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Deleveraging While Disseminating: The Task Facing China's Banks

(Editor's Note: In the original version of this commentary published Oct. 18, 2018, table 4 had some errors. A corrected version follows.)

Chinese banks face a daunting mandate. As the country's dominant financial intermediators, they need to supply credit to fuel China's economic expansion. At the same time, new rules have tightened the sector's interbank funding markets and require banks to reduce off-balance-sheet risks. S&P Global Ratings believes this process of "deleveraging while disseminating" will require accommodative monetary policy, new capital-raising exercises, and could lead to further credit divergence in the sector.

Banks are in the process of "financial deleveraging," a general term used by Chinese authorities in various rules and guidance to contain the interbank and shadow banking activities. They are also expected to channel funds to desired economic sectors, such as small and micro lending and innovation sectors, and away from certain restricted sectors such as those with overcapacity.

Our analysis of 41 listed Chinese commercial banks shows that this dramatic process has already increased funding strains and is chipping away at capital buffers. Some smaller banks have had trouble adjusting to the new strictures. Given their stronger financial positions, we expect megabanks will play a more important role in China's transformation over the next two years. More efficient and effective credit allocation is a key to achieving this deleveraging while disseminating mandate, in our view.

Who's Who Among The Listed Banks?

We surveyed 41 listed Chinese commercial banks for this analysis. By end-2017, the listed banks represented 66.0% of the sector's total assets (including policy banks), 67.4% of total loans, and 65.9% of total deposits (see chart 1).

These institutions fall into four main categories (see table 1):

  • Megabanks (Group A). This category covers the "big five" commercial banks plus the Postal Savings Bank of China (PSBC). The six megabanks together account for 42.3% of the banking sector assets and have extensive branch networks. These banks share a similar geographic reach and business scope, though PSBC lags in product offerings.
  • National banks (Group B). The nine listed joint-stock commercial banks (JSCBs) have a nationwide presence and adequate financial disclosure for peer comparison purposes. There are 12 JSCBs in China as of end 2017, accounting for 17.8% of total banking sector assets.
  • City commercial banks (Group C). Our group covers only the 18 listed city commercial banks. There are 134 city commercial banks as of end 2017, accounting for 12.6% of total banking sector assets.
  • Rural commercial bank (Group D). We include eight listed rural commercial banks. There are 1,262 rural commercial banks as of end 2017, accounting for around 10% of the total banking sector assets.

Group C and Group D are "regional banks." While their deposits and loans are geographically concentrated, in recent years these banks have been gaining greater nationwide exposures via the interbank and bond markets.

The 41 listed banks include 15 banks listed in Hong Kong ("H shares), 17 banks listed on China's domestic bourses ("A shares") and nine banks with dual listings in China and Hong Kong. See our appendix for a full list of these banks, and their key statistics.

Chart 1

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Table 1

China's 41 Listed Banks Ranking By Assets
Rank in 2017 Rank in 2016 Bank Total assets in 2017 (mil. RMB) Total assets in 2016 (mil. RMB) Total adjusted assets in 2017 (mil. RMB) Group
1 1 Industrial and Commercial Bank of China Ltd. 26,087,043 24,137,265 28,752,838 A
2 2 China Construction Bank Corp. 22,124,383 20,963,705 23,855,203 A
3 3 Agricultural Bank of China Ltd. 21,053,382 19,570,061 22,633,909 A
4 4 Bank of China Ltd. 19,467,424 18,148,889 20,625,160 A
5 5 Bank of Communications Co., Ltd. 9,038,254 8,403,166 10,000,771 A
6 6 Postal Savings Bank of China Co., Ltd. 9,012,551 8,265,622 9,744,551 A
7 7 Industrial Bank Co., Ltd. 6,416,842 6,085,895 7,569,124 B
8 8 China Merchants Bank Co., Ltd. 6,297,638 5,942,311 8,475,494 B
9 11 Shanghai Pudong Development Bank Co., Ltd. 6,135,061 5,857,263 7,670,405 B
10 10 China Minsheng Banking Corp., Ltd. 5,902,086 5,895,877 6,715,924 B
11 9 China CITIC Bank Corporation Ltd. 5,677,691 5,931,050 6,810,367 B
12 12 China Everbright Bank Company Ltd. 4,088,243 4,020,042 4,826,124 B
13 13 Ping An Bank Co., Ltd. 3,248,474 2,953,434 3,749,536 B
14 14 Hua Xia Bank Co., Ltd. 2,508,927 2,356,235 3,211,862 B
15 15 Bank of Beijing Co., Ltd. 2,329,805 2,116,339 2,682,429 C
16 16 Bank of Shanghai Co., Ltd. 1,807,766 1,755,371 2,037,966 C
17 17 Bank of Jiangsu Co., Ltd. 1,770,551 1,598,292 2,028,551 C
18 18 China Zheshang Bank Co., Ltd. 1,536,752 1,354,855 1,885,671 B
19 19 Bank of Nanjing Co., Ltd. 1,141,163 1,063,900 1,466,446 C
20 20 Shengjing Bank Co., Ltd. 1,030,617 905,483 1,074,319 C
21 21 Bank of Ningbo Co., Ltd. 1,026,790 885,020 1,226,100 C
22 23 Huishang Bank Corporation Ltd. 908,100 754,774 994,406 C
23 22 Chongqing Rural Commercial Bank Co., Ltd. 905,778 803,158 1,012,965 D
24 24 Bank of Hangzhou Co., Ltd. 833,339 720,424 1,010,644 C
25 25 Guangzhou Rural Commercial Bank Co., Ltd. 735,714 660,951 859,163 D
26 27 Bank of Jinzhou Co., Ltd. 723,418 539,060 746,862 C
27 26 Bank of Tianjin Co., Ltd. 701,914 657,310 797,998 C
28 28 Harbin Bank Co., Ltd. 564,255 539,016 631,563 C
29 29 Zhongyuan Bank Co., Ltd. 521,990 433,071 554,594 C
30 31 Bank of Guiyang Co., Ltd. 464,018 372,253 534,721 C
31 32 Bank of Zhengzhou Co., Ltd. 435,829 366,148 473,330 C
32 33 Bank of Chengdu Co., Ltd. 434,539 360,947 454,428 C
33 30 Bank of Chongqing Co., Ltd. 422,763 373,104 476,342 C
34 34 Bank of Qingdao Co., Ltd. 306,276 277,988 357,320 C
35 35 Bank of Gansu Co., Ltd. 271,148 245,056 237,109 C
36 36 Jilin Jiutai Rural Commercial Bank Corporation Ltd. 187,009 191,471 189,948 D
37 37 Jiangsu Changshu Rural Commercial Bank Co., Ltd. 145,860 129,982 173,487 D
38 38 Wuxi Rural Commercial Bank Co., Ltd. 137,125 124,633 138,410 D
39 39 Jiangsu Jiangyin Rural Commercial Bank Co., Ltd. 109,403 104,085 113,883 D
40 40 Jiangsu Zhangjiagang Rural Commercial Bank Co., Ltd. 103,173 90,178 118,897 D
41 41 Jiangsu Wujiang Rural Commercial Bank Co., Ltd 94,266 81,348 101,316 D
Mil.--Million. RMB--Chinese renminbi. Source: Banks' annual reports.

