Database Issues in Financial Sector

Transcription

1 Database Issues in Financial Sector A National Accounts perspective Ramesh Kolli, J.S. Venkateswarlu and S.S. Jakhar 1 Central Statistical Organisation 1. Introduction As per System of National Accounts 1993/2008, the financial sector consists of all resident corporations, Departmental enterprises, un-organised household enterprises and Non-profit institutions principally engaged in financial intermediation or in auxiliary financial activities which are closely related to financial intermediation. Following this approach, in the Indian system of National Accounts Financial sector is broadly divided into the following sub-sectors: I. Commercial Banks including Other scheduled commercial banks & foreign banks,--no issues II. Banking Department of RBI, no issues III. Public non-banking financial corporations (Centre& State) (UTI, NABARD, IDBI) DFC, HPFC, Assam FC and govt. companies (REC, HUDCO, PFC, IRFC) APIDC, KSIIDC, T.N. Transport Finance Corporation no issues IV. Organised Non-government non-banking financial companies engaged in trading in shares, investment holdings, loan finance and the like activities, V. Co-operative credit societies (State Cooperative Banks, Central Cooperative Central Banks, Industrial Cooperative Banks, Primary Agricultural credit societies, Primary co-operative banks, Primary non-agricultural credit societies, State co-operative agricultural and Rural development Banks, Primary co-operative agricultural and rural development banks) VI. Life and non-life insurance activities. VII. Post office savings banks, Employees Provident Fund Organisation VIII. Un-organised non-banking financial enterprises, such as, professional money lenders and pawn brokers etc. 2. Data sources and methodology for compilation of macroaggregates The sources of data for various sub-sectors used for compiling the macroeconomic aggregates of financial sector are given in the Table 1 below and detailed Estimates of GDP Financial Sector are enclosed as Annex-I: Sl. No. I Sub-Sector Commercial Banks includes OSCBs & foreign Banks Table 1: Data sources financial sector Data Source a) Annual Accounts of banks and b) Statistical Tables Relating to Banks in India (RBI) 1 Views expressed here do not necessarily represent those of the Central Statistical Organisation. 1

2 II III IV V VI VII Banking department of RBI Non-departmental Financial Companies and corporations Non-Government Nonbanking Financial Companies Co-operative Credit Societies Life and Non-Life Insurance (including Private insurance companies) Post office savings banks (POSB) & Employees Provident Fund Organisation (EPFO) a) Annual Report of RBI and b) data obtained directly from RBI on expenditure of the issue and banking departments Annual Reports/annual accounts a) RBI s sample study on Financial and Investment companies and b) data on paid up capital from Ministry of Corporate Affairs a) Statistical Statements relating to Co-operative Societies Movement in India , Vol. I-Credit Societies (NABARD, b) Report on Trend and Progress in India, RBI & c) Data on certain financial parameters obtained directly from NABARD for Annual Reports/ Accounts of LIC, GIC and its subsidiaries and Private Companies a) Budget documents of Department of Posts & b) Annual Report/accounts of EPFO Un-organised financial No source VIII services IX Capital Markets Mutual funds including UTI For Commercial Banks, Banking Department of RBI, Non-departmental Financial Companies and corporations, Life Insurance and Non-Life companies, Life and Non-Life Insurance & POSB and EPFO (Sl. No. I,II,III,VI & VII in the above table) their annual accounts (profit and loss account & balance sheet) are analysed and macro-economic aggregates are obtained and as such there are no issues with regard to data availability, quality and timeliness. Therefore, in this paper the discussion is mainly focused on data base issues relating to Non-Government Non-banking Financial Companies, Co-operative Credit Societies and Un-organised financial services (Sl. Nos.IV,V and VIII in the above table) only. 3. Non-Government Non-Banking Financial Companies The non-government non-banking Financial Companies (NGNBFCs) represents the organised non-banking private financial sector in the economy. The sector provides credit to businesses and households and also plays an important role in the capital market through their investment holding, share trading and merchant banking. These companies originate loans and extend lease finance for purchase of 2

