2020 CORPORATE SOCIAL RESPONSIBILITY REPORT
Extracted ESG KPIs
KPIs are organized by ESG aspects.
The types of emissions and respective emissions data.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Nitrogen oxides reduced by green credit | million tons | 1.39 | 72 |
Description of emissions target(s) set and steps taken to achieve them.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Ammonia nitrogen reduced by green credit | tons | 80000 | 72 |
| Carbon dioxide emissions reduced by green credit | million tons | 87.13 | 72 |
| Chemical oxygen demand reduced by green credit | tons | 450000 | 72 |
| Sulfur dioxide reduced by green credit | million tons | 1.64 | 72 |
Direct and/or indirect energy consumption by type (e.g. electricity, gas or oil) in total (kWh in '000s) and intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2018 | 2019 | 2020 | Report Pages |
|---|---|---|---|---|---|
| Electricity consumption per capita in Head Office (kwh/person) | kwh/person | 5866.87 | 6042.16 | 5931.81 | 22 |
| Gas consumption per capita in Head Office (m³/person) | m³/person | 63.04 | 62.82 | 48.15 | 22 |
Water consumption in total and intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2018 | 2019 | 2020 | Report Pages |
|---|---|---|---|---|---|
| Water consumption per capita in Head Office (m³/person) | m³/person | 44.31 | 47.61 | 46.88 | 22 |
| Water saved by green credit | million tons | 52.94 | 72 |
Description of the significant impacts of activities on the environment and natural resources and the actions taken to manage them.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Excellent ESG Enterprise at Fifth Golden Achievement Awards | Rated | 109 | |
| Number of green bonds issued | bonds | 4 | 11 |
Total workforce by gender, employment type (for example, full- or part-time), age group and geographical region.
| Indicator | Unit | 2018 | 2019 | 2020 | Report Pages |
|---|---|---|---|---|---|
| Number of directors on Board of Directors | 13 | 109 | |||
| Number of employees helped and cared for during COVID-19 | persons | 28000 | 100 | ||
| Number of executive directors on Board of Directors | 3 | 109 | |||
| Number of external supervisors on Board of Supervisors | 3 | 109 | |||
| Number of inclusive loans granted to micro and small corporate customers | 300000 | 7 | |||
| Number of independent non-executive directors on Board of Directors | 5 | 109 | |||
| Number of non-executive directors on Board of Directors | 5 | 109 | |||
| Number of senior executives | 7 | 109 | |||
| Number of supervisors on Board of Supervisors | 8 | 109 | |||
| Return on average total assets | % | 0.93 | 0.9 | 0.83 | 21 |
| Return on weighted average net assets | % | 13.66 | 12.43 | 11.35 | 21 |
| Shareholders’ dividends | RMB 100 million | 608.62 | 636.62 | 647.82 | 21 |
| Total assets | RMB 100 million, million RMB, trillion RMB | 226084.52 | 248774.91 | 272050.47 | 9, 17, 21 |
| Total loans and advances to customers | RMB 100 million | 119403.22 | 133603.42 | 151704.42 | 21 |
The percentage of employees trained by gender and employee category (e.g. senior management, middle management).
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Number of employees trained | employees | 895800 | 98 |
| Number of internal trainers certified and engaged at branch level | persons | 3270 | 100 |
| Number of internal trainers certified and engaged at head-office-level | persons | 1604 | 100 |
| Number of training courses held for employees | courses | 7900 | 98 |
Number of suppliers by geographical region.
