Response to discussion Paper and Call for Evidence on SMEs and the SME Supporting Factor
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It is not possible to produce solid statistical analysis able to univocally identify the effects of the SF on credit price or on lending volumes for two reasons: in first place, historical data are of limited availability due to the recent introduction of the SF; in second place, and probably more importantly, any such analysis would be of difficult interpretation because of the multitude of different dynamics affecting lending trends which would offset/hamper/hide the impact of the SF on the final price/volume level.
Despite being difficult to quantify the exact price reduction triggered by the application of the SMEs supporting factor, a direct relation between the SMEs SF and the credit price is easy to draw as the cost of regulatory capital is one of the key components of the credit pricing models. The possibility of applying the SF on the eligible SMEs exposures significantly reduces the cost of regulatory capital for such exposures; this capital relief ensures a direct (positive) effect of the SF on the credit price for SMEs borrowers.
The table below (for formatting reasons tables can be found only in the file attached at the bottom of the page) presents the situation of the Group’s SMEs exposures at the end of June 2015. The application of the SF triggered an aggregate reduction of the total RWA of 7.2% (3.292 million Euros); the impact can be better appreciated if we consider the SMEs retail sector (where the SF is applicable to the whole portfolio, cfr Q3) where the RWA reduction was of 23.8% and 18.9% depending on the rating approach.
As stated above, through the formulas of the pricing models, there is a direct connection between the regulatory capital that the bank needs to hold with respect to each class of exposures and the conditions applied (price) to the related borrowers. In this view, any regulatory development which would trigger an increase in the capital requirements for SMEs exposures (e.g. removing the SF) will have the direct effect of worsening the credit conditions for SMEs borrowers.
We agree with EBA’s position that, during the recent crisis, the SMEs segment (both retail and corporate) showed higher default rates than the LCs sector. Our view is that the reason behind this dynamic lies in the booming period that large corporates have been experiencing during the last decade or so, as opposed to the late eighties/first nineties when default rates were relatively lower for SMEs.
For what concerns the specific ratios, our 10 years’ experience in rating Italian companies suggests that:
1) The more relevant ratios are not those directly related to profitability indicators (i.e. ebitda/total assets or ebitda/total debt);
2) The net-interest ratio and the total sales ratio are the ratios that perform better and, therefore, have the highest weight in our models;
3) The leverage aspect, covered by a measure of equity on total assets or total debt, performs better if calculated with tangible equity;
4) For the smallest companies (i.e. SME retail and SME Corporate with total sales under 2.5 mn), the balance sheet analysis has an accuracy ratio lower than the one of the corporate segment. For this reason we integrate the analysis with additional background information about the wealth of the owners/relevant managers of the company (i.e. ownership of real estate assets and/or financial assets). This information is used as a proxy for the true cash flow of the company, irrespective of the fact that this wealth is pledged - or not - by some form of guarantee.
On the contrary, if we compare the volatility of internal default rates calculated on exposures, we can identify a higher level of volatility for Corporate than for SME Corporate and SME Retail, suggesting that the Corporate segment is riskier than the other segments.
In order to appreciate the benefit in terms of price reduction that the SF is bringing to SMEs borrowers we report below (for the table with the details of the simulation see document attached) the pricing simulation of two analogous financing operations which differ only in the eligibility for the SF.
Both Case A and B refer to a 1 mn Euro unsecured “bullet” financing operation with 5 years maturity where the counterparty is an SME Corporate with turnover below 30 mn Euro. The only difference in the two simulations is that, while in Case A the exposure is not eligible for the SF being the total counterparty exposure with the Group set above 1.5 mn, in Case B the exposure was set eligible for the capital discount.
The result of this simulation is extremely interesting as it shows a considerable price discount (from 198 bp to 164 bp) caused exclusively by the application of the SF: the cost of the financing operation is, all the other factors being equal, reduced by 17.17% by the SF.
Q1: Do you have systems in place to track the reduction in capital due to the application of the SME Supporting Factor (capital relief)? Yes/No. Please explain and provide evidence.
Yes, we have. Our Regulatory Database identifies the SME exposures, subject to the application of the Supporting Factor, through a flag into a dedicated field.Q2: In your experience, is the reduction in capital requirements due to the application of the SME Supporting Factor (capital relief) being used to support lending to SMEs? Yes/No. Please explain and provide evidence.
