’s performance, the integrity of financial reporting is compromised.

Definition and Nature

Earnings management involves the use of accounting methods and operational decisions to manipulate reported earnings within the boundaries of accounting standards. 

Healy and Wahlen (1999) define it as:

“Earnings management occurs when managers use judgment in financial reporting and in structuring transactions to alter financial reports to either mislead stakeholders or influence contractual outcomes.”

In its simplest form, Earnings management refers to the intentional manipulation of financial statements to achieve desired financial results.

Types of Earnings Management

• Accrual-Based Management: Adjusting accounting estimates like depreciation, provisions, or bad debts.
• Real Earnings Management: Altering real business activities such as delaying R&D, offering deep discounts, or postponing maintenance.
• Classification Shifting: Moving items between operating and non-operating income to meet targets.

Motivations Behind Earnings Management

Understanding why earnings are managed is vital for assessing its ethical implications.

• Meet or Beat Market Expectations: Avoid negative market reactions and preserve share price.
• Bonus and Compensation Incentives: Tied to profit performance.
• Loan Covenant Compliance: Prevent technical default.
• Political and Taxation Motivations: Reduce scrutiny or tax burdens.

While motivations may be strategic, the ethicality of manipulating numbers to achieve them remains questionable.

Ethical Theories and Frameworks

• Deontology (Duty-Based Ethics): Actions are ethical if they adhere to rules. Earnings management, if misleading, violates duties of honesty and transparency.
• Utilitarianism (Consequentialism): If earnings management maximizes benefits (e.g., preventing layoffs), it might be seen as justifiable. But this risks undermining long-term trust.
• Virtue Ethics: Emphasizes character. A virtuous manager prioritizes truth and accountability over short-term gains.
• Stakeholder Theory: All stakeholders have rights to truthful information. Earnings management often privileges management at the expense of others.

Is Earnings Management Always Unethical?

Not all earnings management is illegal. Standard allows managerial discretion. However, the intent behind actions determines ethicality. For example:

• Adjusting estimates based on sound judgment ≠ unethical.
• Deliberately manipulating figures to deceive ≠ ethical.

The gray area between judgment and manipulation is where ethical dilemmas reside.

Impacts on Stakeholders

• Investors: Misled into making poor investment decisions.
• Creditors: Provide loans under false pretenses.
• Employees: May suffer layoffs when manipulated numbers reverse.
• Auditors: Face reputational risks if complicit or unaware.
• Society: Loses trust in capital markets and institutions.

Professional Ethics Codes

Organizations like IFAC, AICPA, and ICAEW stress integrity, objectivity, and professional competence. Accountants are expected to resist pressures from management and report unethical behavior.

Recommendations and Remedies

Strengthening Ethical Culture

• Embed ethics in corporate governance.
• Promote whistleblower protection.
• Ethics training for managers and accountants.

Auditor Vigilance

• Challenge assumptions and estimates.
• Increase skepticism and professional judgment.

Enhanced Transparency

• Disclosure of critical accounting estimates and judgments.
• Real-time investor communication to reduce pressure to “hit targets.”

Role of Education

• Academic programs must emphasize ethics alongside technical skills.
• Case studies and dilemma-based learning can sharpen ethical sensitivity.

Earnings management occupies a complex space between legal flexibility and ethical compromise. While not always illegal, it often violates the spirit of transparency and trust upon which financial reporting is based. Ethical financial reporting requires a blend of professional judgment, strong governance, regulatory oversight, and personal integrity.

Addressing earnings management is not only about refining standards but about shaping an ethical culture where truthfulness is not sacrificed for temporary advantage. A sustainable financial system must be rooted in ethical decision-making that respects the rights and trust of all stakeholders.

References

1. Healy, P.M., & Wahlen, J.M. (1999). A Review of the Earnings Management Literature and Its Implications for Standard Setting. Accounting Horizons.
2. Schipper, K. (1989). Commentary on Earnings Management. Accounting Horizons.
3. International Ethics Standards Board for Accountants (IESBA). (2022). Code of Ethics for Professional Accountants.
4. Dechow, P., Sloan, R., & Sweeney, A. (1996). Causes and Consequences of Earnings Manipulation: An Analysis of Firms Subject to Enforcement Actions by the SEC. Contemporary Accounting Research.