| Indicator | Unit | 2018 | 2019 | 2020 | since 2016 | Report Pages |
|---|---|---|---|---|---|---|
| Balance of Huinong e-Loans | RMB, billion RMB | 350000000000 | 7, 51 | |||
| Balance of agriculture-related loans | billion RMB | 4290.667 | 51 | |||
| Balance of county-level loans | RMB | 5000000000000 | 7 | |||
| Balance of green credit | RMB, trillion RMB | 1.51 | 11, 72 | |||
| Balance of green credit (RMB 100 million) | RMB 100 million | 10504 | 11910 | 15149 | 22 | |
| Balance of hog breeding loans | billion RMB | 34.38 | 46 | |||
| Balance of inclusive finance loans for micro and small enterprises | RMB | 961520000000 | 7 | |||
| Balance of loans for 832 key state-level poverty alleviation counties | trillion RMB | 1.28 | 9 | |||
| Balance of loans for county-level urbanization | RMB | 862300000000 | 10 | |||
| Balance of loans for farmers | billion RMB | 435.267 | 51 | |||
| Balance of loans for food security | RMB | 1173000000000 | 10 | |||
| Balance of loans for new agricultural business entities | RMB | 371200000000 | 10 | |||
| Balance of loans for targeted poverty alleviation, 52 remaining impoverished counties under strict supervision | billion RMB | 77.6 | 9 | |||
| Balance of loans for targeted poverty alleviation, counties in extreme poverty | billion RMB | 489.13 | 9 | |||
| Balance of loans for targeted poverty alleviation, counties in extreme poverty, and 52 remaining impoverished counties under strict supervision | billion RMB | 483.58 | 9 | |||
| Balance of loans for the cultural industry | billion RMB | 219.914 | 81 | |||
| Balance of loans for the education industry | billion RMB | 46.74 | 81 | |||
| Balance of loans to the whole hog industry chain | billion RMB | 55.45 | 46 | |||
| Growth rate of Huinong e-Loans | % | 79 | 7 | |||
| Growth rate of county-level loans | % | 16.5 | 7 | |||
| Growth rate of inclusive finance loans for micro and small enterprises | % | 62 | 7 | |||
| Increase in Huinong e-Loans balance | billion RMB | 156.14 | 51 | |||
| Increase in balance of loans for targeted poverty alleviation, 52 remaining impoverished counties under strict supervision | % | 21.5 | 9 | |||
| Increase in balance of loans for targeted poverty alleviation, counties in extreme poverty | % | 22.7 | 9 | |||
| Increase in balance of loans to the whole hog industry chain | billion RMB | 31.95 | 46 | |||
| Increase in number of enterprises and farmers provided credit support in hog-related industries | 22539 | 46 | ||||
| Loans issued for rural self-built houses (Suzhou Branch, Kunshan) | million RMB | 132 | 59 | |||
| Number of accounts for leading 'new infrastructure' enterprises served by ABC | 1500 | 70 | ||||
| Number of counties covered by management platform | 439 | 51 | ||||
| Number of demonstration villages using ABC Banking App | 14000 | 51 | ||||
| Number of domestic branch outlets | 22938 | 17 | ||||
| Number of domestic subsidiaries | 11 | 17 | ||||
| Number of effective county scenarios built | 5482 | 51 | ||||
| Number of enterprises and farmers provided credit support in hog-related industries | 74586 | 46 | ||||
| Number of key enterprises contacted in hog industry | 110 | 46 | ||||
| Number of key enterprises issuing epidemic prevention and control bonds | 19 | 46 | ||||
| Number of major subsidiaries | 16 | 17 | ||||
| Number of new physical outlets | 86 | 9 | ||||
| Number of overseas branch outlets | 13 | 17 | ||||
| Number of overseas representative offices | 3 | 17 | ||||
| Number of overseas subsidiaries | 5 | 17 | ||||
| Number of self-service outlets built in poor villages and towns since 2016 | 599 | 32 |
Description of practices relating to engaging suppliers, number of suppliers where the practices are being implemented, and how they are implemented and monitored.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Number of outlets introduced with digital empowerment | outlets | 7309 | 11 |
Number of products and service related complaints received and how they are dealt with.
| Indicator | Unit | 2018 | 2019 | 2020 | since 2016 | Report Pages |
|---|---|---|---|---|---|---|
| Electronic channel financial transactions as proportion of total transactions (%) | % | 98 | 98 | 99 | 22 | |
| Number of 5G Smart Banking branch outlets | outlets | 69 | 11 | |||
| Number of customers with rural self-built houses receiving loans (Suzhou Branch, Kunshan) | customers | 462 | 59 | |||
| Number of mobile banking customers | million | 165 | 51 | |||
| Number of monthly active mobile banking customers | customers | over 100000000 | 11 | |||
| Number of monthly active mobile banking users | million | 46.89 | 51 | |||
| Number of people directly served and radiated by new outlets since 2016 | 12000000 | 32 |
Description of quality assurance process and recall procedures.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Number of new self-service banks | 48 | 9 |
Number of concluded legal cases regarding corrupt practices brought against the issuer or its employees during the reporting period and the outcomes of the cases.
| Indicator | Unit | 2018 | 2019 | 2020 | Report Pages |
|---|---|---|---|---|---|
| Capital adequacy ratio | % | 15.12 | 16.13 | 16.59 | 17, 21 |
Description of preventive measures and whistle-blowing procedures, and how they are implemented and monitored.
| Indicator | Unit | 2020 | Report Pages |
|---|---|---|---|
| Number of supervisors representing employees on Board of Supervisors | 3 | 109 | |
| Number of supervisors representing shareholders on Board of Supervisors | 2 | 109 |
Focus areas of contribution (e.g. education, environmental concerns, labour needs, health, culture, sport).