Deleveraging Starts With The Liability Side Of The Balance Sheet

China's financial deleveraging is working: the banking sector's asset growth is trailing that of China's nominal GDP. This trend started in late 2017 (for the first time since 2012) and continues to date (see chart 2). It reflects a crackdown on interbank market excesses and is a result of a shift in China's policy settings from "easy money" to "tight/neutral money" aimed at deleveraging China's financial and corporate segments. Credit conditions considerably tightened in 2018 and remain tight for some economic sectors so far, despite more fine tuning measures and a softened tone to "loose/neutral money" since the second quarter of 2018. We consider this to be a pragmatic monetary policy that balances the need to reduce debt and risk in some economic sectors while keeping stable economic growth.

Chart 2

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Table 2

Top 10 Banks With Fastest Credit Expansion
Rank Entity Total credits in 2017 (mil. RMB) Total credits in 2016 (mil. RMB) Growth in 2017 (%)
1 Bank of Guiyang Co., Ltd. 284,294 200,339 41.91
2 Jilin Jiutai Rural Commercial Bank Corporation Ltd. 111,658 81,721 36.63
3 Bank of Jinzhou Co., Ltd. 594,890 436,977 36.14
4 Zhongyuan Bank Co., Ltd. 337,563 262,784 28.46
5 Bank of Zhengzhou Co., Ltd. 323,972 255,583 26.76
6 Bank of Tianjin Co., Ltd. 520,293 413,604 25.79
7 Bank of Qingdao Co., Ltd. 204,736 162,952 25.64
8 Bank of Chengdu Co., Ltd. 233,034 190,940 22.05
9 Bank of Beijing Co., Ltd. 1,643,996 1,354,261 21.39
10 Bank of Chongqing Co., Ltd. 310,135 257,612 20.39
mil.--Million. RMB--Chinese renminbi. Source: Banks' annual reports

Because they depend more on wholesale funding, some smaller banks are at a disadvantage. One key aim of the clampdown is to discourage financial institutions from carving out speculative trading and investment instruments from interbank loans, including wealth management products (WMPs). Banks took advantage of fast-growing interbank funding markets to fuel their rapid asset growth during the past. Now that the rules are changing, these banks are facing significant balance-sheet adjustments. Our analysis shows a general pattern where banks which relied more on wholesale funding have tended to cut back asset growth the most in 2017 (see chart 3).

Chart 3

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Table 3

Top 10 Banks With The Heaviest Reliance On Interbank Funding In 2017
Rank Bank Interbank liability/funding base (%) Interbank liability growth in 2017 (%) Liquidity coverage ratio (x) Reported LDR (%) Broadly adjusted LDR (%)
1 Industrial Bank Co., Ltd. 31.78 (7.66) 1.17 78.74 113.38
2 Shengjing Bank Co., Ltd. 29.75 26.05 1.67 59.02 106.32
3 Shanghai Pudong Development Bank Co., Ltd. 29.38 6.87 1.12 105.16 111.27
4 Bank of Communications Co., Ltd. 29.36 6.80 1.48 90.40 86.35
5 Bank of Jinzhou Co., Ltd. 29.15 10.00 1.38 65.92 162.67
6 Bank of Shanghai Co., Ltd. 28.12 8.58 1.45 71.90 82.50
7 China Minsheng Banking Corp., Ltd. 26.47 (6.43) 1.35 94.54 112.06
8 China Zheshang Bank Co., Ltd. 25.24 (9.47) 1.06 78.19 101.48
9 Huishang Bank Corporation Ltd. 23.76 49.54 1.97 61.37 113.37
10 Bank of Tianjin Co., Ltd. 23.71 (23.51) 1.32 69.55 114.62
LDR--Loan to deposit ratio. Source: S&P Global Ratings

China at first tried tightening interbank monetary policy starting from August 2016, then widened its scope in 2018. For example, policymakers put new rules on negotiable certificates of deposit (NCD)--a popular short-term interbank debt instrument for smaller banks. Since NCDs were introduced in 2013 as part of the country's interest rate liberalization, issuance has soared. Outstanding NCDs exceeded Chinese renminbi (RMB) 9 trillion (US$1.30 trillion) as of Aug. 31, 2018, compared with about RMB3 trillion at the end of 2015.

Because many of the new restrictions are proportional--e.g., caps on interbank funding as a percentage of all funding sources--smaller banks have felt the greater impact. Deposit-richer larger banks have more flexibility to continue issuing such instruments, without hitting new proportional limits. Amid constraints in other funding channels this year and under supportive monetary policy, big banks were able to turn to the NCD market. Issuance picked up after the first quarter 2018 (see chart 4).

Chart 4

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We believe liability-side adjustments will stabilize following large swings. In the first quarter of 2018, outstanding interbank liabilities plunged by 16% and their proportion of banks' total liability reached a historical low (see chart 5). In the second quarter of the year, market liquidity eased, interbank rates ticked down; this led some banks to seek funding and interbank liability size marginally recovered. This indicates that the regulatory impact is softening.

Chart 5

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Banks have until 2020 to comply with new rules on WMPs, cutting off another popular funding source. WMPs often function as deposit-like funding sources to support shadow banking and nonloan credit. Banks sometimes offered high yields, and investors almost always expected an implicit guarantee. The new rules disallow such guarantees, and also require better liquidity matches.

JSB or regional banks were more reliant on this shadow-funding market, and thus continue to face bigger adjustments to balance sheets and strategy. WMP growth slowed to 1.69% in 2017, compared with annual growth of as much as 50% over the past several years. Meanwhile, WMPs held off-balance sheets shrunk by 4.5% in 2017 to RMB22.17 trillion; then fell further to RMB21 trillion as of end June 2018 (see chart 6). That said, we note a marginally rebound in off-balance sheet WMP since July. We believe this is mainly due to the issuance of new products, which are in line with traditional asset management products. While these products are also off balance sheet, they are not designed as a deposit-like tool. This indicates a stable transition is on the way. Even so, some small banks that used to be heavily involved in off-balance sheet activities may still be under pressure to fund and capitalize those previous shadow loans as shadow funding diminishes.

Chart 6

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Competition For Deposits Will Get Fiercer As Funding Profiles Diminish

As speculative and less-regulated funding activities are shrinking, a yield-chasing mood among Chinese bankers in 2015-2016 has turned to a "deposit first" mindset since 2017. The policy of encouraging more loans to the real economy could challenge banks' funding profiles in the next two years. The rising adjusted loan to deposit ratio (ALDR) indicates such funding pressure, especially for small to midsize banks (see chart 7). The ALDR is adjusted to include off-balance sheet items.

Chart 7

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Some national and regional banks seem to be disadvantaged in terms of funding access. Moreover, increasing demand for longer-tenure credit is creating difficulties for banks to attract matching longer-term deposits. The mega banks have a much stronger liquidity position due to their larger branch networks and higher public and depositor confidence. Ten of the 41 listed national and regional banks already have been running ALDR above 100% (see table 4).