Yes. The capital relief generated by the decrease in the RWA is crucial factor which enables the bank to offer loans at better conditions for SMEs borrowers.It is not possible to produce solid statistical analysis able to univocally identify the effects of the SF on credit price or on lending volumes for two reasons: in first place, historical data are of limited availability due to the recent introduction of the SF; in second place, and probably more importantly, any such analysis would be of difficult interpretation because of the multitude of different dynamics affecting lending trends which would offset/hamper/hide the impact of the SF on the final price/volume level.
Despite being difficult to quantify the exact price reduction triggered by the application of the SMEs supporting factor, a direct relation between the SMEs SF and the credit price is easy to draw as the cost of regulatory capital is one of the key components of the credit pricing models. The possibility of applying the SF on the eligible SMEs exposures significantly reduces the cost of regulatory capital for such exposures; this capital relief ensures a direct (positive) effect of the SF on the credit price for SMEs borrowers.
The table below (for formatting reasons tables can be found only in the file attached at the bottom of the page) presents the situation of the Group’s SMEs exposures at the end of June 2015. The application of the SF triggered an aggregate reduction of the total RWA of 7.2% (3.292 million Euros); the impact can be better appreciated if we consider the SMEs retail sector (where the SF is applicable to the whole portfolio, cfr Q3) where the RWA reduction was of 23.8% and 18.9% depending on the rating approach.
As stated above, through the formulas of the pricing models, there is a direct connection between the regulatory capital that the bank needs to hold with respect to each class of exposures and the conditions applied (price) to the related borrowers. In this view, any regulatory development which would trigger an increase in the capital requirements for SMEs exposures (e.g. removing the SF) will have the direct effect of worsening the credit conditions for SMEs borrowers.
Q3: Is your internal definition of SMEs in line with the definition of SME exposures subject to the SME Supporting Factor? Yes/No. If no, how are you reconciling the internal definition of SMEs with the definition of SMEs subject to Supporting Factor? Please explain and provide specific examples.
Our internal SMEs definition is not fully in line with the definition of SME exposures subject to the SME Supporting Factor. According to our definition, SME counterparties are sub-segmented into SME Retail and SME Corporate, according to the € 1 million threshold as required by the CRR. The Supporting Factor threshold is € 1.5 million and is, therefore, applied to SME Retail counterparties and only to a portion of the SME Corporate portfolio.Q4: In monitoring the total amount owed to you, your parent and subsidiary undertakings, including exposures in default, by the borrower and its group of connected clients (as defined in CRR Article 4(1)(39)), what reasonable steps do you take to ensure that amount does not exceed EUR 1.5 million in accordance with Article 501(2)(c)?
The identification of SME exposures subject to the application of the Supporting Factor is done by recalculating the thresholds at each reporting date. As foreseen by the regulation, the thresholds are calculated by considering the total amount owed to the institution and parent undertakings and its subsidiaries, including any exposure in default, by the obligor client or group of connected clients, but excluding claims or contingent claims secured on residential property collateral.Q5: Do you see merits in having a harmonised definition of SMEs for reporting purposes? Yes/No. Please explain and provide specific examples.
Within the Group, a single model for the SME sector is used, in accordance to the borrowers’ composition and in order to capture the business opportunities.Q6: Do you agree with the proposed measures of SME riskiness? Yes/No. Are some of these measures more relevant than others? Yes/No.
See Q7.Q7: Are other aspects relevant in your assessment of the creditworthiness/riskiness of potential SME borrowers? Yes/No. If yes, please provide a list of those aspects and explain how you measure SME riskiness.
On a general level, the approach used by EBA to analyse the riskiness of SMEs vs LCs covers the relevant area of the financial analysis.We agree with EBA’s position that, during the recent crisis, the SMEs segment (both retail and corporate) showed higher default rates than the LCs sector. Our view is that the reason behind this dynamic lies in the booming period that large corporates have been experiencing during the last decade or so, as opposed to the late eighties/first nineties when default rates were relatively lower for SMEs.
For what concerns the specific ratios, our 10 years’ experience in rating Italian companies suggests that:
1) The more relevant ratios are not those directly related to profitability indicators (i.e. ebitda/total assets or ebitda/total debt);
2) The net-interest ratio and the total sales ratio are the ratios that perform better and, therefore, have the highest weight in our models;
3) The leverage aspect, covered by a measure of equity on total assets or total debt, performs better if calculated with tangible equity;
4) For the smallest companies (i.e. SME retail and SME Corporate with total sales under 2.5 mn), the balance sheet analysis has an accuracy ratio lower than the one of the corporate segment. For this reason we integrate the analysis with additional background information about the wealth of the owners/relevant managers of the company (i.e. ownership of real estate assets and/or financial assets). This information is used as a proxy for the true cash flow of the company, irrespective of the fact that this wealth is pledged - or not - by some form of guarantee.