3 consumer goods to the household sector and supply short and intermediate-term credit (including leases) to businesses for acquiring fixed assets, for working capital requirements etc. In the system of Indian National Accounts the NGNBFCs are treated as financial intermediaries. In the last two decades, the NGNBFCs have grown considerably and are offering a wide range of services. This sector is broadly divided into the following groups based upon their activity: share trading and investment holding companies, loan finance companies, hire purchase finance companies, financial leasing companies and companies having a combination of these activities. In respect of this sub-sector, RBI study of Financial and Investment companies is the only source, which provides consolidated profit and loss account & Balance sheet for around NGNBFCs every year. The RBI sample study is available after a gap of nearly 18 months. At present the GVA of this sector is estimated by analysing the data on income, expenditure and profits. 3.1 Problems in using the results of RBI sample Studies As per the present practice, estimates of GDP pertaining to Non-Govt. Non-Banking Financial Companies are being compiled using the results of the study on select non-government financial and investment companies (excluding Chit fund companies) conducted by RBI every year. These results are brought out in the monthly bulletin of RBI during the months of August / September every year. This year RBI bulletin for the month of September 2009 published the detailed results of the above study for three year , & The study is based on audited annual accounts of 1175 companies. Out of these 1175 companies, the study found that there are 13 companies (outliers) with results in large variance with rest of the companies. Therefore, results of the study are separately presented for 1161 companies, excluding these 13 companies or outliers. However, the results are made available for taking all the 1175 companies also. It is important to mention here that results for the years were available in similar studies published in the RBI bulletin of October 2007 & August 2008, whereas for the year in the RBI bulletin of August Table 2 provides total no. of companies, outlier companies, common companies and new companies in the studies published by RBI in November 2006, October 2007, August 2008 & September Further, Table 3 provides output and GVA of NGNBFCs based on RBI studies. RBI bulletin details Table 2: Details of RBI sample studies NGNBFCs Common Total No. of Outlier Cos. With Companies Cos. Previous Study New Cos. In the Present Study Nov., Oct., Aug., Sept.,

4 Table 3: GDP of Sample NGNBFCs based on RBI studies (Rs.Crore) ITEM Nov (1122) Oct (1194) Aug (1176) Oct (1194) Aug (1176) Sept (1161) Aug (1176) Sept (1161) Sept (1161) (1) (2) (3) (4) (5) (6) (7) (8) (9) Output* Interest Received Dividend Lease Rental Profit/Loss on sale of Investment Actual Receipts Interest paid Consumption of Goods& Services Compensation of Employees Operating Surplus Depreciation/CFC GVA PUC-sample companies *Output = FISIM + Actual receipts ** In the above table, the number in the bracket indicates the number of sample companies. To calculate GDP of this segment we are using study results excluding outliers. From the above table it is observed for the year the variations in GDP arrived from different studies is minimum, however, for the years & GDP estimates (as well as estimates of CE & OS also) from the first study are very much on higher side compared to other two studies. The main reason for these variations, within and between years is mainly due to use of different sets companies in the studies. In the case of latest study (as shown in Table 1) published in Sept. 2009, out of 1161 companies 843 companies are common with previous year s study and the remaining are new companies. To overcome this problem as per the present methodology, the estimates are compiled as average of the latest three years data. Therefore, GDP for sample companies for the year would be average of GDP estimates given in cols. (1), (2) & (3). Similarly, for the year , it would 4