Table 4

Top 10 Banks With Highest Adjusted Loan-To-Deposit Ratios
Adjusted LDR (%) Reported LDR (%) Deposit growth (%) Deposit cost (%) Funding cost (%) Loan yield (%) NPL ratio + SML ratio (%)
June 2018 2017 June 2018 2017 June 2018* 2017 2017 2017 2017 June 2018 2017
Industrial Bank Co. Ltd. 125.2 113.4 86.2 78.7 0.5 14.6 1.7 2.8 4.6 3.9 3.9
China Minsheng Banking Co. Ltd. 105.3 112.1 96.7 94.5 6.5 (3.8) 1.8 2.7 4.7 5.4 5.8
Hua Xia Bank Co. Ltd. 100.7 88.9 105.2 97.2 1.9 4.8 1.5 2.4 5.0 6.4 6.4
Bank of Beijing Co. Ltd. 104.8 101.4 87.5 84.9 9.4 10.2 1.6 2.5 4.5 2.6 2.8
Shengjing Bank Co. Ltd. 112.2 106.3 66.2 59.0 6.6 14.0 3.6 3.3 5.9 8.7 3.2
Huishang Bank Corp. Ltd. 117.7 113.4 65.3 61.4 3.9 11.0 1.5 2.3 5.0 2.2 2.5
Bank of Jinzhou Co. Ltd. 141.6 162.7 70.6 65.9 2.7 30.2 3.1 3.6 6.3 4.6 3.3
Bank of Tianjin Co. Ltd. 118.5 114.6 69.5 69.6 (6.0) (2.1) 2.7 3.3 4.8 6.0 5.8
Bank of Zhengzhou Co. Ltd. 108.4 110.6 52.9 50.3 3.0 18.0 2.0 2.8 5.6 4.6 4.8
Bank of Gansu Co. Ltd. 110.6 89.6 75.7 67.8 3.1 12.3 1.9 2.7 6.5 5.2 7.2
41 listed banks peer average 80.6 80.9 76.8 75.9 5.6 6.5 1.9 2.0 4.3 4.3 4.5
Note: LDR--Loan-to-deposit ratio; we used median-adjusted LDR of 41 Chinese listed banks. SML--Special mention loans. NPL--Nonperforming loans; *Compared to end-2017. Source: Banks' annual and interim reports.

Smaller banks are also constrained from competing for deposits because China still has informal caps on deposit rates. Although the People's Bank of China (PBOC) scrapped the official ceiling for deposit rates in October 2015, the rates are still largely constrained by the regulator's window guidance and the market interest rate pricing self-regulation mechanism. Deposit interest rates are set around 1.4x-1.5x the central bank's benchmark rates in general. The PBOC had been expected to relax its informal guidance for the upper limit of commercial banks' deposit rates, equipping small banks to compete for more deposits by offering higher rates. However, given current conditions, that process may be slow to avoid upward pressure on rates.

Some smaller banks have increasingly relied on structured deposits as they seek to fill the hole left by the clampdown on WMPs. Some of the offer yields are as high as 5.5% on three-month deposits (in comparison to 1.1% for the same duration). Structured deposits come in many forms and generally promise a fixed return because the principal is protected, with potential upside through an embedded derivative position. Structured deposits soared 32.4% in the first half of 2018 compared with the same period last year (see chart 8). We consider these instruments as temporary alternatives to WMP that help to grow deposits but at higher cost. We expect growth to slow down as the regulator tightens scrutiny.

Chart 8

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Furthermore, average deposit growth remained sluggish, increasing 7.2% year-on-year in the first half of this year, compared with annual growth of 8.8% in 2017 and 12.5% in 2016. One issue is that as shadow-bank funding is gradually transferred on to balance sheets in line with new rules, they are now subject to required reserve ratios (RRR). This combined with banks' current low risk appetite on lending, means the effective money or deposit multiplier is weakening, constraining potential deposit growth. Although RRRs have been cut four times since 2018, banks aren't channeling funds to the real economy to the extent expected. China commercial banks' surplus reserve ratio has jumped in recent months, after running at almost historical lows of around 1.4% as of late 2017 (see chart 9).

Chart 9

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As a side note, some regional banks, especially rural commercial banks, have quite sufficient local deposit bases. However, if these banks were to suffer substantial credit losses, we see a higher risk of "flight to quality" (among depositors).

While deposit growth is slowing, China's overall banking system is still well supported by a strong deposit base. Even after considering government debt, the banking sector's credit-to deposit-ratio remains less than 100%. However, this strong liquidity buffer is on a weakening trend (see charts 7, 10, and 11).

Chart 10

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Chart 11

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If credit growth continues to outpace deposits growth by around 2% a year, the country's total credits to adjusted deposits ratio could exceed 100% over the next two years. This would give the central bank less flexibility to set interest rates and monetary policy, leading to rising refinancing risk for banks and private borrowers. Banks' credit resilience could be severely tested under such circumstances.

That said, we expect a rapid policy response were a liquidity shock to unfold. The PBOC has numerous tools at hand (see chart 12). For example, the medium-term lending facility (MLF) reached an historical high of RMB5.38 trillion at the end of September 2018, more than 2% of total liabilities in the banking sector.

Chart 12

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We expect further RRR cuts to offset funding pressures borne of shadow banking reform, and also in an attempt to reanimate loan appetite.

Asset Quality Will Marginally Deteriorate

In our view, large banks will play a key role over the next two years in disseminating credit to sectors identified as future growth engines for the Chinese economy (see chart 13). This trend will help policymakers meet their derisking goals, since smaller banks tend to have weaker underwriting standards and riskier exposures.

Chart 13

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Chart 14

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Chart 15

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Because they have fewer constraints, megabanks are in a better position to expand their credit channels. However, they will be relatively risk averse in the face of uncertain economic prospects. Moreover, banks are under pressure to keep lending rates low, yet in some cases this contravenes internal risk management assessment. We believe some supportive policies, such as tax cuts and directional RRR cuts for banks engaged in small and micro lending, will help to increase the risk tolerance of megabanks and enable them to take up more lending in line with policy agenda.

Table 5

Top 10 Banks With The Worst Credit Loss Ratio In 2017
Rank Bank New loan loss provisions/average customer loans (%) Net charge-off ratio (%) NPL ratio (%) Total credit growth in 2017(%)
1 Bank of Guiyang Co., Ltd. 3.29 1.00 1.34 41.91
2 Ping An Bank Co. Ltd. 2.70 2.25 1.70 2.04
3 Huishang Bank Co. Ltd. 2.31 0.86 1.05 19.17
4 Jiangsu Wujiang Rural Commercial Bank 2.02 1.65 1.64 8.31
5 Jiangsu Changshu Rural Commercial Bank Co.,Ltd. 2.00 0.67 1.14 12.78
6 Bank of Jinzhou Co., Ltd. 1.95 0.22 1.04 36.14
7 Bank of Ningbo Co. Ltd. 1.88 0.43 0.82 7.94
8 China CITIC Bank Co. Ltd. 1.84 1.11 1.68 5.28
9 Shanghai Pudong Development Bank Co. Ltd. 1.83 1.61 2.14 1.94
10 Bank of Chongqing Co. Ltd. 1.83 0.87 1.35 20.39
NPL--Nonperforming loans. Source: S&P Global Ratings, banks' annual reports.

