Small and medium-sized enterprises (SMEs) form an essential ingredient of a country’s economy as they are one of the main sources of employment and technological development. They play a very important role by significantly contributing to each country’s Gross Domestic Product (GDP) and its labor market. Therefore, new systems that can help SMEs become more efficient and productive are not only beneficial for SMEs but also for the economy as a whole. One of the strategies that can help SMEs become more efficient is the use of modern Information and Communication Technologies (ICT). However, the size and structure of SMEs make them face a big challenge — the limited access to enough resources. They cannot afford the in-house staff needed to plan, design, implement, and manage increasingly complex software and hardware, and networking kit in today’s tough economic times. It is becoming increasingly hard for SMEs to justify such investment and on-going expenses. Many organizations are seeking alternative solutions that can reduce the total costs of their ICT systems.

We have identified this vast market potential and developed an intelligent financial management information system based on cloud computing, which can help SMEs tackle the cost issue and streamline, simplify and automate their financial operations. 

As the world’s data are exploding in unprecedented volume, variety, and velocity, “big data” creates possibilities for near real-time analysis and has revolutionary potential for financial risk management. By employing big data, we have developed several breakthrough technologies and products which can significantly improve the predictive power of risk models as well as system response times and effectiveness. These technologies greatly boost the financial institutes’ ability to capture, access, and utilize big data, which become the key to risk management success in a world of increasing complexity and demand.

ERP provides the corporate with integrated data sets that can be shared across all functional levels and management hierarchies to increase business productivity and reduce life cycles of product development, service, and marketing. The emergence of Big Data requires the integration of ERP with Big Data analytics, especially when the external data, such as social media and web data, are the subject of Big Data analysis.

We have developed a Big Data analytics integration framework for ERP, which enables flexible integration of heterogeneous external data sources and Big Data analytics with ERP, based on a schema-on-read modeling approach and data virtualization paradigm. This approach overcomes the shortcoming of the standard schema-on-write approach, where the database and schema are predefined and created before the data entry, resulting in extended processing time.

We develop cloud-based computing methodology to provide users with the flexibility of leasing an ERP service through multiple vendors.

By enabling many cloud-based functionalities, our cloud-based ERP systems provide ERP services to businesses via a subscription model, and outperform existing on-premise ERP systems in many aspects including much lower ownership costs, significant time savings on deployment, automatic system upgrades, and much improved accessibility and security.