Understanding ECL-based Loan Classification and Provisioning under IFRS 9 and its Pros and Cons

In the evolving landscape of global banking regulation, one of the most significant changes has been the shift from the traditional "incurred loss" model to the Expected Credit Loss (ECL) model under IFRS 9 – Financial Instruments. This forward-looking approach marks a paradigm shift in how banks assess and account for credit risk in their loan portfolios. Instead of waiting for a credit loss event to occur before recognizing it in the books, IFRS 9 requires banks to anticipate potential credit losses based on past events, current conditions, and future forecasts.

At the heart of this model is a three-stage classification system. In Stage 1, banks recognize a 12-month ECL on performing loans where credit risk hasn’t significantly increased. If the risk increases substantially but the asset is not yet impaired, it moves to Stage 2, where a lifetime ECL is recognized. Loans that are credit-impaired fall under Stage 3, also requiring lifetime ECL provisioning, but with more conservative assumptions and a focus on recovery values. This tiered structure ensures that the financial statements reflect the evolving credit quality of assets more realistically.

The ECL model under IFRS 9 relies heavily on data — historical credit performance, forward-looking macroeconomic indicators (such as GDP growth, inflation, or unemployment), and scenario analysis. Consequently, banks need robust IT infrastructure and analytics capabilities to implement and operate such systems effectively. This includes developing credit risk models, enhancing data collection frameworks, and training personnel.

Formula for Expected Credit Loss (ECL):

Where:

• EAD (Exposure at Default): The total value a bank is exposed to when the borrower defaults.

• PD (Probability of Default): The likelihood that the borrower will default within a given time horizon.

• LGD (Loss Given Default): The portion of the exposure that is expected to be lost, after accounting for recoveries.

Example:

Imagine a bank in Dhaka, Bangladesh—let’s call it “Unity Bank Ltd.”—which granted a term loan of $1,000,000 to a mid-sized garment exporter, “Textura Apparels Ltd.”. The company had always been a reliable client, but in 2025, the global textile market started showing signs of slowdown due to declining demand from Europe. Unity Bank’s risk team, following the ECL-based provisioning under IFRS 9, reevaluated Textura's credit risk.

Based on internal ratings and updated macroeconomic forecasts, the Probability of Default (PD) for Textura was estimated at 5% over the next 12 months. The Loss Given Default (LGD), based on collateral value and recovery history in similar cases, was estimated at 40%. The Exposure at Default (EAD) remained at $1,000,000.

Then:

$$\text{ECL}=1,000,000\times 0.05\times 0.40=20,000$$

The bank should provision $20,000 for this loan as per the ECL model under IFRS 9.

Below is a table summarizing the pros and cons of implementing ECL-based loan classification and provisioning under IFRS 9:

Pros	Cons
Forward-looking risk assessment enhances predictive credit loss accuracy	High implementation cost (systems, training, and data requirements)
Improves financial transparency and global reporting standards	Operational complexity due to advanced modeling needs
Strengthens credit risk management per Basel Committee recommendations	Requires detailed historical and forward-looking data
Aligns with international regulatory compliance (e.g., IFRS 9)	Transition from rule-based to ECL model is challenging and gradual
Enables proactive provisioning to reduce economic procyclicality	Dependence on macroeconomic forecasts adds model risk
Promotes capacity building and IT infrastructure upgrades	May necessitate external expertise and continuous training

How Artificial Intelligence Threatens the Chartered Accountancy Profession

 Artificial Intelligence (AI) is rapidly transforming industries across the globe, and the accountancy profession is no exception. For Chartered Accountants (CAs), AI presents both a formidable challenge and a remarkable opportunity. The profession, historically grounded in precision, compliance, and manual processing, is now being reshaped by technologies capable of performing many of these tasks faster, more accurately, and at a fraction of the cost.

This article explores how AI threatens the role of chartered accountants, the implications for the profession, and offers actionable remedies and recommendations for adapting in this new era.

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Threats Posed by Artificial Intelligence

1. Automation of Routine Tasks

AI systems, particularly those using machine learning and robotic process automation (RPA), can handle repetitive tasks such as bookkeeping, bank reconciliations, invoice processing, and even basic audit procedures. Tasks that once took hours now take minutes or seconds. AI tools like Xero, QuickBooks, and Receipt Bank are already automating bookkeeping, making it unnecessary for accountants to perform manual data entry.

