Company Profile

EBROKER GROUP

8036 Software - Application
Description

eBroker Group Limited, an investment holding company, provides financial software solution services in Hong Kong, Macau, Singapore, and Mainland China. The company offers front offices solution services, back-office solution services, installation and customization services, managed cloud services, and other services income. It also provides AI intelligent investment management, front and back-end solutions, institutional investment management solutions, wealth management solutions, asset management solutions, low latency high frequency trading solution, cloud service solutions, HKEX quotes service, advanced solutions, customized financial solutions; and eBrAIny a self-developed artificial intelligence investment technology. In addition, the company offers automated trading solutions; computer maintenance services; and engages in the research and development activities, as well as sells computer products. It serves financial institutions comprising brokerage firms, proprietary trading firms, and management wealth companies. eBroker Group Limited was incorporated in 2016 and is based in Tsim Sha Tsui, Hong Kong.

Reports

This company has 7 ESG reports available.

ESG Performance Overview

Select a KPI indicator to view performance trend

KPI Indicators

A1.1 Emission Types and Data
27 Data Points
Indicator Data Points Actions
SOₓ Emissions 9
NOₓ Emissions 9
Airborne Particulate Matter (PM) Emissions 9
A1.2 Direct (Scope 1) and Indirect (Scope 2) GHG Emissions
89 Data Points
Indicator Data Points Actions
Scope 3 GHG Emissions (Business Travel) 4
Total GHG Emissions Intensity (By Area) 13
Scope 3 GHG Emissions (Waste Generated in Operations) 8
Total GHG Emissions 13
Direct GHG Emissions (Scope 1) 13
Indirect Energy Emissions (Scope 2) 13
GHG Emissions from Purchased Electricity 12
Total Other Indirect Energy Emissions (Scope 3) 13
A1.3 Hazardous Waste
11 Data Points
Indicator Data Points Actions
Hazardous Waste Recycled 11
A1.4 Non-Hazardous Waste
22 Data Points
Indicator Data Points Actions
Non-Hazardous Waste Recycled 6
Paper Waste 8
Total Non-Hazardous Waste Intensity (By Area) 8

A2.1 Energy Consumption
50 Data Points
Indicator Data Points Actions
Energy Consumption Intensity (By Area) 11
Total Energy Consumption 11
Total Direct Energy Consumption 11
Total Indirect Energy Consumption 11
Purchased Electricity 6

B1.1 Amount and Distribution of Workforce
203 Data Points
Indicator Data Points Actions
Number of Total Employees 10
Number of Male Employees 10
Number of Female Employees 10
Percentage of Male Employees 10
Percentage of Female Employees 10
Number of Full-time Employees 10
Number of Part-time Employees 8
Percentage of Full-time Employees 8
Percentage of Part-time Employees 7
Number of Employees Aged Below 30 10
Number of Employees Aged 30-50 10
Number of Employees Aged Above 50 10
Percentage of Employees Aged Below 30 10
Percentage of Employees Aged 30-50 10
Percentage of Employees Aged Above 50 10
Number of Employees in Hong Kong 10
Number of Employees in Mainland China 10
Number of Employees in Hong Kong and Mainland China 10
Percentage of Employees in Hong Kong 10
Percentage of Employees in Mainland China 10
Percentage of Employees in Hong Kong and Mainland China 10
B1.2 Employee Turnover Rate
80 Data Points
Indicator Data Points Actions
Turnover Rate of Female Employees 10
Turnover Rate of Male Employees 10
Turnover Rate of Employees Aged Below 30 10
Turnover Rate of Employees Aged 30-50 10
Turnover Rate of Employees Aged Above 50 10
Turnover Rate of Employees in Hong Kong 10
Turnover Rate of Employees in Mainland China 10
Turnover Rate of Total Employees 10

B2.1 Number and Rate of Work-related Fatalities
18 Data Points
Indicator Data Points Actions
Number of Work-related Fatalities 9
Work-related Fatalities Rate 9
B2.2 Lost Days Due to Work Injury
9 Data Points
Indicator Data Points Actions
Lost Days Due to Work-related Injuries 9

B3.1 The Percentage of Employees Trained
3 Data Points
Indicator Data Points Actions
Percentage of Trained Female Employees 1
Percentage of Trained Senior Management 1
Percentage of Trained Middle Management 1
B3.2 Average Training Hours Completed per Employee
4 Data Points
Indicator Data Points Actions
Average Training Hours (Male) 1
Average Training Hours (Female) 1
Average Training Hours (Senior Management) 1
Average Training Hours (Middle Management) 1

B7.1 Confirmed Incidents of Corruption
2 Data Points
Indicator Data Points Actions
Number of Concluded Corruption Lawsuits 1
Number of Corruption Litigation 1