5 be average of GDP estimates given in cols. (4), (5) & (6). For the year , it would be average of GDP estimates given in cols. (6), (7) & (8) and finally for the year , it would be average of GDP estimates given in cols. (6), (8) & (9). It is important to mention here that in the series the results of the study were used in the year and after that GDP estimates of this segment for the years , and (Quick) were based on the growth rate observed in the paid up capital of the population of NGNBFCs. The main reason for rejecting the results of these studies is the volatility observed in the results of these studies from year to year and also for the same year from different studies. At the time of changing of base year to , we have examined the above data of NGNBFCs. For the years , , & average GDP estimates of sample are blown up with the inflation factor (which is the ratio of paid up capital of NBFCs in the population to paid up capital of sample companies) to arrive at the GDP of this segment. The results are presented in Col. (2) of Table 4. YEAR Table 4: Non-Govt. NBFCs GDP (Rs.Crore) GDP series (1) GDP based on latest studies (2) Difference (3)=(1)-(2) GDP revised series From the above table, it is observed that for the year , there is a difference of Rs.2448 crore in GDP estimates of the series given in col.1 and estimates based on all the studies for the year given in col.2. For the years , & differences are of the order of Rs to 15,000 crore. Further, GDP based on studies for is Rs crore or 70% higher than the estimate for the year We could not find any justification for such an increase in the value addition from NGNBFCs. Therefore, we decided not to use the data from the studies for the years to or average of three years data. However, we revised our estimates for the year (Base year) to Rs crore from the present Rs crore. For the other years estimates were based on growth in PUC as followed in the series. 5

6 Another issue of importance is the population estimates of Savings of this segment provided by RBI. The same are presented in Table 5 and are used in the compilation of Savings. Table 5: Non-Govt. NBFCs Savings (Rs.Crore) YEAR Savings (1) Growth rate (2) Savings as % of GDP (3) % % 97% % 51% % 89% From Column (3) it is observed that Savings rate appears to be very high for NGNBFCs and it is also observed that annual growth rate is highly volatile. Even if we take GDP based on studies (Col.2 of Table 3), savings rate is found to be of the order of 40 to 70%; however, with the present available data this discrepancy can t be corrected and as the savings estimate for the population are compiled and made available by RBI, they were used. Therefore, at this stage, even though, we were not using the RBI studies for compilation of GDP, the same is used for compilation of Savings. This discrepancy need to be corrected at the earliest. Further the use of RBI studies for future year compilation of GDP can be examined again during the base year revision only. Therefore, from the above discussion it becomes clear that undoubtedly there is a need to improve the quality of data flowing from RBI studies. 3.2 Suggestions for improvement In the past many committees including National Statistical Commission and High Level Committee on Estimation of Saving and Investment examined the data base issues and made recommendations. However most of the recommendations were not implemented till date. The very first priority from National Accounts point of view is to provide a reliable and consistent estimate of value addition from NGNBFCs. Further, Value Addition estimates need to be consistent in comparison with other macroeconomic aggregates. Therefore, we have reviewed the recommendations of the above committees from this view point and added our views to make them implemented. And some recommendations presented here are based on our experience of using data from RBI studies and MCA. 6

7 3.2.1 Recommendations i) One time census of NBFCs (NSC recommendation iii): A one time census of NBFCS covering all companies incorporated with MCA and a periodic sample survey by RBI for updating population estimates was recommended by NSC. The other recommendations mentioned below may not give fruitful results without implementation of this recommendation. As mentioned in the High Level Committee report there has not been any substantive improvement in coverage of financial companies in corporate saving (corporate GDP estimates also) estimates during the last three decades. Therefore, in case we are interested to improve the macroeconomic aggregates of NGNBFCS, the first step should be to conduct a onetime census of NBFCs without any further delay. ii) Financial information of top 500 companies: Chelliah Committee (1996) recommended inclusion of top 1500 companies (both financial and non-financial) in terms of net fixed assets or sales in the sample. Therefore, with respect to financial private corporate sector it is recommended that top five hundred companies in terms of interest receipts, dividend, lease rental and profit/loss on sale of investment need to be identified. However, the present MCA data base does not provide information on any of these parameters. The only information in respect of receipts is related to sale of services and other income. The other income component is supposed to include all the four parameters mentioned above. In the absence of information on these parameters, it is not possible to calculate the implicit output (FISIM) of NGNBFCS. Therefore, from the point of view of calculation of FISIM as well as explicit output and also to identify the top 500 companies properly, it is necessary that the existing MCA database should have provision for (for financial companies) collecting information on the four parameters mentioned above. For the remaining companies, a suitable sample may be selected for estimating Value Added and other aggregates. iii) Continuation of RBI studies (NSC recommendation iv): NSC recommended that RBI should continue the studies on financial and investment companies till the system of one time census supported by periodic sample surveys gets established. We understand that the recommendations 1 and 2 made above will take some more time for their implementation. Therefore, the need for improving the quality of data from RBI studies is a must. We recommend the following for improving the data from these studies: a) Study of same set of companies: The studies shall provide financial parameters on income and expenditure of the same set of companies from year to year also along with the data provided at 7

