China’s new loans in Jan surge to record 2.9 trillion yuan, blow past forecasts

Finance


“Banks hope to lend early to get early returns… private investment and manufacturing investment are picking up due to firmer global demand (and) household loans could be boosted by property demand,” said Nie Wen, an economist at Hwabao Trust in Shanghai.

“This indicates the economy may slow in the first half but any slowdown won’t be sharp…”

Corporate loans surged to 1.78 trillion yuan from 243.2 billion yuan in December, while household loans rose to 901.6 billion yuan in January from 329.4 billion yuan in December, according to Reuters calculations based on central bank data.

Beijing is in the second year of a regulatory push to clamp down on riskier financial activity that has been fueled by a rapid build-up in debt.

But authorities are proceeding cautiously and keeping liquidity broadly supportive to avoid any sharp drag on the world’s second-largest economy or excessive financial market volatility.

Reflecting that tricky balancing act, authorities are already warning China’s banks to rein in new lending growth after the strong start to the year, financial magazine Caixin reported late on Monday, citing banking sources.

Broad M2 money supply also beat expectations, growing 8.6 percent in January from a year earlier, central bank data showed on Monday. Economists had expected the growth rate to edge up to 8.4 percent, from 8.2 percent in December.

Other data last week had painted a somewhat mixed view of the economy at the start of the year, with inflationary pressures easing — possibly pointing to softening activity — but better-than-expected import and export growth.

Taken together, the stronger credit and trade data would appear to still support the consensus view that China will see only a modest pullback in GDP growth to around 6.5 percent this year, after a forecast-beating 6.9 percent in 2017.

However, analysts warn that investors will likely not get a clearer picture of the health of China’s economy until March, because January and February month data are distorted by the timing of the lengthy Lunar New Year holidays.



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