Abstract: Uncertainty and ambiguity are omnipresent in the present day’s business scenario. Living only in today in a limited period of financial boom, hoping for the maintenance of status-quo and enjoying with the optimism that tomorrow (or day-after) will be automatically addressed, is nothing but a recipe of disaster. In the present knowledge economy, it is imperative for any organization to store its knowledge-base with the information about the past and the present and to harness the same towards anticipation of the future, to the extent possible. In other words, knowledge-based systems have emerged as the essential tools of most big and even medium-sized business. Knowledge Management coupled with Artificial Intelligence (AI) and Artificial Neural Networks (ANN) have become the critical components of the so called business intelligence.

All organizations operate in an atmosphere of uncertainty but decisions must be made that aid towards proper planning for the future of the organization. Hence the need of forecasting which reduces the range of uncertainty within which the management has to work and make decisions. Predictions by economists is one of the options but is associated with its own contradictions. Hence it is imperative for us to experiment with technological forecasting. Amongst others, ANN has emerged as a useful tool for business forecasting – both at micro & macro level.

Another relevant area where the potential of ANN, if properly harnessed, can be of immense help to the mankind is Fraud Detection e.g. Credit Card Fraud Detection. For the high data traffic of 400,000 transactions per day, a reduction of 2.5% of fraud can result in saving of one million dollar per year. However, the anticipated diagnostic accuracy of “not less than 99.9% “ is a major challenge for using ANN in this field. With the rapid change of experts’ knowledge in the face of new and innovative methodologies, as adopted by the fraudsters, traditional expert system based approach is fast becoming suspect towards accurate detection of perpetrators. Hence the ANN based methods.

Bio Sketch: Prof. Suash Deb did his Bachelor of Engineering (B.E.) in Mechanical Engineering from Jadavpur University, Calcutta, India, Master of Technology (M.Tech.) in Computer Science from the University of Calcutta, UN Fellow in Computer Science of Stanford University, USA He was also an Asian Expert of the Advanced Research Project Agency (ARPA), Dept. of Defense, Federal Govt. of USA. He has both industrial & academic experience with more emphasis on the later. Currently he is a Professor of the Dept. of Computer Science & Engineering, C. V. Raman College of Engineering, Orissa, India. He specializes in Soft Computing, Artificial Intelligence, Bioinformatics & related fields.

A Senior Member of the IEEE (USA), Prof. Deb has been the recipient of Bharat Excellence Award & International Albert Einstein Award for Scientific Excellence. He is currently on the editorial board of numerous reputed International Journals. He is the Editor-in-Chief of International Journal of Soft Computing & Bioinformatics, Regional (India & Subcontinent) Editor of Neural Computing & Applications as well as the Advisory Board Members of Intl. Jl. of Bio-Inspired Computation, Intl. Journal of Intelligent Computing in Medical Sciences & Image Processing etc. Previously he also served the IEEE Robotics & Automation as its Regional editor & also the journal Robotics & Computer Integrated Manufacturing as an Associate Editor. He has traveled widely across the globe and delivered Plenary Talk/ Tutorial Address etc. at various National/International Conferences. He is the General Chair of 2009 World Congress on Nature & Biologically Inspired Computing & International Symposium on Innovations in Natural Computing, to be held in Coimbatore & Cochin respectively. He is attached with numerous International conferences as Member-Advisory Board, Program Committee etc & listed on a number of Who's Whos.