Advanced analytics needs to be built on cutting-edge technologies and actionable tools, models and algorithms. IDA is home to such experience by integrating breakthrough research with well proved tools in addressing critical analytical problems.

In this part, we summarize our major approaches and strengths and focused domains through our research and development.

In addition, we showcase several techniques, including predictive modeling, customer analytics, behavior analytics and risk technology.
Research and Development
Research: Motivated by real-world challenging problems, our researchers focus on inventing cutting-edge, next-generation data science, and big data analytics technology, algorithms and models for cracking challenges in complex data and behaviors.

Development: Aiming at lifting enterprise productivity, economy and competitive capability, we are specialized in synergizing and converting innovation to actionable domain-specific solutions, products and applications, in such areas and domains as banking, finance, insurance, public sector, education, telecom, and online and social business.
We focus on delivering actionable big data analytics solutions and best practices for areas including but not limited to:
  • Banking
  • Education
  • Financial market
  • Government
  • Heath care
  • Insurance
  • IT
  • Medical/hospital services
  • Online business and e-commerce
  • Retail business
  • Social media and networks
  • Transportation
Building on our years of deep research and widespread engagement practices with many international, multinational government and industrial organisations, the IDA invents and delivers cutting-edge descriptive, predictive and prescriptive analytics, data mining and machine learning technologies, solutions and services to make the most sense of your data.

Our design and solutions have been enabled by long-lasting integrative research, education/training and engagement across disciplines and domains, with the core team. Technologies and resultant solutions and services widely demonstrated and testified across medias, organisations, and countries.

In addition to classic focus such as on descriptive analytics, our successful case studies particularly demonstrate the significant improvement on effectiveness and efficiency made by our most experienced workers in addressing critical challenges such as predictive analytics, risk analytics, fraud detection, forecasting, community analysis, sentiment understanding, behaviour analytics, social analytics, and online analytics in evolving data with complex networking behaviors and relationships in a mixed, interconnected and/or changing environment.

Our customized courses and analytics clinic will assist you in diagnosing and removing the blocks and limitations in your data and solutions towards personalized practices.

We ensure that our technologies, solutions, knowledge and deliverables can be seamlessly taken over by your team, and shared within your business and technical units towards upgrading your team capability, knowledge and thinking during the partnership.
  • Anomaly/Fraud/Outlier detection
  • Behaviour analytics
  • Big data pre-processing and preparation
  • Cross-media and -source data analytics
  • Customer value and satisfaction modelling
  • Data mining and knowledge discovery
  • Debt and overpayment collection, recovery and prevention
  • Educational data mining & predictive modelling
  • Feature/factor analysis, selection, construction and mining
  • Financial data analytics
  • Image processing
  • Machine learning
  • Online business analytics
  • Pattern recognition and discovery
  • Predictive analysis and modelling
  • Recommendation
  • Risk scoring, analytics and management
  • Sentiment analysis
  • Social analytics
  • Statistics and statistical machine learning
  • Text mining and document analysis
  • Predictive Modeling
  • Customer Analytics
  • Behavior Analytics
  • Risk Technology
Concept: Predictive modeling is the most exciting aspect in the emerging and already highly sought after field of data analytics. It performs a learning process over the historical data set for a particular target to assemble a model which is enabled to forecast the future against the target. Our predictive models may be made up of a number of predictors, including variable factors that are likely to influence future behaviors or results. For example, given a click stream of an online customer and his/her demographic data, the model predicts whether the customer will churn out in the next six months. Another example, given the learning behaviour sequence of a student, a predictor calculates the probability that he/she may fail to pass the subject at the end of the semester. The resultant probability (risk score) obtained can be served as a predictor of academic failure.

IDA Technology: Our predictive models are embedded with the latest data mining, machine learning and statistics innovation to mine high-dimensional, heterogeneous and comprehensive relevant variables, with the delivery of discriminative predictors and indicators to best capture the trends or exceptions of data and behaviors. In government services such as taxation and social security, based on the payment behaviors and demographics, we can tell how long it may take debtor A to pay off the debt, while debtor B may take a different period of time. In banking business, by engaging data from social media like Twitter, call centres and banking information systems, we can predict who may likely move from a bank to another at what time for what reasons. In financial markets, by aligning data across capital markets, foreign exchange and petrol market, exceptional movements may be predicted to take place at what time in which market. In education, consolidating student engagements in class, library, online and campus, we can predict the academic performance dynamics of a student and recommend appropriate early intervention actions to convert low-performing students to the high-performing group.