In our view, the tightened regulations and supervision amid derisking will continue to constrain smaller banks. The trend of faster loan growth by smaller banks will thus continue to wane (see chart 13). Nevertheless, we anticipate smaller banks may try to engage in higher-yield loans, such as unsecured personal loans, to balance out their higher costs of funding.

In our base case, we forecast the combined ratio of nonperforming loans (NPLs) and special-mention loans (SMLs) to marginally inch up over the next 12 months, with NPLs rising in the mix. The potential slippage will mainly be triggered by regulatory tightening that exposes hidden credit losses and selectively curbs refinancing; we expect overall refinancing risks to remain manageable. Consequently, the sector's credit-loss provisioning ratio is also likely to increase.

Improvements in reported metrics during more reflationary 2017 conditions are waning. The average NPL ratio for Chinese banks jumped to 1.86% of total loans in the second quarter of 2018, having held at 1.74%-1.76% since 2016. This is partly due to the regulatory urge for banks to classify all overdue 90 days into NPL. We consider combined SML+NPL (aka "problematic loans") as a more useful ratio in assessing Chinese banks' asset quality. This ratio has been trending down, to 5.12% in the second quarter of 2018, after peaking at 5.86% in third quarter-2016 (see chart 16).

Chart 16

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Chart 17

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We see higher credit cost pressure coming from the following sources and risks:

More stringent loan classification.   Under regulatory requirement, most banks have classified NPL more stringently over the past year. We expect this trend to continue for all banks. This is because many loans overdue more than 90 days but not impaired now needs to be moved into the NPL category under regulatory guidance. Whereas megabanks have better loan classification, some JSBs and regional banks have yet to meet the target, so will likely see greater future NPL slippage (see chart 17).

Increased refinancing risk for weak corporates.   Shadow banking reforms have raised funding costs and refinancing risks for corporate borrowers, raising default risks, especially for private enterprises. Small banks have more concentrated in regional exposures.

Consolidation of China's property market.  As mortgage loan growth continues to slow, this will weigh on residential sales for property developers and further stress the liquidity of some smaller developers (see chart 18).

Delinquencies in consumer loans could also increase.   We see a risk of rising consumer loan defaults, from a very low base. Banks have been pursuing retail loans to diversify their loan portfolios and seek new growth (see chart 19). In this arena, financial institutions are increasingly competing with (and sometimes collaborating with) financial technology companies. This promising growth channel also could challenge loan origination ability and lead to consumer credit charge-offs. The fintech model appeals to some smaller city commercial banks and rural commercial banks with limited "big data" but a desire to pursue high-yield consumer credit. However, banks or many fintechs that have self-proclaimed superior consumer lending tools have yet to be tested by a full consumer credit cycle. It would not surprise us if some overly aggressive banks experience a sharp increase in consumer credit charge-offs.

More exposures to SMEs.  Banks are being encouraged to increase risk tolerance and direct funding to small and micro enterprises, in conjunction with various government measures to ease the "lack of funding and high funding cost" for the sector. Bank lending to small and micro firms has been faster than the increase in overall bank loans. As of the end of March 2018, the NPL ratio for small and micro enterprises was 2.75%, 1.7 percentage points higher than the rate for large-scale enterprises. Lending to small and micro-enterprises in China is fraught with risk. That said, banks remain risk averse to this segment despite policy encouragement. Mega banks are making efforts to enhance underwriting skill for such lending.

Implementation of IFRS9 may increase provisioning for domestically listed banks.  China's 24 Hong Kong-listed banks implemented the new accounting standard in 2018, with limited impact. The 17 domestically listed banks will start to implement the new standard from 2019. The impact is likely to be somewhat greater for this second batch, because they tend to have proportionally higher exposure to loan-like assets for which they thinly provisioned. Unlisted banks will also eventually implement the standard.

That said, we see an abrupt deterioration in NPLs as unlikely. For one reason, over the past year, banks have proactively cleaned up loan books through enhanced charge-offs and NPLs disposals. Banks are also encouraged by policy to write off their bad loans to create more room for increasing lending to support the real economy. Strong government intervention for troubled companies through credit committee or debt-for-equity swaps in industries with overcapacity has also helped.

Chart 18

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Chart 19

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Banks Are Turning To New Instruments To Meet Rising Capital Needs

Banks will need to increase capital over the next two years. Core tier 1 capital (CET1) ratios decreased in the first half 2018, in part due to stronger loan growth amid the clampdown on shadow financing (see chart 20). Higher regulatory costs and the impact of deleveraging is also constraining internal capital generation, despite an overall stabilizing trend in net interest margins (NIMs) in the second quarter of 2018, helped by loans being repriced higher and somewhat eased funding pressure (see chart 21).

Chart 20

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Chart 21

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We expect regulatory capital strain to persist in the coming year with further rolling out of regulatory initiatives. That said, we believe policymakers will be pragmatic in the implementation of new rules. For example, they already extended the deadline for new asset management rules to 2020 . Regulators have also proactively lowered selected banks' provision requirements to below 150% to underpin their capitalization.

In our scenario analysis, we tested the impact on CET1 ratio if: (1) all loan-like credit funded by off-balance-sheet WMPs brought back onto the balance sheet; (2) all loans overdue more than 90 days classified to NPL assuming 150% provision coverage ratio (see chart 22).

Chart 22

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Furthermore, banks that issued during China's first round of loss-absorbing additional tier 1 (AT1) instruments back in 2014-2015 will be under pressure to redeem as per the embedded call options, as is the normal practice. This will lead to higher refinancing needs, especially for the megabanks. It's possible that some smaller banks may not redeem due to capital constraints, although this may subject them to reputational risk and a higher cost of funding in the future.

Regulators have guided banks to retain more earnings to consolidate their core capital, and to replenish their capital in order to boost their support for the real economy. Five regulators jointly issued a plan to widen the market for capital instruments, including perpetual bonds and other loss-absorbing debt instruments. Regulators are also working on policies to allow institutions such as social security funds, insurance companies, brokerages, and fund companies to invest in such capital tools. Currently, a large proportion of tier 2 (T2) debts are cross-held by financial institutions, which may increase systematic risk.

More Chinese city and rural commercial banks have access to equity markets, with nine such institutions listing in domestically or abroad from 2017. Offshore AT1 issuance by Chinese banks reached US$15.1 billion in 2017, while onshore issuance rose almost a fourfold to RMB118 billion. T2 bond issuance hit a new high of RMB750 billion issued since 2017. Many banks also issued convertible bonds. Since the beginning of 2017, 12 listed banks have issued or announced plans to issue RMB 250 billion in convertible bonds. Some banks also use private placements, for example, Agricultural Bank of China Ltd., which privately placed US$15.8 billion earlier this year.

Securitization has emerged as a new channel of funding for Chinese banks in recent years. New securitization issuance soared 62.5% to RMB548 billion in 2017, and is likely to set another record in 2018 (see chart 23). Given the deleveraging environment, asset sales through securitization is a favorable source of funding for banks that have longer-tenor loan portfolios.

