Contents. Introduction Credit risk Market risk Operational risk Capital base Individual solvency requirement

Transcription

1 Risk Report 29 Page 29 1

2 Risk Report 29 Page 2 Contents Introduction Market risk Operational risk Capital base Individual solvency requirement

3 Risk Report 29 Page 3 Introduction INTRODUCTION TO THE 29 Risk Report Spar Nord is very much committed to risk management. Accordingly, the Bank publishes an independent risk report as a supplement to the risk section in Spar Nord s Financial Statements. The report is structured into the following sections: Market risk Operational risk Capital base Individual solvency requirement Policies, strategies and management of the various categories of risk are dealt with in the respective sections. Pursuant to the Basel II rules, the Bank is required to disclose comprehensive information, se Annex 2 to the Danish Capital Adequacy Order. The disclosures in the Risk Report concern Spar Nord Bank A/S, CVR no , Selagervej 15, P.O. Box 162, DK-91 Aalborg, and its fully consolidated subsidiaries. The Risk Report is published on Spar Nord s website.

4 Risk Report 29 Page 4 CREDIT RISKS is the risk of losses arising because counterparties fail to meet all or part of their payment obligations. Spar Nord s overall credit risks are managed pursuant to the Bank s credit policy, which is geared to strike a balance between earnings and risks, and to ensure that the risk assumption is always quantified. Spar Nord s policy is to have full insight into the customers financial health and paying behaviour before granting credit facilities. Also, creditworthiness - the customer s ability and will to meet current and future obligations - is a key parameter in all customer relations. Spar Nord aims to develop long-term relationships with customers and does not want to use risk appetite as a competitive parameter. Spar Nord only wants to conclude transactions that conform to good banking practice and do not jeopardize the Group s reputation and professional profile. As a basic rule, the Spar Nord does not grant loans and credit facilities based on collateral alone. Thus, the customer should show the will and have the ability to repay loans without the Bank having to realize the collateral. In its endeavours to ensure sound risk diversification of its credit exposure, Spar Nord has introduced some internal objectives. The Group does not want to be exposed to individual customers or industries that might solely and separately jeopardize its independence. Consequently, Spar Nord has introduced a cap on credit facilities at DKK 4 million, and the unsecured share of credit exposure may not exceed DKK 2 million in respect of any facility. This limit has been kept at all times. In determining the amount of exposure, due provision is made for the so-called particularly secure claims, which are stated in the Danish Financial Supervisory Authority s Executive Order on Large Exposures. The DKK 4 million cap does not apply to trading partners in the financial sector. CREDIT MANAGEMENT AND MONITORING Credit authorization is -granting powers are governed by two factors: the expertise of the individual Local Bank managers and the desire that the Credit Rating Department review a certain share of the authorizations from the individual areas. The decentralized credit authorization limits range between DKK 2 and 1 million. All facilities in excess of DKK 6 million are subject to authorization by the Supervisory Board. Customer advisers, in consultation with the individual managers, handle day-to-day management of the Bank s credit risks. Decentralized powers are allocated based on an assessment of need and expertise. If a credit facility exceeds the local loan approval limits, it will be passed on and dealt with by the Credit Rating Department, the Executive Board (the Credit Committee) or the Supervisory Board. Overall monitoring of the Group s credit risk exposure is managed by the Credit Quality function. This department monitors changes in the credit quality of all exposures and undertakes a systematic credit quality control of the Bank s entire exposure portfolio. Spar Nord has developed IT tools for controlling and monitoring credit risks. The Bank s credit analysis system is used for monitoring purposes, and key data regarding credit facilities and customers financial affairs are recorded in it. This is done to detect danger signals at an early stage. At the same time, changes in the credit quality of portfolios and organizational units are being monitored. As an element in the procedure, business customers are rated and retail customers credit scored based on risk analyses. Rating and credit scoring have been introduced in all the Bank s departments, and these tools are used at the local level to grant credit facilities. Thus, customers in the risk categories accorded the lowest risk exposure are likelier to be given higher credit limits or extensions than those with the highest risk exposure. In addition, the systems are used for managing overdrafts and for pricing purposes. CREDIT SCORING OF RETAIL CUSTOMERS AND RATING OF BUSINESS CUSTOMERS Retail customers are categorized into seven risk categories using behavioural data (with 1 being the best), and a separate credit watchlisted group has also been established. The model for scoring retail customers, which is based on the customers behaviour history, is used to quantify the likelihood that a loan will not be repaid and fall into default in the forthcoming 12-month period (the so-called Probability of Default, (PD)). This model is based on 1-2 variables that are picked from a comprehensive gross list as the ones that best describe previously defaulted loans. A statistically-based credit application scoring model is used to classify new borrowing customers according to risk. A smaller number of variables are used for credit application scoring than for behaviour scoring. Once a credit limit has been assigned, the models are adapted on a sliding scale, and after six months the shift to using behavioural data alone is completed. Business customers are divided into eight rating categories according to financial data (earnings, solvency ratio, etc.). The model is not based on statistical data, but could be termed an expert model of sorts. The above models are not yet used for all retail and business customers. Efforts are ongoing at Spar Nord to become an IRB bank according to the Basel II rules, but it is not yet ready to apply to the Danish Financial Supervisory Authority for permission to use its own models for the solvency calculation.

