Securitizations and structured products involve the repackaging of pools of financial assets (loans, mortgages, or other receivables) into tradeable securities. The emissions accounting challenge here is unique because the financial institution holds an interest in a pool of underlying assets rather than a single loan or investment. The applicable approach is a form of look-through extending through multiple layers of financial structure.
Asset Class Definition
This asset class covers:
- Asset-backed securities (ABS): Securities backed by pools of auto loans, consumer loans, or trade receivables
- Mortgage-backed securities (MBS): Securities backed by pools of residential or commercial mortgages
- Collateralised loan obligations (CLOs): Securities backed by diversified pools of corporate loans
- Other structured credit products where the financial institution holds a tranche of a securitised pool
The key common feature is that the financial institution's investment is in a structured vehicle (a special purpose entity) rather than directly in the underlying assets.
The Look-Through Principle
Like UoP structures, securitizations require a look-through approach: the financial institution looks through the structured vehicle to the underlying asset pool and applies the methodology appropriate to each asset type within the pool.
The look-through process works as follows:
- Identify the underlying asset pool: What types of loans or assets make up the pool? (mortgages, auto loans, corporate loans, etc.)
- Determine the tranche position: The financial institution holds a specific tranche (senior, mezzanine, equity). Its exposure is to that tranche's proportion of the pool.
- Apply the underlying methodology: For each type of underlying asset, apply the relevant PCAF chapter's methodology.
- Aggregate: Sum the attributed emissions across the pool.
ABS look-through example
A bank holds a 10% position in a $500 million auto loan ABS. The underlying pool consists of 50,000 car loans with an average outstanding balance of $10,000 each. The pool's total outstanding balance is $500 million and the total vehicle value at origination was $700 million.
For emissions calculation purposes, the bank looks through to the 50,000 underlying auto loans and applies Chapter 5.6 (Motor Vehicle Loans) methodology.
The bank's attributed share of the pool:
Attribution on pool level = $50M (the bank's 10% holding) / $700M (total origination value) = 7.1%
The bank then multiplies this by the estimated total annual emissions of all 50,000 cars in the pool.
Attribution Formula
The general formula for securitizations simplifies to:
Securitization Attribution Factor
Attribution Factor
The financial institution's proportional share of the underlying pool's emissions
Tranche Holding
The nominal value of the FI's position in a specific securitization tranche
Total Underlying Asset Value
The aggregate origination value of all underlying assets in the securitized pool
The full multi-layer formula is (Tranche Holding / Total Securitization Nominal) multiplied by (Total Securitization Nominal / Total Underlying Asset Value at Origination), but since the securitization nominal cancels out, the simplified version above is equivalent.
For a CLO, the total underlying asset value is the aggregate of the corporate borrowers' EVIC (for listed) or total equity + debt (for private) values.
Data Challenges
Securitizations present some of the most significant data challenges in PCAF:
Pool opacity: Older securitizations may not provide loan-level data. The financial institution may only know aggregate statistics about the pool (geographic mix, vintage distribution, collateral type).
Dynamic pools: Many securitizations have revolving pools where loans are continuously added and removed. The composition of the underlying pool may change significantly over the year.
Tranche complexity: Credit enhancement structures mean that different tranches have different expected loss profiles. The emissions attribution does not adjust for default probability; every tranche holder is attributed based on their nominal holding.
For older securitizations where loan-level data is unavailable, PCAF allows financial institutions to use the aggregate pool statistics (average loan size, geographic distribution, asset type mix) to estimate the portfolio emissions. This produces a Score 3 to 5 calculation, reflecting the lack of asset-specific data. Financial institutions should escalate to loan-level data as portfolio management systems improve.
MBS and Green Covered Bonds
For mortgage-backed securities, the look-through reaches residential or commercial mortgages, and the Chapter 5.5 or 5.4 methodology applies respectively. Green covered bonds (securities backed by green mortgages or energy-efficient commercial property loans) may also incorporate EPC data from the underlying loan pool.
Relationship to UoP Structures
Securitizations differ from UoP structures in one important respect: in UoP, the issuer designates specific projects. In a securitization, the pool is defined by loan characteristics (collateral type, vintage, geography) rather than by project purpose. There is no "green securitization" equivalent to a green bond in the current PCAF framework, though PCAF anticipates further guidance as sustainable securitization markets develop.
Securitizations are like buying a slice of a pizza buffet. When you paid for the buffet, you did not choose specific slices. Your responsibility for the carbon footprint of those pizzas is proportional to your share of the buffet, distributed proportionally across whatever was available in the buffet. The look-through methodology forces you to trace back through the buffet to what was actually consumed on your behalf.
Key Takeaways
- 1Securitizations require a look-through approach: identify the underlying asset pool, apply the relevant PCAF chapter methodology for each asset type, then aggregate
- 2The attribution factor simplifies to: tranche holding divided by total underlying asset value at origination
- 3Pool opacity is a major challenge - older securitizations may lack loan-level data, requiring reliance on aggregate pool statistics (Score 3-5)
- 4Dynamic revolving pools mean the composition of underlying assets can change significantly over the reporting year
- 5Credit enhancement and tranche structures do not affect emissions attribution - every tranche holder is attributed based on nominal holding regardless of seniority