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Credit to industry in Spain grows 9%, according to a report

The report “Evolution of credit to companies in Spain 2022”, prepared by the consultancy AIS Group, shows that the credit portfolio to industry grew by 9% in the first half of 2022, reaching a total balance of almost 118,000 million euro. This is the highest rise among all the productive sectors, which ends the downward trend reduction of this portfolio experienced in 2021when it closed with a total of 109,893 million euros in outstanding loans.

It should be noted that industry is one of the sectors that has been most affected for the war in Ukraine, with the consequent decrease in inputs, especially raw materials, and by growing inflation, as a result of the increase in the cost of energy. This last effect implies a very hard blow for the sector that has increased its financing needs to face these higher costs.

As soon as to doubtful credits, the industry accumulates 17% of the total of them with a portfolio whose balance at the end of the first half of 2022 was slightly higher than 4,380 million euros, some 475 million euros below the figure of December 2021 and more than 765 million below June 2021. This has allowed the NPL rate to be lowered to 3.7%.

According to the AIS Group study, the trend already observed at the end of the 2021 financial year continues, and the general decreases in the volume of credits in practically all sectors, except for activities related to the primary sector (agriculture, livestock, fishing, hunting and forestry), commerce and industry, which have seen their portfolio balances grow.

Despite the variations, the weight of credit in each sector has barely varied from what is the usual framework. Thus, the bulk of the loans, 70%, go to companies in the service sector, while those granted to industry represent 20.7%. The construction concentrates 4.7% and the primary sector barely accounts for 4% of the total.

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Despite all the warnings of a foreseeable increase in default, the statistics do not yet reflect this rise. Rather the opposite, the balance of doubtful credits has decreased by almost 2,500 million euroswhich has caused a reduction of four tenths in the delinquency rate, which in the last year has dropped from 5% to 4.6%.

The industry is one of the sectors most affected by the scarcity of raw materials, the increase in its costs and the runaway price of energy, a situation that explains the growth of the sector’s indebtedness, aggravated by galloping inflation”, comments David Fernández, commercial director of AIS. “A scenario where the immediate future is marked by both inflation and the rise in interest rates from the European Central Bank”.

In the face of uncertainty, intelligence

According to David Fernandez, “In the current macroeconomic scenario, with a significant degree of uncertainty, artificial intelligence (AI) has become an invaluable tool to generate efficiency in credit risk management of the entities and keep it within the parameters desired by each entity”.

The ability of AI to analyze an infinite number of variables of a diverse nature and its high predictive power make it an ideal tool to automate processes, optimize resources and improve results. “Its application offers efficiency improvement rates in many cases greater than 25%”, says the director of AIS. “This improvement, evidently, is transferred to the business level, as it translates into increased contracting of products, evaluation and approval of a greater number of credit applications, reduction of the default rate, etc.”

The AI It can be implemented in many facets of risk management, but from AIS five very relevant applications stand out at the present time: open banking tools to have real-time information on clients (individuals or companies); machine learning models to have more accurate credit profiles; alert systems that give room for maneuver in situations of deterioration, avoiding falling into the increase in provisions; default recovery tools in which AI helps define profitability strategies; and balance projection systems that allow the Risk areas to predict the behavior of the companies that make up the portfolio, being able to simulate their evolution in different macroeconomic scenarios.

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