5 Risk Report 29 Page 5 In 29, a new statistically-based PD model for business customers was developed. This model will be used internally in for our risk management of business customers, starting in early in 21. Feedback from our use of the new model is positive. IMPAIRMENT All significant loans and advances and those slated for credit quality review are re-evaluated individually, and other loans are reviewed on a group basis. All loans and advances that have not been impaired on an individual basis are assigned to groups having uniform credit risk exposure. If the review discloses objective indications of impairment, an impairment loss is recognized. Impairment is calculated as the difference between the carrying amount of loans and advances and the present value of anticipated repayments on the loan. A credit facility need not be in default before impairment is recognized and approval procedures regarding any new extension of credit are tightened. Group impairment losses are recognized when objective indications show that expected future losses exceed the anticipated loss when the loan was granted. Accordingly, in addition to objective indications for a group, group impairment losses are basically recognized when customers are transferred to groups with a higher credit risk exposure. The rating and credit scoring constitute the primary sources of group allocationcustomer categorization, but customers slated for credit review without individual impairment provisions also make up a group. Doubtful loans - loans for which interest accruals have been suspended because full collection of the principal is unlikely or because no interest has been paid for an extensive period of time - are subject to special scrutiny, and if repayment is considered doubtful and loss unavoidable, the loan is categorized as partially or fully impaired and uncollectible. Interest on the parts of facilities that have been written down for impairment is not recognized as income. THE GROUP S LOANS, ADVANCES AND GUARANTEES The Group s total loans, advances and guarantees before setoff of impairment losses amounted to DKK 45.7 billion at end-29 compared with DKK 5.5 billion at end-28. Retail customers account for 37 of total loans, advances and guarantees and business customers for 63, equivalent to an increase in retail customers share of about 3 percentage-points on end-28. The largest portion of the reduction in credit exposure stemmed from the discontinuation of reverse transactions, accounting for DKK 2.2 billion, the approx. DKK 1.9 billion decline in credit exposure to business customers at the local banks and the approx. DKK.3 billion decline relating to retail customers at the local banks. Finally, the Bank recorded a DKK.8 billion drop in exposures to financial customers, while Finans Nord s slight increase in lending had the opposite effect. The development in credit exposure to retail customers at the local banks covers two contrary trends, viz. a decline in lending and an increase in guarantees stemming from arranging mortgage -credit loans. Lending to retail customers dropped by DKK 2.3 billion, and guarantees increased by DKK 2. billion. Apart from the reverse transactions that have been discontinued, no significant shifts in the breakdown by industry occurred from 28 to 29 as concerns the Group s loans, advances and guarantees. BREAKDOWN OF EXPOSURES BY BUSINESS AREA 5, 45, 4, 35, 3, 25, 2, 15, 1, 5, Figure 1 Loans, advances and guarantees, total Retail customers Local Banks Business customers Local Banks Financial customers Finans Nord A/S Customers are divided into four groups as part of the ongoing risk monitoring: Retail customers at the local banks, business customers at the local banks, financial customers and customers at Finans Nord. As appears from Figure 2fig. 1, in 29 the total credit volume declined in the three first areas, while it grew slightly for Finans Nord. 29 saw credit facilities further diversified with respect to size of facilities. The share of total loans, advances and guarantees attributable to large exposures was reduced, and the share attributable to <DKK 5 million facilities rose.

