IN BRIEF:
• Central Philippines has again experienced extreme flooding, marking a significant escalation from historical patterns.
• Major floods can significantly increase the losses banks face from unpaid loans—especially when the property securing that loan, like a car, is damaged.
• As climate impacts worsen, Loss Given Default (LGD) estimates must be reviewed and/or adjusted to also reflect the increasing severity and frequency of future scenarios, such as extreme and recurring flooding events, on top of existing information.
Another Super typhoon, Uwan, is upon us even as communities try to recover the extreme flooding in the central Philippines from Typhoon Kalmaegi (Tino). These events are a significant escalation from historical patterns. Streets and communities that were previously considered safe were inundated, highlighting a new and expanded risk profile for these areas.
Internationally, extreme flood events have produced striking images of vehicles piled on streets or even lodged in trees, as well as significant river debris after flood surges. Such scenes have been reported following extreme floods in parts of Italy and Spain.
When a disaster strikes, damage to people and property is obvious. This article explains how major floods can significantly increase the losses banks face from unpaid loans — especially when the property securing that loan, like a car, is damaged. We’ll also discuss how banks must adapt their financial planning to prepare for this new reality.
This article intends to provide applications to Expected Credit Loss (ECL) modelling under IFRS 9 focusing on the Loss-Given-Default (LGD) dimension, and outlines practical adjustment approaches for banking risk management and modelling teams.
HOW FLOODED CARS INCREASE FINANCIAL RISK FOR BANKS
Motor-vehicle loans form a material slice of the Philippine consumer-loan market; according to the Bangko Sentral ng Pilipinas (BSP), motor-vehicle loans accounted for 29% of consumer loans in May 2025. When flooding inundates parking lots, highways or neighborhoods, vehicles become immediate loss magnets: damage to engines, electronic systems, interiors and structural components ensues. In major floods, vehicles may float away, collide or pile up, turning them into urban flood drifters.
Consequently, collateral that underpins vehicle-loan exposures can suffer abrupt impairment, potentially prolonging time to recover or causing a potential reduction in recoverability amount of loan collateral in the event of default. For banks subject to IFRS 9, this means LGD assumptions may need urgent review.
HOW FLOODING MAY ELEVATE LGD
Under IFRS 9, LGD represents the proportion of a loan’s exposure at the time of default that a lender expects to lose, and this is usually expressed as a percentage of the total exposure at the date default occurs. While LGD is influenced by the recoverable value of pledged collateral, it also reflects potential losses on any unsecured portion of the loan.
In consideration of climate risk events such as frequent super typhoons in a particular geography, here’s how a bank’s potential loss worsens:
• The collateral becomes worthless: A flood-damaged car, especially up to the engine or dashboard, is often declared a “total loss” worth almost nothing on the resale market.
• Repo costs go up: It costs more to tow, clean, and legally process a damaged vehicle, especially when recovery services are overwhelmed after a disaster.
• It takes longer to get any money back: The whole process of getting the car, processing insurance, and selling it at auction gets bottlenecked. The longer it takes, the less that “future money” is worth to the bank today.
• Everyone is selling at once: When thousands of cars are flooded in the same area, insurance gaps are exposed and the market for used cars and salvaged parts is saturated. This drives prices down, making it even harder for the bank to recover financially.
This results in conventional LGD considerations, built on historical default data, no longer being reflective of current and prospective market conditions. As climate impacts worsen, these parameters must be reviewed and adjusted to reflect the increasing severity and frequency of future climate scenarios, not just past events.
ILLUSTRATIVE CALCULATION
To illustrate the magnitude of potential LGD shifts following a severe flood event, consider a typical financed vehicle loan of about P700,000. The vehicle might have an initial market value of P1 million, and the lender could expect to incur around P50,000 in costs related to repossession and sale if the borrower were to default.
Let us assume:
• We are two years into a five-year loan when the borrower defaults
• For purposes of simplicity, that the FMV follows a straight-line depreciation rendering the vehicle pledged as collateral to have a FMV of P600,000 as of that time
• The collateral net recoverable value would be P550,000 after deducting costs to sell from FMV
• The outstanding loan balance at the end of year two is P450,000
Under normal circumstances, this would imply an LGD of 0%, as the recoverable amount, P550,000 is greater than the outstanding loan amount at default or Exposure at Default (EAD) of P450,000.
