The External Expert Review committee headed by Dr. C. Rangarajan has recommended that the focus of IDRBT research should be primarily applied in nature i.e., original investigation to acquire new knowledge towards a practical aim or objective that will serve the banking industry.

• Networks: In the domain of networks, a variety of aspects have been studied. Network traffic was analyzed to detect intrusion, a security architecture framework has been evolved for wireless local area networks in corporate offices, and security threats such as anti-phishing and identity theft have been explored. Role based access control mechanisms and authorization have been studied in the context of grid computing.
• Security: In the second wave of research, we have publications in the domain of Information Security. From introducing PKI to banking industry, to investigations on creating proxy signatures and efficient key pairs for RSA have been explored. Digital watermarking has also been investigated as a possible means for protecting copyright information from being misused by unauthorized duplication or software piracy. Biometrics on fingerprint, palm print and vein pattern recognition have also been researched.
• Software Engineering: In software engineering, software development cost estimation, software reliability prediction, software defect prediction, web-services classification are all important topics of research. IDRBT made contributions to each one of them by developing soft computing hybrid techniques.
• Soft Computing and Data Mining: In third wave, we have researched in the broad areas of soft computing (subsuming artificial intelligence) and data mining. These included the fields of fuzzy logic, neural networks, evolutionary computing, decision trees, support vector machines and rough sets.
  
  Primarily, most of this research has initially focused on developing general-purpose, novel architectures of soft computing, global optimization metaheurstics and their applications to bankruptcy prediction in banks, profitability modeling and ranking in banks, customer credit scoring, customer churn prediction, fraud detection in financial companies, asset liability management etc.
  
  For the illustration purposes, various datasets available in the public domain were utilized. In the process, faculty-level collaborations took place between IDRBT and Business School, University of Hong Kong. While a majority of them are data-driven in nature, a few knowledge-driven techniques were also developed. Most of this research has concentrated on proving the merits or efficiency of one technique or algorithm over the others. However, this research has evolved and matured so that the techniques and methods can now be practically used for the banking industry. A part of this research has been the backbone for the creation of the Customer Relationship Management Lab at IDRBT.

An Expert Committee constituted by Dr Rangarajan has mandated that the focus of IDRBT research should be primarily applied in nature i.e., original investigation to acquire new knowledge towards a practical aim or objective that will serve the banking industry. The Expert Committee also suggested four broad areas of research:

• Financial Networks and Applications
• Electronic Payments and Settlement Systems
• Security Technologies for the Financial Sector
• Financial Information Systems and Business Intelligence

Currently, two major research projects are underway in collaboration with IIT Kanpur (apart from research work carried out by doctoral scholars and post graduate students). The first project is to forecast customer demand for ATMs leading to optimal cash management using decision science methodologies. The second project is on application security and it aims to automatically detect vulnerabilities in software.