6 Risk Report 29 Page 6 THE GROUP S LOANS. ADVANCES AND GUARANTEES BROKEN DOWN BY SIZE OF FACILITY Broken down Number by Number Figure 2 Broken down by 28 38, , , , , , , , , , Retail customers at the local banks The Bank s credit exposure to retail customers at Spar Nord s Local Banks amounts to DKK 16.3 billion, equivalent to 35.7 of the Group s total loans, advances and guarantees. The breakdown on the above risk categories and the developments in them appear from fig 3. After a several-year period with sharp rises in the retail customer portfolio s credit quality, credit quality stagnated in 28 and 29, with the average credit quality tending to decline slightly. The average decline in the portfolio s credit quality is attributable to an increase in the number of credit-watchlisted customers. Thus, in 28 and 29 the average quality among the other risk categories improved compared with 27. The retail customer model comprises only customers in risk categories 1 to 7, as the retail customers in the credit-watchlisted group have been transferred to individual monitoring. Thus, the credit-watchlist flagging in the model is used as part of the default definition. Spar Nord has not yet developed so-called LGD-models, i.e. models that can predict losses when a customer is certain to default (Loss Given Default). Figures 6 and 7 below show how customers have migrated across risk categories during the past two years. The migration is shown as the percentage of customers migrating from one group to another, and the percentages are calculated based on the figure at the beginning of the year. The only exception is the top line, which shows customers who are not included in the model at the beginning of the year, primarily new customers. The tables clearly show that customer migration was heavier in 29 than in 28. Not only did more customers migrate to weaker groups, but the migration towards better groups also increased. The highlighted diagonal shows the share of customers in each risk category that stayed in the same group. The decline in stability can, for instance, be illustrated by risk category 7, where the share of customers that remained in the group from one year to another dropped from 26.8 to In general, Management considers the development in the retail customer portfolio satisfactory, in that it shows an almost unchanged average credit quality compared with the situation at end-27, a markedly improved lending margin and a distinct decline in the unsecured share of credit exposure. BREAKDOWN OF RETAIL CUSTOMERS BY RISK GROUP 3, 2,5 2, 1,5 1, 5 Figure Watchlisted Not scored In the past four or five years, during which ongoing back tests were performed, the model we are using has proved its worth as a highly accurate risk classification tool, capable of predicting default rates for a given year. The results of expected and realized default ratios during the past few years are shown in fig 4. As appears from the figure, the model predicted the number of defaults in 28 with high accuracy, while the closing figure for 29 was slightly higher than estimated. For 21, the number is expected to drop. ESTIMATED AND REALIZED NUMBER OF DEFAULTS, RETAIL CUSTOMERS of all customers in the model, beginning of year Figure Estimated number Realized number Unauthorized overdrafts are monitored on an ongoing basis at the Bank. During the past few years, this monitoring has been tightened up as a result of economic developments. Retail customers unauthorized overdrafts have been gradually reduced on a monthly basis during the past two years. Average unauthorized overdrafts have been reduced from some.9 to about.6 at end-29.

7 Risk Report 29 Page 7 DEVELOPMENTS IN UNAUTHORIZED OVERDRAFTS FOR RETAIL CUSTOMERS THE PAST TWO YEARS Figure 5 Unauthorized Linear (unauthorized overdrafts in of overdrafts in of loans loans & advances & advances) Business customers at Spar Nord s Local Banks The credit exposure to business customers at Spar Nord s Local Banks amounts to DKK 2.1 billion, equivalent to 44. of the Group s total loans, advances and guarantees. As appears from Figure 8 below, rating group 7 and the group of credit-watchlisted customers grew sharply in 29. This development was expected and reflects the fact that business customers are navigating rough waters in the current economic climate. As mentioned above, Spar Nord s rating model for business customers is not a statistical model showing default probabilities for individual groups. Actually, the model simply classifies customers in accounting terms based on their earnings performance and solvency. The model accords great weight to earnings, and a customer will automatically be downgraded from risk category 7 if its financial results for the past two years amount to a loss. RETAIL CUSTOMERS SCORE CLASSES No. of customers No model at beginning of year Deposits Not Default scored impairm. Default watchlisted Default loss Deposits Impaired Watchlisted Losses Figure 6 RETAIL CUSTOMERS SCORE CLASSES No. of customers No model at beginning of year Deposits Not Default scored impairm. Default watchlisted Default loss Deposits Not scored Impaired Watchlisted Losses Figure 7

8 Risk Report 29 Page 8 The model s highly restrictive approach to a combined loss record for the past few years on end accounts for the sharp growth in rating group 7. Previous back tests on the model have, in fact, shown that risk category 7 always came out with lower bad rates than expected, whether the number of customers or the amount of facilities was measured. Figs. 9 and 1 show business customers migration between rating groups during the past two years. As was the case for retail customers, the scope of migration increased, although to a lesser degree. As opposed to the situation in the retail customer area, the trend in migration was predominantly adverse for business customers, triggered by the above-mentioned growth in rating group 7, among other factors. BUSINESS CUSTOMERS BROKEN DOWN BY RATING GROUP 4, 3,5 3, 2,5 2, 1,5 1, 5 Figure 8 BUSINESS CUSTOMERS EXISTING MODEL No. of business customers Not rated Not rated Default impairm. Default loss Impaired Watchlisted Losses Figure 9 BUSINESS CUSTOMERS EXISTING MODEL No. of business customers Not rated Default 8 impairm Watchlisted Not rated Watchlisted Watchlisted Default loss Impaired Watchlisted Losses Figure 1