8 present. This will substantiate the growth observed from year to year and the use of results could be justified. At present the volatility in the growth rates from year to year and also for a particular year from different studies becomes very difficult to understand and as a result it raises doubts regarding the reliability/ usability of the data as discussed above. b) Top companies: RBI may identify (taking all the five group of companies together viz. loan finance companies, leasing companies, Share trading companies etc.) top ten or twenty companies in terms of their value addition (or main income consisting of Interest, dividend, lease rental and profit/loss from sale of investment) and provide the information to CSO with a time lag of six to eight months for compilation of Quick Estimates of value addition from this sector. c) Financial Parameters of Individual companies: Financial parameters of Individual companies covered in their studies may be provided to CSO to check if any volatility has been observed in the results of RBI study. This procedure of comparing individual companies is followed by CSO in their analysis and preparation of macroeconomic aggregates of NDCUs. d) Comparison of MCA and RBI data: In Annexure 7.2 of HLC report a comparison of select data items viz. PUC, Dividends and depreciation of select companies (including some financial and investment companies e.g. Bajaj Auto Finance Ltd., Abhirami Financial Services Ltd., Dewan Housing Finance Ltd. Escorts Finance Ltd., etc.) of data bases maintained by MCA and RBI is presented. The data comparison should have been made in terms macro aggregates compiled from these two sets of data. Based on the comparison made in terms three parameters (which are not associated in compilation of any of the aggregates), drawing conclusions regarding the quality of the data is not completely agreeable. The four parameters which are made available by RBI studies (interest receipts, dividend, lease rental and profit/loss on sale of investment) are required for calculation of FISIM and are not available in the MCA database. By following income approach, value addition (may be approximately) may be calculated using information on Compensation, Profits and Rent. However the calculation of FISIM is of utmost importance, as the same has to be allocated to user industries for arriving at a reliable estimate of value addition from different industries. In the absence of the information on the four parameters mentioned above it is not possible. Further, the saving estimates arrived at using the incomplete information may not be reliable and consistent. 8

