The risk measurement and management models used by BBVA have allowed it to be a leader in best practices in the market and to be in compliance with Basel II guidelines.
The Bank quantifies its credit risk using two main metrics: expected loss (EL) and economic capital (EC). The expected loss reflects the average value of the losses. It is considered the cost of the business and is associated with the Group’s policy on provisions. Economic capital is the amount of capital considered necessary to cover unexpected losses if actual losses are greater than expected losses.
These risk metrics are combined with information on profitability in the value-based management framework, thus building the profitability-risk binomial into decision-making, from the definition of business strategy to approval of individual loans, price setting, assessment of non-performing portfolios, incentives to areas in the Group, etc.
There are three risk parameters that are essential in the process of calculating the EL and EC measurements: the probability of default (PD), loss given default (LGD) and exposure at default (EAD). These are generally estimated using historical information available in the systems. They are assigned to operations and customers according to their characteristics. In this context, the credit rating tools (ratings and scorings) assess the risk in each transaction/customer according to their credit quality by assigning them a score. This score is then used in assigning risk metrics, together with additional information such as transaction seasoning, loan to value ratio, customer segment, etc. The increase in the number of observed defaults in the current economic situation will help reinforce the soundness of the risk parameters by adjusting their estimates and refining methodologies. The incorporation of data from the years of economic slowdown is particularly important for refining the analysis of the cyclical behavior of credit risk. The effect on the estimate of PD and the credit conversion factor (CCF) is immediate. An analysis of the impact on LGD, however, requires waiting for the maturing of the recovery processes associated with these defaults. The current situation could be leading to a delay of the client recovery process and a change in his behavior pattern, which explains why the consequence of the crisis in the LGD estimates will be observed in the long term, although the LGD cycle adjustment, LRLGD (long run LGD), mitigates this effect.