Company: BBVXF
Filing Date: 2025-02-27
Form Type: F-4/A
Source: 0001193125-25-037317
Chunk: 310

Company: BANCO BILBAO VIZCAYA ARGENTARIA, S.A.
Filing Date: 2025-02-27
Form: F-4/A
Chunk 310
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 of the customer (portfolio) and each one uses explanatory variables that uniformly catalogue all of the portfolio’s exposures. The purpose of the segmentation of models is to optimise the capture of customers’ default risk profile based on a set of common risk drivers. Therefore, the exposures of these segments can be considered to reflect a uniform collective treatment. The models for companies calculate PD at the borrower level and are fundamentally segmented according to the size of the company (annual turnover). The PD models for natural persons, including the self-employed, follow a segmentation that centres primarily on the lending product. Models broken down by product are available: mortgage and consumer loans, taking into account the purpose of the transaction (individual or business), credit cards and lines of credit. PDs are estimated at the contract level, meaning that a 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