Chart 23

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Chart 24

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In particular, the issuance of residential mortgage-backed securities (RMBS) shot up in recent years (see chart 24). In 2017, banks issued RMB170.8 billion in RMBS, up 63% from 2016, and accounting for 31% of total ABS issued by banks. In the first nine months of 2018, this sector has seen over RMB346 billion new issuance, about 4x the number in the same period last year. Megabanks are frequent issuers in this product. China Construction Bank Corp., which has a large concentration on mortgages, issued RMB84 billion in RMBS in 2017, and RMB150 billion in the first three quarters of this year. With increasing investor interest in safer/higher rated products, banks can create more liquidity and room for asset growth by issuing RMBS. An upward loan pricing trend has also incentivized mortgage securitization. Issuing asset-backed securities (ABS) can also mitigate some capital pressure from NPL, as Chinese regulators allowed banks to repackage NPLs into securities in 2016. However, in the past two years, NPL-backed ABS issuance remains relatively thin and have yet to evolve into a mainstream tool for dealing with bad loans.

Whereas large banks, especially global systemically important banks, have stronger CET1 standing (see chart 25), they are utilizing their diversified funding channels to issue capital instruments in a process to meet their total loss-absorbing capacity (TLAC) requirements. Give that market conditions make capital-raising more difficult, many JSBs or regional banks have cut their dividends, shrunk assets or diversified into more retail business or micro lending which benefits from favorable regulatory risk weighting. Small and mid-sized banks that were most heavily engaged in shadow banking would have to set aside more provisions for those debts moving back to balance sheet especially under an increasingly stringent loan classification.

Chart 25

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Table 6

China's Least Capitalized Listed Commercial Banks (2017)
Rank Entity S&P Global Ratings' RAC ratio as of end-2017* (%) Projected S&P Global Ratings' RAC ratio as of end-2019* (%) Tier-1 capital ratio as of end-2017 (%)
1 China Zheshang Bank Co., Ltd. 3.33 3.00 9.96
2 Bank of Ningbo Co., Ltd. 3.74 4.16 9.41
3 Shengjing Bank Co., Ltd. 3.85 3.41 9.04
4 Bank of Tianjin Co., Ltd. 3.86 3.62 8.65
5 Bank of Jiangsu Co., Ltd. 3.94 3.60 10.40
6 Bank of Gansu Co., Ltd. 4.07 4.45 8.71
7 Bank of Chengdu Co., Ltd. 4.15 3.79 10.48
8 Ping An Bank Co., Ltd. 4.21 4.40 9.18
9 Hua Xia Bank Co., Ltd. 4.21 4.85 9.37
10 Shanghai Pudong Development Bank Co., Ltd. 4.23 4.70 10.24
Note: We have assumed the following: banks' returns on equity to be 90% of the average of the past two years'; and dividend payout ratio equals to actual dividend payout ratio in 2017. RAC--Risk-adjusted capital. *Our RAC estimate here considers risk exposures stemming from loan-like assets, such as investment receivables and off-balance-sheet wealth management products (WMPs). We view such WMPs as funding instruments, and expect banks to bear the credit risks (with the exception of certain product with underlying investments that are recorded as net asset value). Source: S&P Global Ratings, bank's annual reports.

So What Could Go Wrong?

China's banking system is undergoing big changes. The funding structure is in a flux as regulators clamp down on speculative interbank funding and less-regulated shadow funding. This has intensified sector-wide competition for core deposits and is raising demand for more market-oriented funding tools, including capital instruments and ABS.

We believe this structural change in funding is informing China's bank deleveraging and disseminating story. Efficient and effective credit allocation by banks is necessary, given that credit needs to target the sectors that will drive growth, without adding too much debt to the economy or worsening economic imbalances. Capital markets can facilitate the process, to the extent that market forces select who gets the most market funding, and bank underwriting standards are also critical.

In our view, regulatory tightening aimed at derisking can facilitate efficient and effective credit allocation to the desired economic sectors. China created a "super-regulator" earlier this year to cover both banking and insurance sectors to enhance supervision. Major Chinese banks have maintained reasonable underwriting standards and refrained from lending to overcapacity or high-risk sectors.

So what can go wrong, and where to watch for the warning signs?

In a less likely scenario, authorities may relax prudential regulation or increase regulatory forbearance amid short-term pain for the banking sector. That, together with the accommodative monetary policy, could refresh speculative activities. Banks may loosen underwriting standards and pile in to secure a first-mover advantage as new areas of lending opens up, such as consumer finance or government promoted small and micro-lending. If credit flows again to the traditional big borrowers, leverage in these industries will further increase as marginal efficiency declines. Such a trend would undermine China's multi-year efforts to lower corporate leverage and reduce systemic risk. Furthermore, escalated trade-war fears or rising defaults could undermine the market confidence and limit banks' new funding channels, leading to credit squeezes and economic contraction.

Chart 26

image

Table 7

Business Positions And Financial Profiles Of China's Listed Banks
Financial profile Business Profile
Below average Average Above average Superior
Superior
Sub-total 0 4
(1) ICBC
(2) China Construction Bank
(3) Agricultural Bank of China
(4) Bank of China
Above average
Sub-total 1 3 3
(38) Wuxi RCB (15) Bank of Beijing (5) Bank of Communications
(16) Bank of Shanghai (6) Postal Savings Bank of China
(23) Chongqing RCB (8) China Merchants Bank
Average
Sub-total 5 7 4
(28) Harbin Bank (17) Bank of Jiangsu (9) Shanghai Pudong Dvl'ment Bank
(32) Bank of Chengdu Co., Ltd. (19) Bank of Nanjing (10) China Minsheng Banking Corp.
(34) Bank of Qingdao (21) Bank of Ningbo (11) China CITIC Bank
(39) Jiangsu Jiangyin RCB (22) Huishang Bank (12) China Everbright Bank
(41) Jiangsu Wujiang RCB (24) Bank of Hangzhou
(25) Guangzhou RCB
(33) Bank of Chongqing
Below average
Sub-total 8 5 1
(26) Bank of Jinzhou (13) Ping An Bank (7) Industrial Bank
(29) Zhongyuan Bank (14) Hua Xia Bank
(30) Bank of Guiyang (18) China Zheshang Bank
(31) Bank of Zhengzhou (20) Shengjing Bank
(35) Bank of Gansu (27) Bank of Tianjin
(36) Jilin Jiutai RCB
(37) Jiangsu Changshu RCB
(40) Jiangsu Zhangjiagang RCB
Total Below average Average Above average Superior
14 15 8 4
RCB--Rural Commercial Bank.