| Indicator | Unit | 2019 | 2020 | 2021 | since 2016 | Report Pages |
|---|---|---|---|---|---|---|
| ABC employees honored as National Outstanding Individuals in Poverty Alleviation | 3 | 26 | ||||
| ABC institutions honored as National Outstanding Institutions in Poverty Alleviation | 5 | 26 | ||||
| Coverage of 'Hui Nong Tong' electronic devices in 832 key state-level poverty alleviation counties | % | 89.5 | 9 | |||
| ESG Gold Award by The Asset magazine | Awarded | 109 | ||||
| ESG rating by MSCI (Morgan Stanley Capital International) | BBB | 109 | ||||
| Helped sell agricultural products from poor areas | billion RMB | 1.67 | 9 | |||
| Housing area improved for farmers (Jiangsu Branch) | million square meters | 9.5 | 59 | |||
| Jining Branch loans granted to major transportation and water conservancy projects | million RMB | 500 | 70 | |||
| Loans and advances to customers | million RMB | 15170442 | 17 | |||
| Models of financial poverty alleviation summarized and promoted by Agricultural Bank of China | 25 | 26 | ||||
| New loans to affordable housing projects | billion RMB | 40 | 81 | |||
| Number of 'Clean Your Plate' campaign events | events | 3997 | 11 | |||
| Number of administrative villages covered by management platform | 64800 | 51 | ||||
| Number of education institutions included in bank-university cooperation program | 402 | 81 | ||||
| Number of environmental campaigns organized and participated by ABC | 3397 | 102 | ||||
| Number of manual outlets built in poor villages and towns since 2016 | 168 | 32 | ||||
| Number of mobile service vehicles used in poverty-stricken areas | 43 | 9 | ||||
| Number of policies introduced to support hog industry development | 19 | 46 | ||||
| Number of rural households benefiting from Huinong e-Loans | 2760000 | 7 | ||||
| Number of targeted poverty alleviation counties in 'Small Bonus Points for Big Dreams' campaign | 10 | 102 | ||||
| Poverty-stricken counties receiving financial services under Opinions on Providing Solid Financial Services for Poverty Alleviation | 52 | 26 | ||||
| Poverty-stricken villages receiving financial services under Opinions on Providing Solid Financial Services for Poverty Alleviation | 1113 | 26 |
Resources contributed (e.g. money or time) to the focus area.
| Indicator | Unit | 2018 | 2019 | 2020 | Report Pages |
|---|---|---|---|---|---|
| ABC bonds underwritten for leading 'new infrastructure' enterprises | billion RMB | 10 | 70 | ||
| ABC loans granted to leading 'new infrastructure' enterprises | billion RMB | 10 | 70 | ||
| Amount donated in 'Small Bonus Points for Big Dreams' campaign | RMB | 806500 | 102 | ||
| Direct purchase of agricultural products from poor areas via Poverty Alleviation E-Mall | million RMB | 305 | 9 | ||
| Epidemic prevention and control bonds underwritten by ABC | billion RMB | 16.98 | 46 | ||
| Exclusive loan programs for farmers (Jiangsu Branch) | billion RMB | 21.3 | 59 | ||
| Funds raised from green bonds | RMB | 2780000000 | 11 | ||
| Investment in anti-epidemic material purchase and assistance provision for employees | million RMB | 133 | 100 | ||
| Net increase in number of Internet scenarios | scenarios | 80500 | 11 | ||
| Number of farmers benefiting from Huinong e-Loans | million | 2.76 | 51 | ||
| Number of farmers receiving exclusive loans (Jiangsu Branch) | farmers | 64000 | 59 | ||
| Number of farmers served by loans | million | 3.89 | 51 | ||
| Number of issues of epidemic prevention and control bonds underwritten | 20 | 46 | |||
| Number of left-behind impoverished children assisted in 'Small Bonus Points for Big Dreams' campaign | 655 | 102 | |||
| Number of poor people lifted out of poverty | million | 16.46 | 9 | ||
| Number of young employees providing volunteer services | 55000 | 102 | |||
| SIENSOL EP GREEN ASSET-BACKED NOTES issuance | RMB | 555000000 | 75 | ||
| Social contribution value per share | RMB | 2.34 | 17 | ||
| Social contribution value per share (RMB) | RMB | 2.06 | 2.27 | 2.34 | 22 |
| Taxes | RMB 100 million | 838.32 | 929.81 | 1040.02 | 21 |
| Taxes paid | billion RMB | 104.002 | 17 | ||
| Total amount donated by ABC for charitable activities | million RMB | 199.17 | 102 | ||
| Total hours of volunteer services provided by young employees | hours | 140000 | 102 | ||
| Total offering size of epidemic prevention and control bonds | billion RMB | 26.6 | 46 | ||
| Total participants in environmental campaigns | 35000 | 102 |
The types of emissions and respective emissions data.