9 Risk Report 29 Page 9 As part of our endeavours to establish an even better-balanced and detailed risk classification, Spar Nord is currently working on implementing a new statistically based model, which will incorporate company profiles and behaviour variables in addition to accounting data. Figure 11 shows developments in business customer exposures, broken down by rating groups using the new rating model. The new model is based on statistical probabilities, which also applies to the credit scoring model used for retail customers. The new model classifies risk significantly more accurately, and provides a breakdown on rating groups that is closer to a Gaussian distribution. Another characteristic feature is the distinctly larger difference in terms of default probabilities for the individual rating groups, and that the three poorest rating groups show significantly higher default probabilities. BUSINESS CUSTOMERS BROKEN DOWN BY RATING GROUP - NEW MODEL 6, 5,5 5, 4,5 4, 3,5 3, 2,5 2, 1,5 1, Not rated take into account the financial statements presented for the period impacted by the current recession. At the beginning of 21, the model will be updated based on experience from 29 and macro figures. ESTIMATED AND REALIZED NUMBER OF DEFAULTS, BUSINESS CUSTOMERS NEW SCORING MODEL of all customers in the model, beginning of year Figure Estimated number Realized number Over the past two years, business customers unauthorized overdrafts have remained at an unchanged low level of about.45 of lending to business customers in the local bank regions. This development is considered highly satisfactory, particularly in light of economic trends. It appears from the figure that the last month in a quarter is the month having the highest amount of unauthorized overdrafts. The level reaches almost.6, but these peaks are declining, as can be seen from the figure. Authorized overdrafts have dropped for both retail and business customers during the same period. Figure 11 The new model also shows a rising risk level for 29, as did the existing model. A back test conducted on the new model for business customers covering the period shows that the realized number of defaults matches the estimated number of defaults fairly accurately, and that the number of defaults was much higher than estimated for 29. The actual number of defaults grew from 1.6 in 28 to 3.5 in 29, compared to the estimated increase to 1.9 based on the model. One explanation for the sharp default rate growth is that the new model includes impairment in its default definition, and that the relatively sharp increase in impairment thus pushes up its default rate. The model was developed based on customers financial statements covering the period 21-27, for which reason it does not DEVELOPMENTS IN UNAUTHORIZED OVERDRAFTS FOR BUSINESS CUSTOMERS THE PAST TWO YEARS Figure 13 Unauthorized overdrafts Linear (unauthorized in of loans overdrafts in of loans & advances & advances)

10 Risk Report 29 Page 1 FINANS NORD Finans Nord s total credit exposure amounted to approx. DKK 7.7 billion, equivalent to 17 of the Group s total loans and advances. In line with Spar Nord Bank s policy, Finans Nord s credit application processing is based on an assessment of the customers ability and will to meet their current and future obligations. Compared with Spar Nord Bank, the situation is different for the leasing company Finans Nord, in that it always has security in the assets, either through ownership or charges. Thus, the credit portfolio held by Finans Nord is composed of 91 lease contracts and 9 asset purchase financing and loans. The agricultural and transporting industries constitute the two largest categories for Finans Nord. While the leasing performance was fairly good for the agricultural industry in 29, the transport area presented major challenges, with customers encountering financial difficulties that forced Finans Nord to repossess equipment and recognize impairment losses. The number of customers in financial difficulties has risen sharply in another core area, viz. the industrial sector. Finans Nord recorded an overall impact of impairment on the income statement in the amount of DKK 116 million, representing 1.5 of average loans and advances. FINANS NORD S LOANS AND ADVANCES BY INDUSTRY 2, 1,75 1,5 1,25 1, Figure 14 Public authorities Agriculture, etc. Manufacturing, etc. FINANCIAL CUSTOMERS Building and construction The Bank s credit exposure to financial customers is DKK 1.6 billion, equivalent to 3.5 of the Group s total loans, advances and guarantees. The exposure primarily consists of foreign loans to customers at other banks that request the provision of a guarantee. IMPACT ON THE INCOME STATEMENT FROM IMPAIRMENT OF LOANS AND ADVANCES The impact on the income statement from impairment of loans Trade, etc. Transport, etc. Credit and financing Property man. and letting Other business areas Retail customers, total and advances amounted to an expense of DKK 692 million, DKK 17 million of which is attributable to the Danish Banking Sector Emergency Fund (Bank Package 1). At the beginning of 29, impairment of loans and advances was expected to impact the income statement by about of total loans, advances and guarantees. After Q1, the forecast was adjusted upwards to The impact on the income statement for the year ended at As concerns impairment, there was a predominance of business customers in relative terms, including with respect to the categories Agriculture and Trade, etc. and Manufacturing, which accounted for the largest shares. Since end-28 the agricultural industry s share has doubled. Groups of impairment losses break down as follows: retail customers accounted for DKK 49.4 million, and business customers for DKK 59.5 million. 66 of the impact on the income statement for the year contributes to increasing the Group s impairment allowance account, now accounting for about 2.2 of the total credit exposure at the close of the year. At the beginning of the year, the impairment allowance account represented 1.1 of total credit exposure. For the Group, the total impact on the income statement amounted to DKK million for 29 when the expenses for the Danish Banking Sector Emergency Fund are not taken into account. Of this impact, DKK 387 million, corresponding to more than 66, has contributed to an increase in the allowance account for impairment losses, which grew from DKK 583 million to DKK 97 million at end-29 if contributions to the Danish Banking Sector Emergency Fund are excluded. If these contributions are included, the impairment balance at end-29 amounted to DKK 1,1 million. As expected, the total credit portfolio rose in terms of risk during 29. This increase was followed by a sharp increase in the lending margin on the overall portfolio. THE GROUP S LOSSES AND IMPAIRMENT Losses, incl. losses covered by provisions/impairment Losses on sector-targeted solutions Loss guarantee, the Bank s pension pool 4 Covered by provisions/impairment Losses not covered by provisions/impairment New provisions/impairm., excl. sector-targeted solutions New provisions for sector-targeted solutions Reversal of provisions/impairment Interest on impaired loans and advances taken to income New provisions/impairment, net Recoveries on loans written off as uncollectible Impact on income statement Losses and provisions for credit inst. and other losses impact on income statement - of which sector-targeted solutions Impact on the income statement, excl. sector-targeted solutions Figure 15