Table 8

Credit Statistics Of China's 41 Listed Banks
Balance sheet data (mil. RMB) Earnings (mil. RMB) Capital (%) Asset quality (%) Funding & liquidity (%)
Rank Entity name Year Total assets Customer loans Total credits Net profit RAC before diversification adjustments NPL ratio SML ratio NCO ratio Stable funding ratio Liquidity coverage ratio (x)
1 Industrial and Commercial Bank of China Ltd. 2017 26,087,043 14,233,448 16,378,544 286,049 8.24 1.55 3.95 0.51 131.67 2.80
2016 24,137,265 13,056,846 15,437,556 278,249 8.40 1.62 4.47 0.58 130.30 2.77
2015 22,209,780 11,933,466 14,327,998 277,131 9.32 1.50 4.36 0.52 131.52 2.71
2014 20,609,953 11,026,331 12,724,800 275,811 7.98 1.13 2.90 0.35 135.47 2.97
2 China Construction Bank Corp. 2017 22,124,383 12,903,441 14,438,863 242,264 7.99 1.49 2.83 0.49 131.30 3.14
2016 20,963,705 11,757,032 13,569,846 231,460 7.60 1.52 2.87 0.61 127.31 2.67
2015 18,349,489 10,485,140 11,924,242 228,145 8.43 1.58 2.89 0.91 125.67 2.49
2014 16,744,130 9,474,523 10,544,600 227,830 7.77 1.19 2.97 0.40 128.07 2.82
3 Agricultural Bank of China Ltd. 2017 21,053,382 10,720,611 12,069,963 192,962 7.93 1.81 3.27 0.85 142.81 3.29
2016 19,570,061 9,719,639 11,104,674 183,941 7.80 2.37 3.88 0.86 145.33 3.49
2015 17,791,393 8,909,918 10,343,445 180,582 8.20 2.39 4.20 0.47 145.36 3.53
2014 15,974,152 8,098,067 9,246,803 179,461 7.28 1.54 3.84 0.37 149.29 4.66
4 Bank of China Ltd. 2017 19,467,424 10,896,558 11,880,232 172,407 7.38 1.45 2.91 0.64 121.98 2.22
2016 18,148,889 9,973,362 11,095,150 164,578 7.40 1.46 3.11 0.51 125.81 2.48
2015 16,815,597 9,315,860 10,488,655 170,845 8.09 1.43 2.50 0.50 121.04 2.32
2014 15,251,382 8,483,275 9,549,511 169,595 7.40 1.18 2.37 0.31 124.04 2.36
5 Bank of Communications Co. Ltd. 2017 9,038,254 4,456,914 5,528,970 70,223 7.38 1.50 2.93 0.44 107.44 1.29
2016 8,403,166 4,102,959 5,027,208 67,210 7.00 1.52 3.02 0.52 110.93 1.38
2015 7,155,362 3,722,006 4,705,944 66,528 7.26 1.51 3.17 0.45 111.97 1.53
2014 6,268,299 3,431,735 4,387,145 65,850 7.07 1.25 2.68 0.46 107.44 1.39
6 Postal Savings Bank of China Co. Ltd. 2017 9,012,551 3,630,135 4,358,802 47,683 6.42 0.75 0.68 0.12 160.49 13.31
2016 8,265,622 3,010,648 3,972,946 39,801 5.20 0.87 0.81 0.28 148.84 7.17
2015 7,296,364 2,471,853 3,622,632 34,859 4.86 0.80 1.50 0.32 155.54 5.47
2014 6,298,325 1,875,748 2,587,705 32,567 N.A. 0.64 2.30 0.20 193.26 19.03
7 Industrial Bank Co. Ltd. 2017 6,416,842 2,534,190 4,828,739 57,200 5.20 1.59 2.31 0.76 91.32 0.91
2016 6,085,895 2,172,613 4,573,920 53,850 4.60 1.65 2.59 1.36 80.98 0.75
2015 5,298,880 1,855,564 4,069,495 47,138 5.39 1.40 2.35 1.45 82.37 0.79
2014 4,406,399 1,652,987 3,045,385 47,138 5.26 1.06 1.82 0.75 102.36 1.20
8 China Merchants Bank Co. Ltd. 2017 6,297,638 3,565,044 5,425,271 70,150 6.06 1.61 1.60 0.55 118.65 1.96
2016 5,942,311 3,261,681 5,463,730 62,081 5.20 1.87 2.09 1.09 117.22 1.71
2015 5,474,978 2,824,286 4,764,038 57,696 6.11 1.68 2.61 1.38 112.31 1.48
2014 4,731,829 2,513,919 3,517,537 55,911 5.92 1.11 1.86 0.61 117.20 1.78
9 Shanghai Pudong Development Bank Co. Ltd. 2017 6,137,240 3,236,798 5,093,326 54,258 5.22 2.14 3.29 1.61 84.81 0.79
2016 5,857,263 2,805,131 4,996,332 53,099 4.70 1.89 3.82 1.24 85.38 0.81
2015 5,044,352 3,555,260 4,139,048 50,604 5.79 1.56 2.88 0.49 98.21 1.04
2014 4,195,924 2,892,902 3,220,153 47,026 5.34 1.06 2.12 0.36 109.89 1.40
10 China Minsheng Banking Corp. Ltd. 2017 5,902,086 2,909,037 4,249,843 49,813 5.40 1.71 4.06 0.77 88.84 0.87
2016 5,895,877 2,559,818 4,559,703 47,843 5.30 1.68 3.75 1.12 93.95 0.96
2015 4,520,688 2,143,400 3,094,209 46,111 6.30 1.53 3.69 1.00 112.86 1.40
2014 4,015,136 1,903,843 2,439,427 44,546 5.58 1.11 1.98 0.87 115.94 1.45
11 China CITIC Bank Co. Ltd. 2017 5,677,691 3,196,887 4,420,664 42,566 5.10 1.68 2.14 1.11 99.01 1.08
2016 5,931,050 2,877,927 4,198,920 41,629 5.10 1.69 2.65 1.12 104.58 1.20
2015 5,122,292 2,528,780 4,018,951 41,158 5.65 1.43 3.57 1.09 99.66 1.10
2014 4,138,815 2,187,908 3,108,114 40,692 5.76 1.30 3.12 0.55 107.75 1.46
12 China Everbright Bank Co. Ltd. 2017 4,088,243 2,089,785 3,133,722 31,545 5.91 1.59 2.97 0.56 94.36 0.99
2016 4,020,042 1,852,347 3,143,017 30,329 5.10 1.60 3.78 0.92 90.79 0.92
2015 3,167,710 1,513,543 2,618,473 29,528 6.81 1.57 4.49 0.61 96.64 1.33
2014 2,737,010 1,299,455 2,088,322 28,883 5.56 1.17 3.23 0.45 108.94 1.61
13 Ping An Bank Co. Ltd. 2017 3,248,474 1,704,230 2,396,684 23,189 4.85 1.70 3.70 2.25 108.62 1.37
2016 2,953,434 1,475,801 2,348,727 22,599 5.10 1.74 4.11 2.55 113.16 1.51
2015 2,507,149 1,216,138 1,847,854 21,865 5.75 1.45 4.15 1.89 125.17 1.87