POST-SEVERE CHRONIC FLOODING CONSIDERATIONS
When a severe flood event submerges the vehicle and causes substantial engine or interior damage, the collateral value can plummet. Assume the resale value falls by about 60% — a stylized but conservative assumption drawn from studies indicating that flood-damaged or “salvage-title” cars typically lose 60-70% of their value.
This can potentially alter our assumptions to:
• Vehicle pledged as collateral to have a FMV of P240,000 (P600,000 reduced by 60% flood induced damage)
• The collateral net recoverable value would be P190,000 after deducting costs to sell from FMV (which currently conservatively assumes costs to sell remain the same)
Under severe chronic flooding circumstances, this would now imply a much higher LGD of 42%; as the recoverable amount, P190,000, is now much less than the outstanding loan amount at default or EAD of P450,000.
This simplified example underscores how quickly loss severity can escalate when collateral is physically destroyed or when markets for recovery and resale are impaired. While the exact figures will vary depending on insurance coverage, vehicle type, and the availability of salvage buyers, the directional effect is clear: catastrophic flooding can transform a once moderately secured exposure into one with very limited recoverable value.
RECOMMENDED ACTIONS FOR RISK TEAMS
Organizations can update risk models and governance in response to these events by taking practical action:
• Triage impacted accounts: Isolate vehicle-loan exposures within the affected zones. This can be achieved by overlaying geospatial flood data and insurance claim registries with the bank’s own portfolio data (e.g., branch geography). This assessment must account for both the borrower’s registered home address and their place of work, as vehicles may be at either location during a flood event.
• Segmentation by risk factors: Impacted accounts should be stratified based on key risk parameters. This includes differentiating exposures by vehicle age, loan-to-value (LTV) ratio, insurance coverage status, and the location’s specific flood-zone designation (e.g., high-risk vs. moderate-risk zone). High-risk sub-segments should be flagged for enhanced LGD adjustments.
• Collateral haircut calibration: The core of the adjustment involves recalibrating collateral values. Using empirical damage-curve studies and industry data on salvage or “total-loss” values, teams should apply conservative, evidence-based “haircuts” to the collateral value for the impacted segments.
• Scenario analysis and stress testing: Beyond immediate adjustments, banks must use this event as a basis for forward-looking scenario analysis. Teams should run simulations for moderate and severe future flood scenarios to quantify the incremental impact on IFRS 9 lifetime ECL provisions and overall capital adequacy.
• Enhanced disclosures: In line with IFRS 7 Financial Instruments: Disclosures and IFRS 9 Financial Instruments, banks must disclose the key judgments, model changes, and sensitivities related to natural disaster risk. This transparency is critical for explaining how these risks are integrated into LGD and ECL calculations and, ultimately, into capital and provisioning plans.
KEY CONSIDERATIONS FOR BANKS
With global greenhouse gas emissions remaining unabated, the increase in average temperatures means that climate change-induced extremes in the Philippines will continue to rise in frequency and severity. It is therefore critical that banks adopt a more systematic approach, recognizing these climate-related physical risks not as isolated operational events, but as fundamental credit-risk drivers that materially affect ECL assumptions under IFRS 9.
This evidence-based assessment cannot be limited to collateral-driven impacts on LGD, such as in the auto-sector. It must also address how these events affect the Probability of Default (PD) of their clients. Crucially, banks can no longer rely only on historical climate events; they must look forward, integrating future climate projections that model events with a magnitude and frequency far exceeding previous experiences.
By doing so, banks can better align their models with the emerging reality of climate-driven losses, resulting in more robust provisioning, deeper risk insight, and greater stakeholder confidence in their resilience.
This article is for general information only and is not a substitute for professional advice where the facts and circumstances warrant. The views and opinions expressed above are those of the authors and do not necessarily represent the views of SGV & Co.
Bonar A. Laureto is a Sustainability Principal and Melisa Turingan is a Sustainability Senior Manager, both of SGV & Co.