Balaji Adusupalli

This paper will take a critical view of issues of investment management, secure transactions, and risk in the digital era. The Financial Services Industry is a product of the Information Technology (IT) revolution. The application of IT have had profound implications for how products are produced, how they’re exchanged, who develops the new products, and how the old products are replaced. The current wave of technological evolution is changing the way in which financial services are produced and delivered. Developments in the World Wide Web sector have accounted for an expansion and strengthening of the online transaction sector, with a growing number of fully automated banking platforms. This transition has been accompanied by considerable public expenditures on new security technologies to protect it. Of particular interest in this context is the provision of data privacy and the prevention of fraud through secure transactions in order to bolster consumer and institutional confidence in the transacting financial markets. This paper will consider investment management, secure transactions, and risk assessment for online activities in the financial sector. Technological advancements in the field of IT have allowed the financial industry to take advantage of networked computing, to automate trading decisions, and to trade very quickly and in large volumes. The financial industry can now use sophisticated high performance computer driven trading platforms. These developments have had a significant impact on the way banks, fund managers, and individuals trade currency and equity. To this day most financial orders are negotiated through people, often using voice linked dealing systems. This experience has decreased considerably due to the rapid growth of automated computer systems capable of almost instantaneous order placement with the corresponding financial institutions. With appropriate technology and clear development the banks and exchanges alike can now record at high frequency virtually all transactions that occur in the financial market. Furthermore, several data vendors are now selling high frequency data in relatively cheap and easy to work formats, essentially lowering the barriers to entry in this field. Some people consider these characteristics to be sufficient to classify financial data (specifically price data) as “Big Data”.

This research study develops for the first time concepts that bring to the forefront an order of magnitude leap in the way financial risk is managed and mitigated by corporations, and in their interactions with their financial services suppliers. At the core of the research work are the development of a specific type of enterprise robotics theories and solution methodologies; end-to-end systems for secure access, navigation, and protection for financial applications using federated identity and attribute management; and the introduction of predictive intelligence using a few dominant principles, modeling, and estimation methods, risk equations, and estimation feedback protocols. In addition to the foundation studies for each of the three major components, we integrate the three into an enterprise financial risk solution and demonstrate through a set of complex activity models and problem derivative-specific applications the nature and degree of financial engineering, financial and data communications, modeling and corporate customer service integration analytics, information and business intelligence, managerial zones, and innovation theories involved.