Workshop on the Implementation of the 2008 SNA in EECCA Countries and Linkages with BPM 6 and GFSM May 2015, Istanbul, Turkey 1

Outline of Presentation Introduction SebStat: Step Forward Towards Innovative Solution How the data are structured? SebStat as an additional data source for SNA and BOP compilers SebStat: How does it work? Lessons Learned and Way Forward 2

Introduction Against the background of rapidly increasing statistical standards and requirements National Bank of Georgia (NBG) carries out a consistent strategy for the sustainable development of statistics under its mandate. Moreover, expanding and improving our data sources and statistical production, in general, we strongly believe that we should think about other compilers of macroeconomic statistics also. This task is quite solvable with the recently launched completely new statistical business process model for National Bank of Georgia, so called SebStat. 3

SebStat: Step Forward Towards Innovative solution SebStat is an innovative statistical business process model for NBG providing full range of possibilities to satisfy requirements of monetary and financial statistics, as well as the needs of various macroeconomic statistics, directly or indirectly. This can be achieved by structuring of statistical and financial data using standardized approach for all statistical domain under the NBG’s mandate. 4

How the data are structured? Is it difficult to define data structure properly? The answer is “Yes” and “No”. In order to build the data structure several phases shall be done: – Identification of peer data groups to create proper data families for Central Bank’s needs; – Elaboration of the Code Lists for each data families; – Development of appropriate methodology how the financial instruments should be classified and structured properly by financial institutions; – The room for further development should be left. 5

How the data are structured? ( example for monthly financial statement data structuring ) Data Entry Data Characteristics Clients’ Characteristics Additional Info Attributes Financial Statement Data Structure 6

How the data are structured? (example for monthly financial statement data structuring) The structure of financial statement data (FIM_Data Family) consists of: Data entries – Data family – Source – Frequency Data characteristics – Financial/nonfinancial instruments – Assets/liabilities – Stock/flow – Maturity – Currency Client’s characteristics – Residency – Institutional sector – Type of economic activities – Region (if resident) Additional info – Additional info on loans – Loans collateral – Range (for loans&Deposits) Attributes – Interest rate – Measure type 7

How the data are structured: Other data families FEX_data Family - Foreign Currency Transactions Data entries (data family, source, frequency) Type of transactions Buying prices Selling prices Counterpart Measure type MTR_Data Family - Money Transfer Operations Data entries (data family, source, frequency) Type of transactions Type of wire transfer Country (sender/receiver) Currency Measure type BPC_Data Family - Payment Cards’ Statistics Data entries (data family, source, frequency) Card type and category Type of transaction Type of service post Measure type 8

SebStat as an additional data source for SNA and BOP compilers 1. Data sources to calculate the output of financial corporations FIM_Data Family – Monthly Financial Statements FEX_Data Family – Foreign Currency Transactions Output of Financial Institutions Financial Intermediation Central Bank Monetary Policy Services FISIM Deposit-taking Corporations Explicit fees charged in lieu of providing services FISIM Transactions in foreign currencies 9

SebStat as an additional data source for SNA and BOP compilers 2. Data sources to calculate the part of international transactions of Goods and Services Account of BOP BPC_Family- Payment Cards’ Statistics Goods and Services Account Goods E-Commerce (to be added) Services Travel Additional information to financial intermediation services, related with acquiring of payment cards 10

SebStat as an additional data source for SNA and BOP compilers 3. Data sources for calculation of PIB & SIB items of BOP MTR_Data Family- Money Transfer Operations PIB - Primary Income Balance Compensation of Employees SIB - Secondary Income Balance Personal Transfers 11

Financial/Nonfinancial Instruments Assets/Liabilities Stock/Flow Maturity Currency Residency Institutional Sector Type of economic activity Region Additional info on loans Loan’s collateral Range Interest rate Measure type Monetary Gold&SDRs Currency Deposits Securities other than shares Loans Shares and other equity Insurance technical reserves Financial derivatives Other accounts receivable/payable Nonfinancial assets Report description (example) Indicator: Loans Assets Stock Maturity: 10 year and more Currency: GEL Counterpart description: Residency: Resident Sector: Nonfinancial corporation Economic activity: Trade Region: Kakheti Additional info: SME loan Collateral: Real estate Range: Interest rate: Measure type: BV (book value) SebStat: How does it work?NextSkipBack Generate 12

Table 1. Loans granted by commercial banks, Jan 2010-Feb 2015 (Mln GEL) … Loans, total………… SebStat: How does it work? ( example ) 13

Lessons Learned Based on Georgian experience, it is obvious, that comprehensive multifunctional statistical data model for Central Bank is best solution in order to meet not only own statistical requirements, but also needs of other macroeconomic statistical systems compilers; The right cooperation strategy with data providers is essential, to ensure project success in terms of data relevancy and quality, and readiness for boosting joint effort aimed at strengthening of statistical capacity; Close cooperation with SNA, BOP and GFS compilers on the earlier stage of project designing is important to ensure data model comprehensiveness and methodological consistency. In addition to high level management support, it is very important to have the backing of international partners to raising awareness of the similar achievements on the national and international level, in order to get more benefit from each other’s experience and knowledge. 14

Thank you Contact information : Nana Aslamazishvili tel: (995 32) , 15