9 iv) Blow up Factor: At present the estimates based on the RBI studies are blown up using the PUC of population provided by MCA. There are two issues with regard to PUC: a) its reliability and b) its use as blow up factor. At present, we don t have any source to cross check either its reliability or a substitute blow up factor. It was mentioned in the HLC report that GCF or sales could be used as substitutes; however it was mentioned that the suggestion is not implementable due to non availability of information on these variables at population level. To overcome the issue of blow up factor and all the issues discussed above, a onetime census of NBFCs shall be taken on priority by RBI. 4. Co-operative Credit Societies The magnitude and structure of this sector is posing major problems to compilers of financial information of this sub-sector. Financial information of credit cooperatives is brought out by NABARD in its publication Statistical Statements relating to Co-operative Societies Movement in India, Vol. I-Credit Societies with a time-lag of more than 6 years. The latest publication available pertains to These Statistical statements provide detailed information on assets, liabilities, income, expenditure and profit/loss in respect of eight categories of credit cooperatives viz. State Co-operative Banks (SCBs), Central Co-operative Banks (DCCBs), Industrial Co-operative Banks (ICBs), Primary Agricultural Credit Societies (PACs), Primary Co-operative Banks (PCBs), Primary Non-Agricultural Credit Societies (PNACs), State Co-operative Agricultural & Rural Development Banks (SCARDBs) and Primary Co-operative Agricultural & Rural Development Banks (PCARDBs). However, in no way these statements are substitute for consolidated profit and loss a/c & balance sheet. Further, NABARD provides directly the information to CSO on certain financial parameters like interest received, other income consisting of commissions, brokerage & other receipts, interest paid, salary, depreciation, rent, other expenses, net profit, provisions for bad debt reserve, over due interest reserve and other reserve with a time-lag of around 18 months. This information is made available for SCBs, DCCBs, SCARDBs & PCARDBs only and the latest information available pertains to Further, RBI also brings out similar information in its publication Report on Trend and Progress of banking in India for the above four categories and also for Urban Banks. At present for compiling GVA for a particular year (say ) following procedure is adopted. GVA for all the eight categories of cooperatives for is compiled and the ratio of GVA for the above four types of cooperatives (SCBs, DCBs, SCARDBs & PCARDBs) to the total GVA of all cooperatives is calculated. Then, GVA of the total sub-sector for a particular year is obtained by blowing up the Gross value added for the four categories of cooperatives using the ratio obtained above for the year GVA from co-operatives following this methodology is presented in Annex-I (item 1.1.5). Contribution of different types of credit cooperatives their nos. and membership is given in Table 6. 9

10 Sl. No. Table 6: Contribution of different Types of Co-ops. ( ) No. of % Type of Credit Cooperative societies ( 000) Credit Membership contribution to GDP 1 DCBS SCBs PACADBs SCARDBs PNACS PACs PCBs Suggestions for improvement of database on Credit-Cooperatives With regard to Credit Co-operatives, the problems relating to data availability and the time lag are very well known. In the past the same was pointed out by many committees including National Statistical Commission and the High Level Committee on Estimation of Saving and Investment. The recommendations made by the above Commission/Committees remain unimplemented. From national Accounts perspective, quality and timely data on this segment is absolutely necessary to correctly depict the picture of financial sector and also to take corrective policy measures for improving the status of Co-operatives. The recommendations made by NSC and also HLC on Estimation of Saving and Investment relating to Credit Cooperatives are presented with our views for a purposeful discussion in this forum Recommendations i) Sample survey of Primary Rural Cooperatives (NSC Recommendation ii): The NABARD should adopt a suitable sample survey to collect data from Primary Rural Cooperatives as it becomes difficult to collect data from all such cooperatives at frequent intervals.--- As explained above at present NABARD makes available data on few financial parameters for compilation of GDP in respect of four schemes (SCBs, DCCBs, SCARDBs & PCARDBs) with a time lag of eighteen months. As suggested in NSC recommendation, the sample survey shall be conducted with main focus on DCCBs, SCBs, PACs, PCBs and PNACs, as they found to be contributing more than 98% to GDP (see Table above) of credit cooperatives. This sample survey could be conducted by NABARD in association with NSSO and it may be a survey on the lines of other surveys conducted by NSSO once in five years. Further, for providing income & expenditure information of the above five types of cooperatives on a year to year basis with a time lag of 6-8 months, a panel consisting of top cooperatives (with respect to income) from each type could be prepared and information may be collected. This panel information would be helpful in moving the estimates of cooperatives based on the above proposed sample survey. ii) Accounts of Cooperative Banks (NSC Recommendation iii): The balance sheet of the cooperative banks should be standardized to a form, 10

