Risk > Regulatory Compliance

Credit risk

Credit risk

Credit risk is the possibility of incurring losses if debtors fail to meet their contractual obligations. Changes in credit risk are conditional on the economic and financial environment. In the case of Spain, economic recovery was consolidated and GDP grew by more than 3%. Against this backdrop of improved activity, lending to the resident private sector continued to recover. According to the Bank of Spain, in September 2016 lending to companies was up by 0.6% year-on-year, while loans to households, although the rate of decline eased, continued to be less than the previous year (-1.6%). Lending to the resident private sector on the whole was less than that of the previous year (-0.3%), although the trend towards recovery was consolidated during the year. 

In Spain, Bankinter once again increased lending to customers (up 5.9%) as well as the computable risk, which includes off-balance-sheet exposure (up 5.8%). The inclusion of the business in Portugal increased the computable risk by 16%.

Non-performing loans

Non-performing loans

The year ended with a non-performing loan ratio of 4.01%, which is 12 basis points less than that of the previous year (down 2.9%). The Bank's non-performing loan ratio is 43% of the sector average (9.23% according to Bank of Spain data in November 2016). At 31 December, the foreclosed asset portfolio was 523 million euros, which is 0.9% of total credit risk, down 1.5% year-on-year.

The total risk arising from doubtful assets was 2.3 billion euros, an increase of 257 million euros (12.6%). This increase is mainly the result of the inclusion of the business in Portugal in 2016, which had 438 million euros in doubtful assets at the end of the year, 88.9% of which were hedged with provisions. In Spain the balance of doubtful assets amounted to 1,859 million euros, down 8.9% year-on-year.

Distribution of the portfolio


Distribution of the portfolio

The Bank has been balancing the distribution of its lending portfolio between individuals and legal entities for years. In 2016, credit risk in Spain for individuals grew by 3.4% and that for legal entities by 8.2%. Computable risk for individuals was 50.7% of the total, and that for legal entities was 49.3%. The most important characteristics are described below by segments:

  • Individuals. In 2016 the housing market and the financial situation of households continued to improve. Against this backdrop, lending to individuals grew by 3.4%, thanks to traditional mortgage lending activity and the growing momentum of consumer loans. The individual lending portfolio amounted to 24.85 billion euros at 2016 year-end, with a non-performing loan ratio of 2.7%. The residential mortgage loan portfolio for individuals showed a loan-to-value (LTV) ratio of 63% at 2016 year-end and 89% are secured by the primary residence of the owners. The non-performing loan ratio of this portfolio was 2.6% at the end of 2016.
  • Corporate Banking. Investment in Corporate Banking grew by 5.5% to 14.1 billion euros, with a non-performing loan ratio of 1.8%. Bankinter devotes considerable attention to this segment, the business activities of which are more international and less exposed to Spain's economic cycle and which has a solid competitive position based on understanding the customer, flexibility and quality of service.
  • Small and medium-sized enterprises. This line of business has once again been especially buoyant, with growth of 10.3%. The portfolio stood at 11.3 billion euros, with a non-performing loan ratio of 6.5%. The Bank applies automated decision-making models for managing this segment, along with teams of highly-experienced risk analysts.
  • Developers. Bankinter maintains a very limited risk appetite in this segment, which forces the Bank to be very selective in its operations, which focus exclusively on first-class projects of solid development companies with a long history in consolidated areas. Developer lending ended the year at 1.3 billion euros, representing 2.3% of the Bank's credit risk, which is significantly less than the average exposure of the Spanish banking system.
  • Portugal. The Portuguese lending portfolio acquired from Barclays in 2016 contributed a total risk of 5.1 billion euros to the balance sheet, with a non-performing loan ratio of 8.70%, and with provisions recognised for 88.9% of doubtful assets. Bankinter's business plans in Portugal are based on the Bank's usual high lending standards.

Risk quantification models

Risk quantification models

Bankinter has used internal rating models as a tool for supporting its decisions regarding credit risk since the 90s. These models enable the Bank to assess the credit quality or solvency of transactions and customers and provide quantitative measurements of its credit risk. These models are mainly used to support approvals, set prices, quantify the coverage for impairment or provisions, monitor portfolios, support recovery and facilitate active management of the portfolios' risk profile.

The internal rating models provide homogeneous classes of solvency and internal ratings that group together customers and transactions with comparable credit ratings. These models are also calibrated to assess expected and unexpected losses of capital. These metrics are fundamental for managing and monitoring credit risk at Bankinter.

Bankinter has rating models both for retail segments (mortgages, consumer spending, SMEs, etc.) and wholesale segments, such as Corporate Banking. These statistical models are developed using information on customers, operations and macroeconomics, combined with expert analysis for the wholesale segment. The models are updated and monitored on a regular basis to ensure their power of discrimination, stability and accuracy under a strict governance structure. The Models Committee and the Executive Risk Committee are responsible for approving Bankinter's models. The Risk Committee also receives information on a regular basis on the status and monitoring of these models.

The distribution of exposure at default (EAD) by internal segments or categories is shown in the following graph.

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