Q8: In your experience, are SMEs as cyclical or more/less cyclical than large enterprises?
We performed some analyses on the sensitivity of internal PDs to the economic cycle (estimated by the Bank of Italy default rates). In the case of the SMEs sector, it was not possible to identify a clear relationship. For Corporate, however, even if results are affected by a substantial level of statistical uncertainty, a positive link can be identified, showing that the model is, as expected, hybrid.On the contrary, if we compare the volatility of internal default rates calculated on exposures, we can identify a higher level of volatility for Corporate than for SME Corporate and SME Retail, suggesting that the Corporate segment is riskier than the other segments.
Q9: Do you agree with the proposed methodology to assess the own funds requirements in relation to SME riskiness? Yes/No. If no, please provide alternative methodologies or indicators, if available.
We agree with the approach of separating the two risk’s components: systematic (depending on asset correlations) and idiosyncratic. In this view, we would like to stress that the level of asset correlations implicit in Basel formulas leads to unrealistic capital requirements: this can be appreciated by the comparison between internal economic capital and regulatory capital. As a consequence of that, it is clear that the difference between the internal economic capital and regulatory capital will become even higher were the discount of the supporting factor abolished.Q10: Did the arrears and loss experience in 2009/2010/2011 exceed an (internal) limit? Yes/No. Were (expected/unexpected) losses adequately covered by loan loss provisions? Yes/No. Please explain and provide specific figures.
In 2009, 2010 and 2011, we did not apply the IRB Approach for SME Retail; we are applying the AIRB Approach on the SME Corporate portfolio since December 2010. In 2010 and 2011, the expected losses on non-performing loans were adequately covered by loan loss provisions.Q11: Do you agree with the above interpretation of statistical data on lending trends and conditions? Yes/No. If no, please explain.
Yes, our internal databases report figures and statistics mostly in line with the analysis of lending trends and conditions showed in the EBA discussion paper.Q12: Since 1 January 2014, have you changed your SME credit lending and assessment policies and procedures, specifically as a result of the introduction of the Supporting Factor? Yes/No. If yes, please explain and provide specific examples.
No. The policies and procedures of the Bank were taking into consideration the capital absorption in setting the credit limits already before 2014. The introduction of the Supporting Factor, therefore, did not affect the policies and procedures of the Bank but produced a difference in the credit limits (in terms of less centralization) for SMEs borrowers, at the same conditions.Q13: Have changes to your SME credit lending and assessment policies and procedures been driven by other factors (e.g. competition from alternative sources of SME financing as described in section 4.1)? Yes/No. Please explain and provide specific examples.
Yes. In particular, the Bank took part to many initiatives targeting SMEs lending set up by the State-owned development bank Cassa Depositi e Prestiti until the end of 2014.Q14: In your experience, is there an impact of the SME supporting factor on the volume of SME lending compared to other loans? Yes/No. Please explain and provide evidence.
We believe that the effect on volume is positive even though difficulty quantifiable. The impact of the Supporting Factor on SME volumes compared to other loans can’t be clearly quantified due to the lack of historical data and to the difficulty in disentangling the effects caused by the economic cycle and those due to the capital reduction.Q15: In your experience, is there an impact of the SME supporting factor on the pricing and overall conditions of SME lending compared to other loans? Yes/No. Please explain and provide evidence.
Yes. The pricing model of the Bank takes into consideration the cost of regulatory capital (capital absorption); a change in the calculation of capital requirements, therefore, is producing, at the same conditions, an improvement in the price applied to the SMEs borrowers.In order to appreciate the benefit in terms of price reduction that the SF is bringing to SMEs borrowers we report below (for the table with the details of the simulation see document attached) the pricing simulation of two analogous financing operations which differ only in the eligibility for the SF.
Both Case A and B refer to a 1 mn Euro unsecured “bullet” financing operation with 5 years maturity where the counterparty is an SME Corporate with turnover below 30 mn Euro. The only difference in the two simulations is that, while in Case A the exposure is not eligible for the SF being the total counterparty exposure with the Group set above 1.5 mn, in Case B the exposure was set eligible for the capital discount.
The result of this simulation is extremely interesting as it shows a considerable price discount (from 198 bp to 164 bp) caused exclusively by the application of the SF: the cost of the financing operation is, all the other factors being equal, reduced by 17.17% by the SF.