5 Costly Mistakes PLCs Make with IFRS S2
The introduction of IFRS S2 Climate-related Disclosures marks a pivotal shift in how Public Listed Companies (PLCs) must approach sustainability reporting. No longer just a voluntary exercise, climate disclosures are now a mandatory component of financial transparency—backed by regulatory enforcement from Bursa Malaysia and global investor expectations. Yet, despite the urgency, many businesses are falling into avoidable traps that waste time, inflate costs, and expose them to compliance risks.
Let’s explore the five most common—and costly—mistakes PLCs make when preparing IFRS S2 reports, along with actionable solutions powered by AI-driven sustainability reporting.
Mistake #1: Overlooking the Full Scope of Emissions Reporting
Many PLCs mistakenly assume that tracking Scope 1 (direct emissions) and Scope 2 (purchased energy) is sufficient for IFRS S2 compliance. However, the standard explicitly requires disclosure of Scope 3 emissions—those generated across the supply chain—if they are deemed material. Ignoring this requirement not only risks non-compliance but also leaves companies vulnerable to investor skepticism.
How Carbon Gen AI Helps:
Our AI-Sustainability Reporting (AI-SR) tool, designated for Bursa Malaysia’s CSI Platform, automates Scope 3 calculations by integrating procurement data and industry benchmarks. This eliminates manual errors and ensures audit-ready disclosures.
Mistake #2: Superficial Climate Risk Assessments
IFRS S2 demands forward-looking climate risk analysis, including scenario modeling (e.g., 2°C temperature rise impacts).
Many PLCs treat IFRS S2’s climate risk disclosure requirements as a box-ticking exercise, submitting generic statements like "We acknowledge climate risks" without substantive analysis. Avoid relying on templates, it results in disclosures that lack credibility. This approach fails both regulators and investors because:
- Physical vs Transition Risks:
- Physical risks (e.g., factory flooding) require location-specific vulnerability mapping
- Transition risks (e.g., carbon taxes) demand financial modeling of policy scenarios
Temporal Mismatch: Most companies analyze only current risks, while IFRS S2 requires 2-5 year forward-looking assessments tied to financial statements.
Data Scarcity: SMEs often lack access to climate projection models (e.g., IPCC datasets) needed for credible analysis.
How Carbon Gen AI Helps:
Our platform simulates climate risk scenarios using real-time data, predicting financial impacts on operations and supply chains—turning compliance into strategic foresight.
How? Because our platform integrates:
- Geospatial risk mapping (flood/fire projections for asset locations)
- Policy databases (simulating carbon pricing impacts)
- Automated financial impact scoring (EBITDA at risk under different scenarios)
Example: A Malaysian palm oil client discovered 12% of plantations were in high-flood-risk zones—intel that reshaped their insurance strategy.
Mistake #3: Relying on Manual Data Processes
Spreadsheets and email chains lead to version chaos and last-minute errors. IFRS S2’s granularity exposes these flaws, delaying submissions.
The True Costs of Manual Work
| Activity | Hours/Year | Hidden Costs |
|---|---|---|
| Data collection | 500+ | Delayed decisions from stale data |
| Version control | 200+ | Audit failures from unlogged changes |
| Stakeholder reviews | 300+ | Misaligned departments reporting different numbers |
Example: A mid-cap PLC recently spent RM 250,000 on consultant fees to reconcile conflicting emissions data—a cost avoidable with automation.
How Carbon Gen AI Helps:
By syncing with ERPs and utility meters, our AI-powered platform auto-fills disclosures in the correct format, cutting reporting time by 70%.
Mistake #4: Treating Compliance as a One-Time Exercise
Many PLCs treat IFRS S2 as an annual checkbox, missing opportunities to improve sustainability performance. Treating IFRS S2 as an annual compliance drill ignores its potential as a competitive lever. Here’s what proactive PLCs do differently:
From Compliance to Advantage
Investor Engagement: Companies like Sime Darby Plantation use quarterly ESG dashboards to attract green investors, reducing capital costs by 1.5-2%.
Operational ROI: AI-identified inefficiencies (e.g., compressor energy waste) can yield 20-30% utility savings.
Supply Chain Resilience: Continuous monitoring detects high-risk suppliers before they trigger Scope 3 non-compliance.
How Carbon Gen AI Helps:
Real-time dashboards track KPIs year-round, identifying risks early and turning compliance into competitive advantage.
Mistake #5: Underestimating Auditor Scrutiny
Vague claims without verifiable data trails trigger costly revisions. Auditors now treat IFRS S2 like financial statements. So what are the common pitfalls?
Audit Red Flags
🚩 "Estimated" data without methodology notes
🚩 Unsubstantiated net-zero claims (e.g., no carbon credit retirement proofs)
🚩 Inconsistent timeframes (FY2024 report using 2021 baseline data)
How Carbon Gen AI Ensures Audit-Proof Disclosures:
Automated Methodology Documentation: Every calculation includes citations (e.g., "Scope 2: GHG Protocol Market-Based").
Confidence Scoring: Rates data quality (e.g., "Supplier fuel use: 85% verified vs 40% estimated").
Version Control: Full history of report edits (who changed what and when).
Example: A property developer avoided RM 120k in audit rework after our system flagged incomplete tenant energy data pre-submission.
Final Takeaways
These mistakes reveal a stark truth: IFRS S2 compliance requires operational transformation, not just reporting.
As Bursa Malaysia’s designated solution, Carbon Gen AI embeds compliance into daily workflows—turning regulatory burden into investor confidence, cost savings, and climate resilience.
The Future of IFRS S2 Reporting is AI-Driven. As Bursa Malaysia’s AI reporting partner, Carbon GPT helps PLCs automate compliance, reduce costs, and unlock strategic insights.
🚀 Take Action Today:
Book a Demo to see our AI-SR in action.