This enabled a fast transmission of monetary policy signals to the interbank and deposit markets. Also, the increase in deficit and public debt was absorbed by the liquidity generated in the domestic financial market. Against the backdrop of a high demand for investment in government securities, their yields dropped significantly for all maturities. All these developments created premises for credit interest rates to decline in 2013. Monetary indicators were largely in line with the real-economy developments. The annual money supply growth slowed down during the year. This slowdown reflected the weak demand for borrowing by the private sector, especially businesses. Lending to the private sector started to contract in the second half of the year. At the end of the year, the loan portfolio stood 1.4% lower than a year earlier. Similar to developments in the other countries in the region, this performance was influenced by economic agents’ reluctance to spend and invest, and banks’ more conservative lending policies. I will dwell on lending issues and measures taken by the Bank of Albania to boost lending in the following. Summing up the performance of the economy for 2013, aggregate demand remained weak and economic growth was low but below potential. This economic slowdown had serious implications for the economy’s health and balances. It affected public finances, which saw increase in budget deficit and public debt. Albanian businesses faced financial constraints and banks’ balance sheets suffered from worsened non-performing loan portfolios. It also led to a higher unemployment rate and slower rise in wages and prices.
We depend on our ability to access it, analyse it, and draw conclusions from it to set policies. Effective management and use of data is how we meet our goals. 1  A foot as we now know it is 304.8mm 2  All speeches are available online at www.bankofengland.co.uk/news/speeches and @BoE_PressOffice  2  Of course, we are far from alone here – many organisations rely heavily on their use of data. But we are, perhaps, different to many in that the vast majority of the data we want is generated by others rather than ourselves. The data we care about is the sum of millions of financial and economic interactions, taking place every second. And much of that data2 is captured and stored by financial institutions, as they go about serving their customers. We need to get our hands on that data. We need data on the financial system in aggregate and also on specific markets within it, to help us understand where risks are emerging and to help us calibrate policies to maintain stability. And we need data about individual regulated firms, for our work as supervisor and as resolution authority. So we have built data collection processes to give us that data. We publish reporting instructions. Firms then go through various steps: they interpret our instructions, identify the right data within their systems, put in place processes to integrate, cleanse and check the data, and then sign it off and deliver it to us.