11 Risk Report 29 Page 11 THE GROUP S DEVELOPMENTS IN LOSSES AND IMPAIRMENT AND NON-PERFORMING LOANS Loans, advances and guarantees, gross, year-end 45,431 5,543 45,65 Losses and impairment for the year in of loans, advances and guarantees Impairment balance ,1 - in proportion to loans, advances and guarantees Impairment balance, excl. sector-targeted solutions in proportion to loans, advances and guarantees, year-end Non-performing loans, year-end in of loans, advances and guarantees Impairment balance in of non-performing loans 1,644 1,263 1,68 Figure 16 IMPAIRMENT AND LOSSES BY INDUSTRY 29 Industry group Building and construction Property man. and trade, business service Fisheries Manufacturing businesses, raw materials extraction, etc. Trade, restaurants and hotels Credit and financing and insurance activities Agriculture and forestry Retail customers Transport, postal services and telecommunications Other business areas , Figure 17 Past due and impaired Value adj. and impairment * *) The Group s total value adjustments and impairments must be supplemented by groups of impairment amounting to DKK 19 million and impairment in the amount of DKK 13 million regarding the the Danish Banking Sector Emergency Fund. IMPAIRMENT AND LOSSES BY INDUSTRY 28 Industry group Amounts expensed Building and construction Property man. and trade, business service Manufacturing businesses, raw materials extraction, etc. Trade, restaurants and hotels Credit and financing and insurance activities Agriculture, forestry and fisheries Public administration Retail customers Transport, postal services and telecommunications Other business areas , Figure 18 Past due and impaired Value adj. and impairment * *) The Group s total value adjustments and impairments must be supplemented by groups of impairment amounting to DKK 83 million and impairment in the amount of DKK 23 million regarding the the Danish Banking Sector Emergency Fund. Amounts expensed THE GROUP S EXPOSURES AND IMPAIRMENT BY INDUSTRY Industry - Figure 19 DEVELOPMENT IN THE GROUP S CREDIT QUALITY Management considers overall development in credit quality in 29 to be satisfactory in light of business trends. Moreover, it is satisfactory that the increase in risk level has been countered by the widened interest margin and the strengthened impairment allowance account. COLLATERAL Sector 28 Publ. administration Agriculture, etc. Fisheries, etc. Manufacturing, etc. Building and construction Trade, etc. Transport, etc. Credit and financing, etc. Property man., etc. Other business areas Business customers, total Retail customers, total , *) Only individual impairment The Group 28 The Group 29 Impairm. * The Group 29 Whenever possible, Spar Nord wants to reduce the risk attaching to individual exposures by accepting collateral, such as mortgages and charges over physical assets, securities and guarantees, etc. Mortgages on real property, securities and vehicles make up the most common type of collateral. Mortgages on property make up by far the most important collateral type provided to the Group. In this connection, it should be noted that even if these properties are located throughout Denmark, only a very small share is located in the Aarhus area and on Zealand, where housing prices have dropped the most. See fig. 24. The bulk of mortgages on property relate to private housing. Spar Nord continuously monitors the value of the collateral furnished. If the risk attaching to a counterparty increases, the collateral is subjected to a particularly critical scrutiny. The value is assessed based on the expected price to be fetched in a compulsory sale of the collateral, less any expenses arising from its realization. Collateral that may be used for credit risk mitigation purposes under the standardized approach is included for the purpose of calculating the Group s solvency ratio. The figures are shown after a reduction to reflect volatility adjustments.

