2018. the investment cycle which began in 2015, and which accelerated significantly in the past two years, is having a considerable impact on import dynamics and structure. import growth in that period is mostly attributable to the economy ’ s increased needs for intermediate goods and equipment, and partly to consumer demand amid conditions of citizens ’ rising living standard. imported equipment boosted the serbian economy ’ s export capacity, therefore we expect to see high export growth rates continuing in the medium run. external sustainability is also confirmed by the fifth year of full coverage of current account deficit by the net fdi inflow ( 113 % in 2019 ). the external position is further endorsed by the project and geographical diversification of both exports and fdi inflow, which we worked systematically on, broadening our international cooperation. in addition, our economy ’ s resilience to potentially adverse developments in the international environment is confirmed by the high level of fx reserves of eur 13. 4 bn at end - 2019, which is their maximum level at year - end in the period since 2000, when data began to be monitored in this manner. the level of fx reserves is adequate in terms of both their size and structure. chart 7 fdi structure by sector ( in % ) chart 8 nbs fx reserves ( in eur bn ) gross fx reserves net fx reserves 2005 – 2008. 2009 – 2012. construction and real estate finance manufacturing source : nbs. 2013 – 2017. 2018 – 2019. other trade tradeable goods and services * * agriculture, industry, mining, transportation, catering. source : nbs. increased production capacities and competitiveness of our economy were conducive to positive developments in the labour market. owing to this, employment increased, while the unemployment rate decreased to a single - digit level. since the beginning of the investment cycle, the unemployment rate has been halved ( from 19. 2 % to 9. 5 % ), and formal employment in serbia ’ s private sector increased during the new investment cycle by more than 230, 000 persons. at the same time, wages are on the rise, notably in the private sector, which in turn increases household consumption and supports the social component of growth. it is important to note that consumption is rising at sustainable rates, i. e. that consumption growth contributes to the sustainability of economic growth. economic growth outlook remains favourable, therefore we expect similar gdp growth dynamics in the medium term of around 4 % per annum, as in the previous two years

“ in ftc study, five percent of consumers had errors on their credit reports that could result in less favorable terms for loans, ” news release, ( february 11, 2013 ), https : / / www. ftc. gov / newsevents / press - releases / 2013 / 02 / ftc - study - five - percent - consumers - had - errors - their - credit - reports ; federal trade commission, “ ftc issues follow - up study on credit report accuracy, ” news release, ( january 21, 2015 ), https : / / www. ftc. gov / news - events / press - releases / 2015 / 01 / ftc - issues - follow - study - credit - report - accuracy ; and bureau of consumer financial protection, data point : credit invisibles ( washington : bureau of consumer financial protection, may 2015 ), https : / / files. consumerfinance. gov / f / 201505 _ cfpb _ data - point - credit - invisibles. pdf. the primary federal statutes governing fair lending are the equal credit opportunity act ( ecoa ) and the fair housing act ( fha ). see, also lael brainard, “ where do consumers fit in the fintech stack? ” ( speech at the fintech risks and opportunities conference, ann arbor, mi, november 16, 2017 ), https : / / www. federalreserve. gov / newsevents / speech / files / brainard20171116a. pdf. u. s. department of the treasury, “ opportunities and challenges in online marketplace lending ” ( washington : u. s. department of the treasury, may 2016 ), https : / / www. treasury. gov / connect / blog / documents / opportunities _ and _ challenges _ in _ online _ marketplace _ lending _ white _ paper. pdf. - 11a recent example illustrates the risk of unwittingly introducing bias into an ai model. it was recently reported that a large employer attempted to develop an ai hiring tool for software developers that was trained with a data set of the resumes of past successful hires, which it later abandoned. because the pool of previously hired software developers in the training data set was overwhelmingly male, the ai developed a bias against female applicants, going so far as to exclude resumes of graduates from two women ’ s colleges. 24 importantly, the equal credit opportunity act ( ecoa ) and the fair credit reporting act ( fcra )