I am Ankur Kimtani. I have worked as an Institutional Investment Consultant in the BFSl Sector for about 7 years. Working in the Investment & Portfolio Management Profile, numbers and statistical data have always surrounded me.
It was my passion to understand this organized and unorganized data of the client’s Investment needs, their Investment pattern, and the kind of Portfolio Structuring required to fulfill their investment goals. When I started my career in 2015, we mostly used to create portfolios with the help of Advanced Excel and put that data in the form of PowerPoint presentations. But from the last 2 -3 years, I have noticed how big corporations have adopted Data Science to understand client needs and started presenting research reports using Data Science techniques. This made our (Investment consultants) life very easy to give a clear picture to our clients about their portfolio management.
Data science helped me a lot in providing support and advice to the team. The main problem faced by almost everyone in this field is investment decisions. Still, using visualization techniques, it became easier for me to create dashboards to improve the investment process.
Removing data redundancy and creating dashboards to represent big investment data helped me to get a clear picture of the statistics and, in turn, helped me make profitable investment decisions for the organization. Now, the efficiency and the speed of the whole process have been increased by two folds, and we’re expecting huge growth in the coming months. Recently we made a Portfolio Analysis of a client where we used Exploratory Data Analysis using Python to understand insights factors based on his last 3 years’ investment data which was available with us. The major factors which we focused on by doing Exploratory Data Analysis were:
- Risk Profiling of the client on the basis of the Investment segment he had chosen in the last 3 years.
- Understood the common investment goals for him by using his Profiling like his age, marital status, number of dependents, salary range & expenditures.
- Presented the future portfolio segregation in terms of Debt Equity Ratio analysis.
- Prepared a Business Inside report for our Sales team to give the Portfolio Management presentation to the client.
Outcome of the report:
By using Data Science, we made a deep analysis of client’s past Investments. On the basis of that and considering the factors above, we recommended a portfolio rebalancing to the client which helped us on board the client to our Advisory Services in just 1 week and the deal was profitable.
This shows the ideal portfolio structure for the client as per the profiling, which we analyzed on the basis of their past information for the last 3 yrs. After analyzing the given data, we concluded that option Debt Instruments are beneficial for the client’s portfolio rather than going for Bank FDs. We worked on a margin of 2% per deal. In terms of rupees, the profit made was 6 lacs.