12 Risk Report 29 Page 12 The unsecured share of the Group s credit exposure declined from 52.5 to 44.2 in 29. The decline is attributable partly to growth in guarantees connected with mortgage-credit lending, and a general increase in collateral, both as concerns new exposures and existing ones. In addition, the collateral situation is unchanged for many customers, and the exposures have also declined in volume. The Group s credit exposure broken down by unsecured share of credit exposure Unsecured share of credit exposure < > 75 Average unsecured share of credit exposure Spar Nord Bank A/S The Group 29 Spar Nord Bank A/S The Group CREDIT-MITIGATING FINANCIAL COLLATERAL Type of collateral Properties Custody account / securities Guarantees / sureties Vehicles Cash Other collateral Other collateral, total Partic. sec. transactions (mortage-credit guarantees) Secured, total, excl. Finans Nord Collateral, Finans Nord Figure , ,37.8 2,23.7 4, , , , , , , ,11. 17, , , , ,27.6 Figure 2 The largest drop in the unsecured share of credit exposure is seen among retail customers - a decline attributable primarily to an increase in business volume connected with the arrangement of mortgage-credit loans. The low unsecured share for the industry, Transport, etc. is due to the hefty share of Finans Nord s exposures to this industry. BREAKDOWN OF THE GROUP S CREDIT EXPOSURE BY UNSECURED SHARE OF CREDIT EXPOSURE (IN ) AND DKK MILL., BY INDUSTRY Industries Publ. authorities Agriculture, etc. Fisheries, etc. Manufacturing, etc. Building and construction Trade, etc. Transport, etc. Credit and financing, etc. Property man., etc. Other business areas Business customers, total Retail customers, total Average Figure , , , , , , , , , , , , , , , , , , , The reason that the property value under mortgages broken down by property type is calculated at DKK 11.7 billion and that only DKK 8.7 billion is recorded as security on the properties (fig. 22) is that the DKK 11.7 billion is the amount mortgaged to the Bank and recorded as collateral, while the DKK 8.7 billion is the share actually used for calculating collateral regarding a facility; some facilities are smaller than the collateral value, and collateral has also been provided by customers who do not currently have any facilities. MORTGAGES WITH POSITIVE EQUITY Private housing Summer cottages Agriculture Offices and businesses Miscellaneous Figure 23 5 Share in in DKK bn GEOGRAPHICAL BREAKDOWN OF MORTGAGES - END 29 DKK bn Figure shows total collateral broken down by category and Finans Nord. It can be clearly seen from Finans Nord s collateral that the collateral, which primarily consists of leased assets, that it has been downgraded. Assets are valued on an ongoing basis, and the collateral values are reduced as and when market prices are estimated to decline Zealand Århus Rest of the country Figure 24

13 Risk Report 29 Page 13 Spar Nord uses the Basel II standard approach to calculate the solvency ratio. The following figures show the financial collateral that has given solvency relief under these rules. CREDIT RISK MITIGATION BY VIRTUE OF FINANCIAL COLLATERAL 29 Industry Central governments or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exposures secured by mortgages on real property Exposures in default or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, including assets without counterparty risk , ,246 4,954 Figure 25 CREDIT RISK MITIGATION BY VIRTUE OF FINANCIAL COLLATERAL 28 Industry Central governments or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exposures secured by mortgages on real property Exposures in default or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, including assets without counterparty risk Exposure covered by guarantees Exposure covered by guarantees On-balancesheet netting On-balancesheet netting Other financial security Other financial security , ,58 1, , ,972 BREAKDOWN BY INDUSTRY Figure 16 breaks down the Spar Nord Group s loans, advances and guarantees by industry. Compared with the average for the Danish banking sector, a relatively larger share of Spar Nord s loans, advances and guarantees is attributable to retail customers, while Spar Nord has a lower-than-average share of loans, advances and guarantees attributable to credit, financing and manufacturing businesses. Finally, the Spar Nord Group has a larger-than-average exposure to the agricultural industry. THE GROUP S LOANS, ADVANCES AND GUARANTEES BROKEN DOWN BY INDUSTRY 2, 15, 1, 5, Figure 27 Building and construction Property man. and trade, etc. Manufacturing, etc. Trade, etc. Credit and financing, etc. Agriculture and forestry Fisheries Public administration Retail customers Transport, etc. Other business areas Figure 26