2014 2,186,459 1,024,734 1,366,982 19,802 5.48 1.02 3.61 0.89 129.05 2.06
14 Hua Xia Bank Co. Ltd. 2017 2,508,927 1,394,082 1,902,433 19,819 5.32 1.76 4.60 0.71 104.16 1.23
2016 2,356,235 1,216,654 1,766,989 19,677 5.40 1.67 4.20 0.67 112.94 1.44
2015 2,020,604 1,069,172 1,441,159 18,883 5.65 1.52 4.21 0.51 121.82 1.67
2014 1,851,628 939,989 1,362,314 17,981 5.03 1.09 2.58 0.41 118.68 1.74
15 Bank of Beijing Co. Ltd. 2017 2,329,805 1,077,101 1,643,996 18,733 5.77 1.24 1.56 0.48 104.86 1.21
2016 2,116,339 899,907 1,354,261 17,802 5.90 1.27 1.46 0.37 117.51 1.45
2015 1,844,409 775,390 1,021,780 16,839 6.40 1.12 1.05 0.08 128.04 1.57
2014 1,524,437 675,288 859,268 15,623 6.30 0.86 1.29 0.01 127.39 1.62
16 Bank of Shanghai Co. Ltd. 2017 1,807,767 664,022 953,405 15,328 6.80 1.15 2.08 0.28 101.74 1.09
2016 1,755,371 553,999 943,599 14,308 6.50 1.17 2.16 0.58 101.10 1.07
2015 1,449,140 536,508 978,799 13,043 7.37 1.19 2.06 0.84 102.02 1.10
2014 1,187,452 484,521 795,936 11,400 6.77 0.98 1.44 0.64 111.87 1.33
17 Bank of Jiangsu Co. Ltd. 2017 1,770,551 777,870 1,255,920 11,875 4.42 1.41 2.54 0.73 105.97 1.22
2016 1,598,292 674,573 1,065,217 10,611 5.30 1.43 3.01 0.78 102.79 1.13
2015 1,290,333 569,000 862,542 9,497 5.95 1.41 3.12 0.56 107.15 1.24
2014 1,038,309 488,512 648,469 8,685 5.58 1.30 2.18 0.43 116.45 1.55
18 China Zheshang Bank Co. Ltd. 2017 1,536,752 672,879 1,227,486 10,950 3.87 1.15 1.58 0.25 83.56 0.73
2016 1,354,855 459,493 1,187,684 10,153 3.60 1.33 2.14 0.68 84.97 0.78
2015 1,031,650 345,423 680,777 7,051 4.05 1.23 1.86 0.86 77.79 0.69
2014 669,957 259,023 403,925 5,096 4.25 0.88 1.40 0.88 94.34 0.97
19 Bank of Nanjing Co. Ltd. 2017 1,141,163 388,952 835,632 9,668 6.45 0.86 1.64 0.40 130.14 1.96
2016 1,063,900 331,785 766,205 8,262 5.50 0.87 1.93 0.73 138.15 2.13
2015 805,020 251,198 616,792 7,001 6.80 0.45 1.92 0.66 104.32 1.28
2014 573,150 174,685 417,369 5,609 5.79 0.51 2.24 0.40 106.76 1.31
20 Shengjing Bank Co. Ltd. 2017 1,030,617 279,513 549,992 7,580 4.00 1.49 1.70 0.00 102.67 1.13
2016 905,483 235,417 508,901 6,865 4.80 1.74 2.34 0.04 107.33 1.14
2015 701,629 195,460 428,425 6,211 6.22 0.42 1.43 0.09 120.19 1.47
2014 503,371 158,644 248,192 5,405 7.18 0.44 0.62 0.02 133.43 1.83
21 Bank of Ningbo Co. Ltd. 2017 1,032,042 346,201 654,817 9,334 4.38 0.82 0.68 0.43 108.51 0.90
2016 885,020 302,507 606,671 7,810 4.10 0.91 1.33 0.92 120.59 1.58
2015 716,465 255,689 373,786 6,544 4.66 0.92 1.77 0.77 98.02 1.13
2014 554,113 210,062 291,604 5,627 5.69 0.89 1.77 0.50 107.49 1.37
22 Huishang Bank Co. Ltd. 2017 908,100 341,515 679,186 7,615 6.48 1.05 1.43 0.86 106.60 1.24
2016 754,774 295,886 569,921 6,870 6.80 1.07 1.96 0.97 114.34 1.51
2015 636,131 251,032 435,319 6,161 7.66 0.96 2.89 0.54 111.65 1.32
2014 482,764 219,397 285,375 5,673 7.34 0.83 2.07 0.22 130.72 1.91
23 Chongqing Rural Commercial Bank Co. Ltd. 2017 905,778 338,347 499,280 8,936 7.07 1.77 2.50 0.40 121.24 1.54
2016 803,158 300,421 460,550 7,945 6.40 0.96 2.70 0.37 125.29 1.64
2015 716,805 268,586 397,412 7,223 7.40 0.98 2.26 0.21 130.53 1.77
2014 618,889 242,198 341,473 6,828 8.00 0.78 2.35 0.09 139.95 2.02
24 Bank of Hangzhou Co. Ltd. 2017 833,339 283,835 496,212 4,550 5.07 1.59 2.85 0.88 110.11 1.34
2016 720,424 246,608 462,089 4,021 4.60 1.62 4.82 1.07 94.94 1.02
2015 545,315 215,256 350,912 3,704 5.44 1.36 4.97 0.95 139.33 2.97
2014 418,541 196,657 294,326 3,506 5.29 1.20 4.30 1.18 126.18 2.21
25 Guangzhou Rural Commercial Bank Co. Ltd. 2017 735,714 294,013 475,023 5,709 6.11 1.51 2.41 0.09 127.52 1.74
2016 660,951 245,891 421,151 5,026 5.30 1.81 3.82 1.06 117.16 1.40
2015 582,807 223,659 309,856 5,001 6.20 1.80 4.64 0.92 135.32 1.92
2014 466,608 185,981 252,533 5,375 6.82 1.54 4.83 0.24 169.62 3.70
26 Bank of Jinzhou Co., Ltd. 2017 723,418 222,141 594,890 8,977 6.31 1.04 2.30 0.22 90.83 0.92
2016 539,060 131,463 436,977 8,130 6.00 1.14 3.61 0.09 99.34 1.09
2015 361,660 101,174 280,463 4,889 6.59 1.03 3.77 0.25 94.22 0.98
2014 250,693 88,799 171,463 2,116 5.69 0.99 4.65 (0.01) 101.66 1.16
27 Bank of Tianjin Co. Ltd. 2017 701,914 248,881 520,293 3,916 4.26 1.50 4.28 0.07 82.55 0.76
2016 657,310 214,001 413,604 4,522 4.80 1.48 4.44 0.35 99.24 1.06
2015 565,668 184,604 308,553 4,916 5.61 1.34 3.50 0.39 114.70 1.40
2014 478,859 170,918 246,189 4,417 5.99 1.08 3.10 0.23 122.68 1.55
28 Harbin Bank Co. Ltd. 2017 564,255 253,450 585,648 5,249 6.18 1.70 2.80 0.16 109.88 1.46
2016 539,016 216,911 404,524 4,877 5.80 1.53 2.61 0.13 111.43 1.40
2015 444,851 159,232 237,678 4,458 7.79 1.31 2.47 0.11 138.90 2.43