11 similar to that of commercial banks by RBI and NABARD. --- At present Saving estimates of credit cooperatives are compiled for bench mark year using the information published in Cooperative movement in India for the year brought out by NABARD and for subsequent years the same is moved with the growth observed in the GDP of the credit cooperatives. The savings in the case of commercial banks is calculated as the difference between (CG, PBDD, IPY/EPY,TTR, TBS) and (CL,TFR and TLA), whereas, the saving in the case of cooperative banks - change in the statutory reserves, bad debt reserve special bad debt reserves, overdue interest reserves, other reserves, agriculture credit stabilization reserve etc. is taken as savings. Therefore, in strict sense savings of these two segments of financial sector are not comparable. However in the absence of a Profit & loss account and Balance Sheet on the lines of commercial banks the present procedure is adopted. Further, the data on important financial parameters published in statistical statements of credit cooperatives is incomplete and inconsistent presentation of data on assets, liabilities and operations is found to be different for different types of cooperative banks. e.g. accumulated profit /loss is not provided for all types of cooperatives, asset/ liability mismatch in many cases, difference in depreciation reserve for two subsequent years not tallying with depreciation given under cost of management etc. Therefore, cooperative banks shall be statutorily be made to prepare their Profit & Loss Account and Balance Sheet on the lines of Commercial Banks as recommended by NSC. iii) FISIM of cooperative banks: FISIM is the implicit output of enterprises involved in financial services and is the difference between Interest, Dividend received plus net profit on sale of investment and interest paid. Because of the incomplete data, at present FISIM is taken as a fixed proportion of GDP. This in turn has an impact on the user industries for which this FISIM is allocated as intermediate consumption. Therefore, it further strengthens the need for having a Profit & Loss Account and Balance Sheet on the lines of Commercial Banks as recommended by NSC. iv) Constant Price estimates of credit cooperatives: With regard to credit cooperatives, constant price estimates are compiled by extrapolating the base year estimates of GVA with average of indices of deposits and membership. As the details of deposits and membership are available with a time-lag of around six years, compilation of reliable estimates for this segment at constant prices is not possible. Therefore, NABARD shall make available this information on regular basis to CSO to enable us to compile constant price estimates. 5. Un-organised Non-Banking Financial services In the absence of availability of direct data for measuring the volume of activity of un-organised non-banking financial activities and own-account money lenders, in the current ( ) series the estimates of value added for this segment are assumed to be one-third of the gross/net value added in the organised activities. The estimates of value added arrived at by following this methodology is presented in Annex-I (item ). 11

12 It is important to mention here that the NSSO has included financial enterprises for the first time in its 63 rd survey ( ) on services and the results were published during January This survey covered all financial intermediation services (organised and unorganized) and excluded Government & Public sector enterprises, commercial banks, discount houses, savings banks etc. To put it in terms of household and non-household enterprises, all household financial enterprises were included; whereas non-household enterprises (NHHEs) covered under public sector were not included in the survey i.e. NHHEs owned and run by corporate sector, cooperative societies, other type of societies, associations, trusts, etc. are only included. The estimates of GVA from financial enterprises based on the 63 rd round results is compiled and presented in Table 7. Table 7: Estimates of GVA of Financial enterprises (63 rd round of NSSO) NIC-2004 code (1) Description (2) Average GVA (Rs.) (3) Estimated No.of enterprises (4) Total GVA (Rs.crore) (5) Money lending from own source Self-help groups in financial intermediation Co-operative credit societies Rest of 659 Hire purchase financing, housing finance companies, commercial loan cos., pawn shops, mutual funds, chit fund/kuris, Investment companies Insurance and pension funding Activities auxiliary to financial intermediation -financial advisers, mortgage advisers, insurance agents, actuaries and salvage administrators etc GVA of financial enterprises Apart from activities of Money lending from own source (65925) & Self-help groups in financial intermediation (65994) which are completely unorganised, other activity codes also have unorganized non-banking financial activities viz. pawn brokers, unorganized chits, financial advisers, mortgage advisers etc. It is also observed that own account enterprises (OAEs) accounted for a value addition of Rs.4581 crores and establishments contributed Rs crore. Further, information for compilation of FISIM viz. interest receipts, dividend receipts, profit/loss on sale of investment and interest paid are available for the first time in respect of different types of financial enterprises. The survey also collected data on asset and liabilities. However, Value addition/assets/liabilities from un-organised non-banking activities are not made available separately. The unit level data has to be examined to find out the magnitude of value addition, savings and capital formation of 12

