Securitization of (bad) loans to Italian SMES: The role of the public guarantee

Abstract

This study investigates the main factors driving the evolution of the securitization of loans to Italian small and medium-sized enterprises (SMEs). The value of securitization increased in last two years, even though it has not been used as collateral for central banks. The disposal of non-performing loans (NPLs) may have been rather triggered by increasing attention of the international institutions to such an issue, within the general purpose of financial stability. The purpose of this paper is to interpret such a phenomenon focusing on Italian banks and restricting the analysis to the case of securitizations backed with loans to small and medium-sized enterprises (SMEs). The interesting result that emerges, supported by econometrically tested empirical evidence, is that given the orientation of international financial institutions, such as the ECB and the EBA, and reacting to incentives coming from the fiscal policy authorities for the public guarantee of loans, banks have been using securitization to reduce the burden on their bad balance sheets due to (NPLs). It was found that the public guarantee had a positive impact on SME securitization, whereas securitization in other sectors has not been affected significantly. Such evidence suggests that, in the absence of a public guarantee, the financial stability target would have been at risk, and the effectiveness of collateral-based policies in the recent past must be improved to enhance access to credit for SMEs.

Shadow banking and non-performing loans: international evidence

“…The sample period is from 2002 to 2020. All variables are as defined in Table1Source: Authors' own creation/work country with the strand of previous literature, which shows that NPLs decrease with an increase in shadow banking activity in the country(Di Cesare, 2009;Affinito and Tagliaferri, 2010;Poschmann, 2012;Bittucci and Murè, 2021;Irani et al, 2021). Our evidence regarding the role…”

“…An obvious outcome of these activities (securitization or sale of loans to third parties) can be observed in NPLs. In this paper, we argue that since shadow banking can change the composition of the asset side of banks' balance sheets, it is expected that banks may engage in JFRC 32,2 shadow banking activities to reduce the burden of bad debt on their balance sheets (Bittucci and Murè, 2021;Affinito and Tagliaferri, 2010;Dell'Ariccia et al, 2012;Dahiya et al, 2003;Flannery, 1994). These banks may also engage in shadow banking to reduce the expected credit losses.…”

“…Furthermore, traditional banks may effectively reduce the amount of total risk-weighted assets both through securitization (Affinito and Tagliaferri, 2010; Poschmann, 2012; Bittucci and Murè, 2021) and by selling loans with higher risk-weights (Irani et al , 2021; Bolognesi et al , 2020). Since the expected losses related to NPLs are higher, such loans have higher risk weights and require more regulatory capital.…”

“…An obvious outcome of these activities is lowering NPLs on the bank’s balance sheet. Bittucci and Murè (2021) show that banks engage in shadow banking activities to reduce the amount of bad loans on their balance sheets.…”

Demand forecasting: AI-based, statistical and hybrid models vs practice-based models - the case of SMEs and large enterprises

“…As already mentioned by previous studies, SMEs have lower economic power (Metzker et al, 2021a), lower amount financial resources and assets (Civelek et al, 2020;Kliuchnikava, 2022;Rashed & Ghoniem, 2022), lower number of high quality workers (Hazudin et al, 2022;Siregar et al, 2022), more fragile structure (Civelek & Krajčík, 2022;Dvorsky et al, 2021) that cause them facing with more financial (Civelek et al, 2021;Ključnikov et al, 2021) and exporting problems (Ključnikov et al, 2022), higher costs (Çelik & Çevirgen, 2021;Bittucci et al, 2021;Msomi & Nzama, 2022), when implementing their market and financing decisions into the practice (Dvorský et al, 2020;Kocisova et al 2018;Samanta, 2022). In this regard, investigation of suitable statistical demand forecasting model for both SMEs and large enterprises might create a value addition for the related academic literature.…”