International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 03 | Mar 2025
p-ISSN: 2395-0072
www.irjet.net
Exploring the Effectiveness of Data Analytics in Financial Service Sector Ananya Srivastava 1, Dr. Rajendra Kumar 2 1B.Com(Hons.) student, Amity Business School, Amity University, Lucknow 2Assistant Professor, Amity Business School, Amity University, Lucknow
---------------------------------------------------------------------***--------------------------------------------------------------------1.1 Importance of Data Analytics
Abstract - Data analytics is a widely used tool in today’s
time. Data analytics is a great tool of decision making since it facilitates in extracting, cleaning, transforming, data collection and modelling, ultimately providing valuable information. The use of data analytics by various companies has been growing tremendously over the decade in many financial fields. This paper aims to study on the topic data analytics and to understand its usage in financial service sector. It focuses on how data analytics is a growing field and its benefits in streamlining business operations. Focusing on how several top financial services companies streamline their business operations efficiently using data analytics.
1.Predict future trends- Data analytics helps in analyzing years of raw data and transform it to provide valuable insights. Data analytics transforms historical data and helps in responding to market trends. 2.Measure Performance-Data analytics is a great technique to measure the performance of the organization by tracking KPI’s and monitoring the efficiency. 3.Improve Security-Data analytics helps in monitoring risks associated with the crucial data and helps organization in alarming them.
Key Words: Data Analytics, Finance, Financial Service Sector, Data Visualization, Data Extraction, Transforming, Data Cleaning, Data Analysis and Interpretation, Key Performance Indicators (KPIs)
4. Personalize Customer Experience- With the help of data insights provided by data analytics software, businesses can provide their customers with personalized products.
1.INTRODUCTION
5.Provide Risk Management-Data analytics help in identifying risks and mitigating fraud.
In the recent years, use of data analytics technology has increased tremendously. Data analytics not only helps in transforming raw data but also draw insightful conclusions. Data analytics helps in analysing and examining the given information to provide results that are helpful in decision making. It helps businesses maximize its profit, perform more efficiently, make more strategically-guided decisions and optimize its performance. Data analytics draw conclusions into valuable insights and examines datasets. It involves studying the data to understand patterns or trends as well as organizing and cleaning. Data analytics depend upon many software tools like data mining programs, data visualization, spreadsheets, open-source languages and reporting tools. Data analytics is a great tool of decision making since it facilitates in extracting, cleaning, transforming, data collection and modelling, ultimately providing valuable information.
1.2 Process of Data Analytics 1. Data Collection - The very first step of data analytics is the collection of raw data for examining. Every insight to raw data can be made only when there is raw data available. If needed, the analysts use different sources of data or combined data for performing data mining and forecasting activities. 2. Data Cleansing - The next step in data analytics is to clean and organize the data available. When data is clean, it becomes easier to navigate things across data sets. The data may have several errors, blanks, and unnecessary spaces, which can create problems while transforming data and gaining insight from it. 3. Data Analysis and Interpretation - Software and other tools help create analytical models. These models interpret and properly visualize the data in order to make data driven decision-making. The tools are R, SQL, Python, and Excel.
Nowadays, integrating data analytics can be seen in every filed whether technical or non-technical. It has always helped organisations to find trends over the years from the given information. This also helps in reduction of human error while working with the data and helps streamline business operations by reducing costs, improving productivity and identifying inefficiencies. Thus, data analytics helps in efficient and smooth operations of a company while also growing performance quality.
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4. Data Visualization - It refers to the process of preparing visual representation of data by making charts and graphs, plots, bar graphs, pie charts, etc. which further helps to analyse the trends and patterns to get valuable insights into the data. Data analysts find useful data from the raw data by comparing the datasets and analysing it.
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