Abstract:
This report is aimed at discussing how my internship experience was in the Treasury Division of Prime Bank PLC. The internship program was arranged in such a way that it would help me get hands-on experience in the banking sector with a special emphasis on the activities of a treasury department of a bank. The major internship goals were to have hands-on experience of financial management, liquidity management, risk management and operations in the treasury. During my internship, I had to deal with a massive scope of work that enabled me to see the fundamental operations of a bank. Such activities involved helping in the observation of the cash flow of the bank, investigation of its liquidity status and making decisions on investment management. Another opportunity that I got was to analyze foreign exchange transactions, project short term financial requirements and prepare market trend reports. These reports played the crucial role of knowing the impacts of the monetary authority and market trends in the decision making of the treasury in the bank. Also, my internship has helped me to work closely with the professionals in the treasury division, which has exposed me to opportunities to observe and learn about their decisions based on the risk management, asset-liability management, balance sheet management and dealing with interest rate risks. I also learned the techniques and instruments of hedging and optimization of financial performance under different conditions of the market. In this report, I have analyzed the economic trends of Prime bank PLC using the ARIMA (p, d, q) model. The following model was used to predict the important economic variables, including export, import and remittance trends, which are critical to the bank treasury operations. The purpose of the analysis was to give insights in terms of how these trends will affect the financial strategy used by the bank. The experience has improved my knowledge of time series forecasting as well as quantitative analysis and proved how and why statistical models are practically used in making decisions in the banking field and risk management.
