Company: BBVXF
Filing Date: 2025-09-09
Form Type: 424B3
Source: 0001193125-25-198517
Chunk: 401

Company: BANCO BILBAO VIZCAYA ARGENTARIA, S.A.
Filing Date: 2025-09-09
Form: 424B3
Chunk 401
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 single borrower can have different PDs depending on the lending product being quantified. The models for Significant Increase in Credit Risk (SICR) carry out calculations at the contract level, in order to consider the characteristics specific to each transaction at the time of origination and at the present time. Where LGD is concerned, contracts with similar risk characteristics are grouped together for collective assessment, using the following segmentation hierarchy:

| – | By type of borrower: companies, developers and natural persons. |

| – | By type of guarantee: mortgage, unsecured, monetary/financial, and guarantors. |

| – | By type of product: credit cards, overdrafts, leases, credits and loans. |

Different LGDs are estimated for each segment, which are representative of the borrowers, of the recovery processes and of the recoverability assigned to each one based on the Institution’s past experience. Risk drivers The risk drivers or explanatory variables of models are the shared credit risk characteristics. In other words, they are common elements that can be used to rate borrowers in a homogeneous way within a portfolio and which explain the credit risk rating assigned to each exposure. Risk drivers are identified by means of a rigorous process that combines historical data analysis, explanatory power and expert judgment, as well as knowledge about the risk/business. The main risk drivers are presented here below, grouped together by type of model (PD, SICR and LGD). PD models use credit ratings or credit scores as input data (Internal Ratings-Based (IRB) models used for both risk management and capital calculations). They incorporate additional information to give a more faithful reflection of the risk at a given moment in time (point-in-time).For companies, the early warnings tool known as HAT and the credit rating are used. For individuals, the behavioural credit score is used. A description of these tools can be found earlier in this same note. In both cases, other recent risk deterioration events (refinancing, exit from default status, non-payments,lending restrictions) also explain the probability of default. The SICR models mainly use as an explanatory factor the ratio between the residual lifetime PD at the time of approval (i.e. for the residual life of the transaction but using the information existing at the time the transaction is originated) and the current lifetime PD (using the information existing at the present time). LGD models use additional risk drivers that enable a more in-depthsegmentation to take place. More specifically, for mortgage guarantees, the Loan-to-Value(LTV)