| Standard Indicator | Unit | 2020 |
|---|---|---|
| NOₓ Emissions | million tons | 1.39 |
Direct (Scope 1) and energy indirect (Scope 2) greenhouse gas emissions (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit |
|---|---|
| Direct GHG Emissions (Scope 1) | Tons |
| Indirect Energy Emissions (Scope 2) | Tons |
| Total GHG Emissions | Tons |
| Total GHG Emissions Intensity (By Employee) | Tons/person |
Total hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit |
|---|---|
| Hazardous Waste Incineration | million tons |
Total non-hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit |
|---|---|
| Non-Hazardous Waste (Electronic Waste) | Sets |
Description of emissions target(s) set and steps taken to achieve them.
| Standard Indicator | Unit | 2020 |
|---|---|---|
| Ammonia Nitrogen Emissions Reduction Compared to Last Year | tons | 80000 |
| CO2 Emissions Reduction Compared to Last Year | million tons | 87.13 |
| SO2 Emissions Reduction Compared to Last Year | million tons | 1.64 |
Direct and/or indirect energy consumption by type (e.g. electricity, gas or oil) in total (kWh in '000s) and intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2018 | 2019 | 2020 |
|---|---|---|---|---|
| Diesel Fuel Consumption | Tons | |||
| Gasoline Consumption | Tons | |||
| LPG Consumption | Tons | |||
| Natural Gas Consumption | Cubic Meters | 63.04 | 62.82 | 48.15 |
| Purchased Electricity | kWh | |||
| Purchased Electricity Intensity (By Employee) | kwh/person | 5866.87 | 6042.16 | 5931.81 |
| Total Energy Consumption | Tons of standard coal | |||
| Total Purchased Energy | MkJ |
Water consumption in total and intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2018 | 2019 | 2020 |
|---|---|---|---|---|
| Water Consumption | million tons | 52.94 | ||
| Water Consumption in Office | m³/person | 44.31 | 47.61 | 46.88 |
Description of the significant impacts of activities on the environment and natural resources and the actions taken to manage them.
| Standard Indicator | Unit |
|---|---|
| Total Investment in Ecological Restoration | RMB |
Description of the significant climate-related issues which have impacted, and those which may impact, the issuer, and the actions taken to manage them.
| Standard Indicator | Unit |
|---|---|
| Investment in Climate Change Management | RMB |
Total workforce by gender, employment type (for example, full- or part-time), age group and geographical region.
| Standard Indicator | Unit | 2018 | 2019 | 2020 |
|---|---|---|---|---|
| Number of Bachelor's Degree Employees | persons | 242595 | ||
| Number of Below Junior College Employees | persons | 34758 | ||
| Number of Doctoral Degree Employees | persons | 549 | ||
| Number of Employees Aged 30-50 | persons | 237663 | ||
| Number of Employees Aged Above 50 | persons | 134063 | ||
| Number of Employees Aged Below 30 | persons | 87274 | ||
| Number of Female Employees | persons | 208151 | ||
| Number of Male Employees | persons | 250849 | ||
| Number of Master's Degree Employees | persons | 31547 | ||
| Number of Total Employees | persons | 473691 | 464011 | 459000 |
| Percentage of Female Employees | % | 46.1 | 45.6 | 45.3 |
Employee turnover rate by gender, age group and geographical region.
| Standard Indicator | Unit |
|---|---|
| Turnover Rate of Total Employees | % |
Number and rate of work-related fatalities occurred in each of the past three years including the reporting year.
| Standard Indicator | Unit |
|---|---|
| Number of Work-related Fatalities | |
| Work-related Fatalities Rate |
The percentage of employees trained by gender and employee category (e.g. senior management, middle management).
| Standard Indicator | Unit | 2020 |
|---|---|---|
| Percentage of Trained Female Employees | % | 43.5 |
| Percentage of Trained General Employees | % | 78 |
| Percentage of Trained Male Employees | % | 46.1 |
| Percentage of Trained Middle Management | % | 15.9 |
The average training hours completed per employee by gender and employee category.
| Standard Indicator | Unit |
|---|---|
| Total Training Hours | person*hours |
Number of products and service related complaints received and how they are dealt with.
| Standard Indicator | Unit |
|---|---|
| Complaints Handling Rate | % |
| Satisfaction Rate of Customer Complaint Handling | % |
Resources contributed (e.g. money or time) to the focus area.
| Standard Indicator | Unit | 2020 |
|---|---|---|
| Number of Employees Participating in Volunteer Activities | 55000 | |
| Number of Participations in Volunteer Activities | 35000 | |
| Total Public Welfare Donations | RMB | 199170000 |
| Total Volunteer Service Hours | hours | 140000 |