14 Risk Report 29 Page 14 In this report we focus specifically on two industries, viz. the agricultural and the real property sectors. The agricultural industry has been chosen because Spar Nord expects this sector to have a major impact on operating results in 21 as well. The real property sector helped trigger the problems experienced by a number of Danish banks in the past two years. Agriculture Agriculture is an important sector for both Spar Nord Bank and Finans Nord and accounts for 12.5 of the Group s total credit exposure. The total credit exposure amounts to DKK 5.7 billion, broken down on 3,6 customers. Of this amount, 1,1 customers account for total facilities of DKK 4. billion, and 2,5 customers at Finans Nord represent a combined volume of DKK 1.7 billion. The total unsecured share of the credit exposure to the industry has been reduced from 48.2 at end-28 to 36.5 at end-29. For both Finans Nord and Spar Nord Bank, agriculture has been a sector that has only caused very moderate losses for many years. BREAKDOWN OF EXPOSURE TO AGRICULTURAL LENDING BY SCORING CATEGORIES, NEW MODEL 1, 8 The Bank s total impairment losses on the agricultural industry cover 8 of the unsecured share of the credit exposure to the two weakest scoring categories at end-29. Figure 29 shows the credit quality development for agricultural customers at Spar Nord s Local Banks during the period from 27 to 29. The model used is the Bank s new agricultural model, which represents an adjusted version of the new business model. As appears from the figure, there is a distinct trend towards the highly risk-prone groups. However, in the big perspective the Group s portfolio of agricultural exposures is considered to be sound and characterized by satisfactory diversification in terms of production lines. Nonetheless, Spar Nord is aware that the sector is facing massive problems, a profitable business being very difficult to run given the prices that can currently be fetched on agricultural produce, particularly milk. Thus, it has been necessary, and will remain so in future, to finance operating losses for farmers who report satisfactory breakeven turnover and realistic and sound budgets. The real property industry The real property industry has proved to be highly risky in recent years on account of the adverse price developments on the market. For a number of years, Spar Nord has been reluctant to assume exposures to property sector customers, and the Group s exposure in this regard extensively consists of customers with long-term relations with the Bank and wide experience in the sector Figure Not scored During 29, the Group cut its combined exposures to customers in the real property industry by about DKK.4 billion to some DKK 5.6 billion, equal to 12.3 of total loans, advances and guarantees. At end-29, the impairment ratio for the industry as a whole stood at 1.4 against a beginning-of-year comprehensive impairment balance of.5. For 29, total losses on customers in the industry amounted to about DKK 24 million. CREDIT EXPOSURE OUTSIDE THE TRADING PORTFOLIO, INCL. COUNTERPARTY RISK Finans Nord did not experience any sharp increase in 29, either, in terms of losses and impairment of equipment leased by customers in the agricultural sector, whereas Spar Nord Bank recorded problems among a large number of agricultural businesses, particularly in the cattle industry. A comprehensive statement of the Group s credit risk shows an exposure of DKK 75.7 billion. The statement corresponds to the Group s credit risk, which is treated according to the standardized approach, with assets and off-balance-sheet items being included. The Group s total individual impairment losses on customers in the agricultural sector amounted to about DKK 16 million at end-29. However, the losses realized on customers in the sector remain at a very low level, with a loss of some DKK 24 million being recorded in 29.

15 Risk Report 29 Page 15 The total credit exposure is the sum total of: Loans, advances and receivables Guarantees Unutilized credit limits Credit commitments Equity investments in group enterprises Non-current assets Intangible assets Other property, plant and equipment Counterparty risk The breakdown of the Group s credit exposure by industry is based on a coding system used in DB7 - the new industry codes published by Statistics Denmark. The industry grouping is supplemented with a breakdown by retail customers, central bank and fisheries. TOTAL CREDIT EXPOSURE Central governments or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exposures secured by mortgages on real property Exposures in default or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, including assets without counterparty risk Figure ,166 2,313 5,71 6, ,878 6,62 2,281 27,736 32,997 32,388 4,699 5,482 1,35 1, ,766 1,674 75,673 83,888 TOTAL CREDIT EXPOSURE BY INDUSTRY 29 Industry Exposure category Building and construction Property man. and trade, business service Fisheries Manufacturing businesses, raw materials extraction, etc. Trade, restaurants and hotels Credit and financing and insurance activities Agriculture and forestry Danmarks Nationalbank (central bank) Public administration Retail customers Transport, postal services and telecommunications Other business areas Grand total Central gov. or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exp. secured by mortgages on real property 58 1, ,42 4,749 2, , ,497 1, ,765 3,71 2, , ,26 1, ,3 12,138 2,943 3, ,782 1, ,172 4, , ,791 17,58 2, , , , ,565 2, ,351 1,166 5, ,878 2,281 32,997 4,699 1, ,766 75,673 Exp. past due or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, incl. assets without counterparty risk Grand total Figure 3 TOTAL CREDIT EXPOSURE BY INDUSTRY 28 Industry Exposure category Building and construction Property man. and trade, business service Manufacturing businesses, raw materials extraction, etc. Trade, restaurants and hotels Credit and financing and insurance activities Agriculture, forestry and fisheries Public administration Retail customers Transport, postal services and telecommunications Other business areas Grand total Central gov. or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exp. secured by mortgages on real property 774 2, ,46 1 4,796 1, , ,677 1, ,4 3,225 1, ,349 2,312 6,56 4, ,527 16,311 3,552 3, ,233 6, ,314 1,369 17,71 3, , ,697 1, , ,69 2, ,31 2,313 6, ,62 27,736 32,388 5,483 1, ,674 83,888 Exp. past due or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, incl. assets without counterparty risk Grand total Figure 31