13 unorganized non-banking financial services and to take a decision regarding its usability in national accounts. 5.1 Suggestions for improvement The recommendations made by National Statistical Commission are presented with our views to highlight the need for strengthening the database of this segment: Recommendations i) Separate survey for financial service enterprises (NSC recommendation ii): The CSO should conduct Enterprise Surveys separately for financial service enterprises and provide data needed to derive value added details as also details of credit. The RBI should closely liaise with CSO and NSSO on the technical aspects of these surveys and ensure the coverage of all known enterprises like, share brokers, multani shroffs, chettiars, Marwari kayas and pawnbrokers and various kinds of money lenders. ii) Sample survey of NGOs and SHGs involved in micro finance (NSC recommendation iv): Financial data in respect of all NGOs and SHGs involved in micro finance should be collected. It is suggested that a sample survey of NGOs and SHGs should be undertaken by NABARD at quinquennial intervals. NABARD should also prescribe a half-yearly return to be submitted by all NGOs and SHGs. In the 63 rd round survey of NSSO, a first step in the direction of implementation of the above recommendations took place by inclusion of financial enterprises. However, from national accounts perspective - a special survey by combining the needs mentioned in above two recommendations shall be conducted. 6. Concluding Remarks The need for discussion on these issues should not have arisen provided the recommendations of National Statistical commission and other committees on financial sector were implemented. However, this never happened and most of the recommendations remained unimplemented. Therefore, from National Accounts perspective, the estimates of financial sector are subjected to all these limitations in the data mentioned above. It is important to remember that National Accounts does not stop with producing estimates of GDP or savings; CSO is mandated to produce Sequence of Accounts as per SNA 1993 Viz. Production Account, Primary distribution of income account, Secondary distribution of income account, Use of income account and Accumulation accounts (capital & finance accounts) for all the five institutional sectors including financial corporations sector. With regard to financial corporations, at present we are compiling sequence of accounts for Non- Departmental financial corporations only. Therefore, to achieve the ultimate goal of sequence of accounts for financial corporations, strengthening the data of NGNBFCs & Cooperatives on the lines suggested above is required. From NSSO survey, there is some hope of developing a database for the unorganised financial services. When the financial enterprises will be surveyed for the second time in its 69 th round, further 13

14 improvements could be built-in based on the experience of the 63 rd round and the feedback received from users. With the increasing necessity for data requirements arising even on quarterly basis, as suggested above, sample surveys / studies supported by panels should be taken up to strengthen the macroeconomic aggregates of financial sector without further delay. ******* References [1] Commission of the European Communities, IMF, OECD, United Nations and World Bank (1993/2008): System of National Accounts 1993 & 2008 [2] Central Statistical Organisation (2007): National Accounts Statistics-Sources and Methods [3] Reserve Bank of India (Nov.2006, Oct.2007, Aug & Sept.2009): Performance of Financial and Investment Companies [4] Reserve Bank of India (November 2007): Report on Trend and Progress of Banking in India [5] National Bank for Agricultural and Rural Development (2009): Statistical Statements Relating to the Cooperative Movement in India , Part-I Credit Societies 14

15 Detailed Estimates of GDP Financial Sector (Rs.Crore) Annex-I Sl.No. Sector/Sub Sectors (QE) 1 Gross Domestic Product Banking banks Banking Deptt.of RBI Post office saving banks Non-banking financial cos.and corpn Govt.NBFCs NGNBFCs HDFC Un-organised non banking activities Co-op.credit socities E.P.F.O Insurance Life insurance (LIC+Pvt.Life) Postal life insurance Non-life insurance Less:- CFC Net Domestic Product Estimates of Saving & GCF of Financial NDCUs (Rs.Crore) Item/Year Gross Savings GCF