2014 343,642 128,133 191,072 3,807 9.08 1.09 1.61 0.03 135.32 2.27
29 Zhongyuan Bank Co. Ltd. 2017 521,990 198,903 337,563 3,839 8.63 1.83 4.57 0.17 109.24 1.25
2016 433,071 164,889 262,784 3,359 7.54 1.86 4.80 0.85 107.05 1.20
2015 306,147 136,996 136,996 3,080 N.A. 1.95 12.64 0.40 125.92 2.05
2014 207,069 111,081 N.A. 2,555 N.A. 1.92 6.35 0.30 141.27 9.56
30 Bank of Guiyang Co. Ltd. 2017 464,106 125,514 284,294 4,173 5.73 1.34 3.19 1.00 110.29 1.36
2016 372,253 102,494 200,339 3,654 4.50 1.42 3.95 2.33 126.08 1.96
2015 238,197 83,174 N.A. 3,222 N.A. 1.48 4.63 0.47 141.41 2.84
2014 156,100 70,071 N.A. 2,436 N.A. 0.81 1.91 0.12 148.43 5.95
31 Bank of Zhengzhou Co. Ltd. 2017 435,829 128,456 323,972 4,280 5.39 1.50 3.32 0.98 104.64 1.18
2016 366,148 111,092 255,583 3,999 4.83 1.31 2.93 0.86 104.56 1.16
2015 265,623 94,294 180,738 3,356 8.73 1.10 2.31 0.18 119.12 1.56
2014 204,289 77,986 138,166 2,463 N.A. 0.75 1.46 0.05 118.73 1.59
32 Bank of Chengdu Co. Ltd. 2017 434,539 148,663 233,034 3,909 4.31 1.69 2.74 0.97 146.76 2.35
2016 360,947 136,496 190,940 2,577 5.50 2.21 3.16 1.98 143.52 2.72
2015 321,445 134,408 179,255 2,816 7.52 2.35 3.65 0.74 146.66 2.90
2014 300,230 124,890 163,508 3,548 6.06 1.19 2.78 0.16 144.44 2.49
33 Bank of Chongqing Co. Ltd. 2017 422,763 177,207 310,135 3,764 5.77 1.35 3.91 0.87 101.21 1.09
2016 373,104 151,021 257,612 3,502 5.40 0.96 3.96 0.36 115.39 1.37
2015 319,808 136,996 222,007 3,170 6.58 0.97 4.25 0.29 115.47 1.45
2014 274,531 106,449 180,722 2,827 6.40 0.69 2.12 0.24 122.66 1.57
34 Bank of Qingdao Co. Ltd. 2017 306,276 98,061 204,736 1,904 6.91 1.69 5.45 1.09 96.05 1.01
2016 277,988 87,168 162,952 2,089 N.A. 1.36 3.98 0.89 100.96 1.08
2015 187,235 72,696 113,624 1,814 N.A. 1.19 3.17 0.31 115.31 1.64
2014 156,166 62,988 N.A. 1,495 N.A. N.A. N.A. 0.21 116.73 1.67
35 Bank of Gansu Co. Ltd. 2017 271,148 130,284 190,170 3,358 4.33 1.74 5.50 1.06 124.07 2.03
2016 245,056 107,855 196,734 1,917 N.A. 1.81 2.00 1.35 118.84 1.71
2015 211,931 90,627 90,627 1,295 N.A. N.A. N.A. (0.06) 118.02 1.59
2014 165,100 56,496 N.A. 1,060 N.A. N.A. N.A. N.A. 132.32 1.99
36 Jilin Jiutai Rural Commercial Bank Corporation Ltd. 2017 187,009 78,827 111,658 1,638 7.97 1.73 2.20 (0.16) 110.70 1.52
2016 191,471 62,101 81,471 2,316 N.A. 1.41 3.30 (0.05) 149.58 2.15
2015 141,953 47,882 63,656 1,402 N.A. 1.42 3.17 (0.09) 135.51 1.94
2014 81,855 34,372 N.A. 1,231 N.A. 1.19 1.60 (0.06) 137.14 2.79
37 Jiangsu Changshu Rural Commercial Bank Co., Ltd. 2017 145,825 77,811 118,080 1,264 5.95 1.14 2.66 0.67 113.37 1.66
2016 129,982 66,419 104,695 1,041 N.A. 1.29 4.20 1.39 115.02 1.67
2015 108,504 57,611 83,169 966 N.A. 1.37 3.92 0.93 123.62 2.44
2014 101,670 48,669 N.A. 999 N.A. 0.93 4.50 0.08 130.03 2.26
38 Wuxi Rural Commercial Bank Co., Ltd. 2017 137,125 66,074 80,182 995 6.32 1.38 1.49 0.52 124.63 3.31
2016 124,633 60,257 75,498 893 N.A. 1.39 1.62 0.52 118.02 2.48
2015 115,491 55,505 66,848 833 N.A. 1.17 1.39 0.40 128.41 2.73
2014 104,463 50,464 N.A. 926 N.A. 1.15 1.69 0.28 N.A. N.A.
39 Jiangsu Jiangyin Rural Commercial Bank Co., Ltd. 2017 109,403 55,853 61,921 808 4.91 N.A. N.A. 0.10 123.47 2.32
2016 104,085 52,526 60,322 778 N.A. N.A. N.A. 0.78 126.96 2.54
2015 90,478 49,857 55,686 814 N.A. N.A. N.A. 0.87 128.16 2.70
2014 83,587 48,392 N.A. 818 N.A. N.A. N.A. 0.30 132.54 2.70
40 Jiangsu Zhangjiagang Rural Commercial Bank Co., Ltd. 2017 103,173 49,111 63,677 763 5.18 1.78 6.42 1.24 111.30 1.62
2016 90,178 44,325 54,113 689 N.A. 1.96 6.95 0.99 114.60 1.87
2015 82,354 39,849 46,070 673 N.A. 1.96 8.68 1.59 115.20 1.73
2014 71,970 38,300 N.A. 731 N.A. N.A. N.A. 1.65 128.31 2.57
41 Jiangsu Wujiang Rural Commercial Bank Co., Ltd 2017 95,271 49,085 55,884 731 6.92 1.64 6.21 1.65 122.42 2.25
2016 81,348 45,445 51,595 650 N.A. 1.78 15.89 1.29 128.45 3.93
2015 71,453 40,994 44,383 604 N.A. 1.86 21.43 1.65 128.14 3.64
2014 61,945 38,044 N.A. 768 N.A. 1.70 21.77 0.97 131.52 7.64
mil.--Million. RMB--Chinese renminbi. RAC--Risk adjusted capital. NPL--Nonperforming loans. SML--Special mention loans. NCO--Net charge-offs. LDR--Loan to deposit ratio. N/A and N.A.--Not applicable or available.

This report does not constitute a rating action.

Primary Credit Analyst:Liang Yu, PhD, Hong Kong (852) 2533-3541;
liang.yu@spglobal.com
Secondary Contacts:Ryan Tsang, CFA, Hong Kong (852) 2533-3532;
ryan.tsang@spglobal.com
Harry Hu, CFA, Hong Kong (852) 2533-3571;
harry.hu@spglobal.com
Research Assistants:Wenyi He, Hong Kong
Jiewei Xu, Beijing

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