16 Risk Report 29 Page 16 AVERAGE VALUE OF EXPOSURES BY EXPOSURE CATEGORY Central governments or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exposures secured by mortgages on real property Exposures in default or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, including assets without counterparty risk Ave. 29 Ave. 28 1,83 1,55 6,14 5, ,317 7,339 21,43 26,855 32,11 29,864 4,846 4,485 1,522 1, , ,755 1,476 76,413 8,336 The Group s credit exposure by the debtor s country of residence is primarily delimited geographically to Denmark. In 29, debtors based in Denmark accounted for about 95 of the Group s credit exposure, for which reason a geographical breakdown is not considered important. Breakdown by term to maturity of the Group s credit exposure is shown by exposure categories. Figure 32 EXPOSURE CATEGORIES BY TERM TO MATURITY Exposure categories Central governments or central banks Regional or local authorities Public entities Institutions Businesses, etc. Retail customers Exposures secured by mortgages on real property Exposures past due or overdrawn Short-term exposures to institutions and businesses, etc. Collective investment schemes Exp. in other items, including assets without counterparty risk Grand total Figure 33 On demand On demand - 3 mths. - 3 mths. 3 mths. - 1 year 3 mths. - 1 year 1 year - 5 year 1 year - 5 year Over 5 years Over 5 years Grand total Grand total , ,166 2,313 1, ,767 4,6 3, ,71 6, ,76 1, , ,274 7,878 6,62 6,33 7,77 4,794 3,32 3,572 7,149 2,639 3,848 2,973 5,937 2,281 27,736 3,642 4,117 5,617 2,395 6,67 4,111 8,746 7,243 8,322 14,522 32,997 32,388 1,223 1, ,666 2,81 4,699 5, ,35 1, ,766 1,674 12,926 16,256 17,879 9,175 13,562 18,466 16,819 14,189 14,487 25,636 75,673 83,888 REAL PROPERTY RISKS Properties are recognized at cost upon acquisition and subsequently measured at fair value. The fair value is calculated on the basis of current market data according to an asset return model that includes the property s rental income, operating expenses, as well as management and maintenance. Operating expenses and maintenance costs are calculated on the basis of the condition of the individual property, construction year, materials used, etc. The fair value of the property is determined based on the calculated return on operations and the individually determined rate of return. The return rate is fixed on the basis of the location of the individual property, potential use, the state of maintenance, etc. The fair value of the individual property is reassessed at least once a year based on the current letting market and the interest level. An external valuation has been obtained from a real estate agent to support the calculation of fair value, including the rental rates and rates of return used. In 29, revaluations of corporate properties totalled DKK 2 million, recognized in equity, and impairment totalled DKK 17 million, recognized as costs. Reference is made to the Bank s Financial Statements for a more detailed description of the accounting treatment of properties.

17 Risk Report 29 Page 17 CREDIT EXPOSURE TO FINANCIAL COUNTERPARTIES As part of its trading in and holding of securities, foreign currency and derivative instruments and its payment services, etc., the Bank will experience settlement risk or credit risk exposure to financial counterparties. Settlement risk is the risk that the Bank may not receive payments or securities that match the securities or payments delivered by it whenever it settles securities transactions or enters into foreignexchange transactions. FINANCIAL CREDIT RISK, TOTAL AAA AA A CCC Non-rated Undistributed Figure 36 1, , , RECEIVABLES FROM CREDIT INSTITUTIONS BY TYPE CALCULATED AS RISK PORTFOLIO Certificates of deposit Reverse transactions Unlisted CDOs Deposits and unlisted bonds Subordinated loans Current accounts Market value of derivatives Undisclosed , , , Bond portfolio The Group s bond portfolio is the most significant source of financial credit risk. Spar Nord s bond portfolio is composed of 9.3 of mortgagecredit bonds, 8.7 of bonds from financial issuers and 1. from other issuers. Corporate bonds amount to DKK 128 million, the bulk of which are Scandinotes. The Bank still expects that tranches of senior loans will be repaid. Figure 34 RECEIVABLES FROM CREDIT INSTITUTIONS BY RATING CATEGORY CALCULATED AS RISK PORTFOLIO AAA AA A Non-rated Undistributed Figure 35 3, , BOND PORTFOLIO BY ISSUER TYPE CALCULATED AS RISK PORTFOLIO Government bonds Mortgage-credit institutions Financial issuers CDOs Corporate bonds Figure , , Spar Nord s Management allocates lines for settlement risk and credit risk exposure to financial counterparties, based on the particular counterparty s risk profile, rating, amount of exposure and solvency. The risks and lines of financial instruments are constantly monitored. Spar Nord also participates in the CLS settlement system (Continuous Linked Settlement), which aims to reduce settlement risks. Overall, Management s assessment is that Spar Nord s credit risk exposure to financial counterparties is moderate. BOND PORTFOLIO BY RATING CATEGORY CALCULATED AS RISK PORTFOLIO AAA AA A CCC Figure 38 7, , ,342 1.