This automation directly threatens many junior and transactional roles traditionally filled by entry-level CAs. As a result, there's a risk of job displacement unless professionals move up the value chain to roles that require more human judgment and strategic insight.

2. AI as an Advisory Tool

With AI’s ability to analyze massive datasets in real-time, generate forecasts, and offer financial advice, even traditional advisory roles are evolving. Tools such as IBM Watson and Microsoft Power BI can analyze trends and offer predictive insights that previously required human interpretation. This shift means clients might rely more on AI-driven dashboards than their accountant’s opinion unless the accountant can add higher-level strategic interpretation.

3. Threat to Compliance-Based Services

A substantial portion of accounting revolves around compliance—preparing taxes, ensuring regulatory adherence, and filing statutory returns. AI-enabled software is increasingly capable of handling these functions with minimal human input. For instance, cloud-based tax software can now automatically update in line with government regulations and complete filings with high accuracy, undermining one of the key services traditionally offered by CAs.

4. Changing Client Expectations

Clients are becoming more tech-savvy and are beginning to expect real-time insights, 24/7 access to financial dashboards, and predictive forecasting. This shift in expectations means that firms not leveraging AI may be seen as outdated or less competitive, further threatening traditional accountancy models.

5. Evolving Regulatory Environment

With AI automating more aspects of financial reporting, regulators are also adapting. New frameworks are emerging for the auditing of AI-generated reports and for the ethical use of AI in financial services. Chartered accountants who do not keep pace with these changes may find themselves unprepared or even legally exposed.

Remedies and Strategies to Adapt

While the threats posed by AI are real, the profession is far from obsolete. Chartered accountants can take proactive steps to not only remain relevant but also enhance their value in a rapidly evolving marketplace.

1. Upskilling and Reskilling

The most effective remedy against automation is human expertise that machines cannot replicate. Chartered accountants should focus on acquiring new skills in:

• Data analytics and visualization (e.g., Power BI, Tableau)

• AI and machine learning basics

• Strategic financial management

• Ethical and regulatory frameworks for AI

• Cybersecurity and data privacy

These skills will enable accountants to interpret AI outputs, detect anomalies, and offer strategic counsel that AI alone cannot provide.

2. Redefining the Role of the Accountant

Rather than focusing on data entry or number crunching, accountants should transition to roles that emphasize strategic planning, business consulting, financial modeling, and risk analysis. The human element- particularly in ethics, judgment, and decision-making—will always be essential and cannot be fully automated.

3. Integrating AI Tools into Practice

Instead of viewing AI as a competitor, accountants should treat it as a tool to increase efficiency. AI can help:

• Analyze financial data at scale

• Identify fraud and irregularities

• Automate repetitive tasks

• Enhance audit quality through better sampling techniques

By integrating AI into their workflow, CAs can focus more on client service and strategy.

4. Education Reform

Accounting curricula must be revised to include modules on AI and data science. Professional bodies like ICAEW, ICAB, and others should update certification programs to ensure that new entrants are AI-literate and ready for the future.

5. Ethical and Regulatory Leadership

Chartered accountants should play a leading role in defining the ethical use of AI in financial reporting, including transparency, accountability, and bias detection. Their deep understanding of standards and compliance makes them ideal candidates to govern AI frameworks responsibly.

Future Outlook: Risks and Opportunities

The future of accountancy in the age of AI is not bleak, but it will be different. The key question is not whether AI will impact the profession—it already has—but how accountants choose to respond.

Risks:

• Job losses in transactional roles

• Reduced demand for compliance-only services

• Pressure on fee structures due to automated competition

Opportunities:

• Expansion into advisory, strategic, and analytical services

• New roles in AI oversight and ethical governance

• Greater work-life balance through automation of mundane tasks

• Competitive advantage for early adopters of AI technology

Artificial Intelligence is not the end of the chartered accountancy profession, but it is a turning point. Those who cling to traditional models of practice risk obsolescence. However, those who embrace technology, commit to lifelong learning, and pivot toward strategic and analytical roles will not only survive but thrive.

The profession must evolve from compliance to consultancy, from record-keeping to insight-generation, and from reactive reporting to proactive strategy. AI may replace some roles, but it also opens up new possibilities that were previously unimaginable. The future belongs to those who adapt.