Currently, the world is being driven digitally with technology and data being present everywhere. The Indian Brand Equity Foundation expects the Data Analytics industry to hit up to $119 billion by 2026. Data Analytics has become important in various businesses across sectors.
Data Analytics provides a major actionable insight into customer behavior and market behavior. Various Data Analytics Courses are high in demand, however, what matters is the skill acquired while pursuing the course.
The power of the banking sector in the 21st century is mostly controlled by Data Analytics. Banks are using Big Data, and Data Science to bring a change towards analytics and data to gain more competitive advantage. With the invention of Data Analysis, the secrets of capital flow have been unlocked, yet it helps to prevent major theft or disaster and understand consumer behavior.
The term data analytics was first used at large in 2011, by Google, Facebook, and Yahoo. Over the years, the use of Data Analytics has increased successfully among financial service firms, insurers, health organizations, etc.
Data analytics has enabled banks to raise the standards and quality of services they offer to their customers. As a result, the banking industry is investing heavily in big data and related technologies. Another important role of data analytics can be seen in the fact that banks and financial institutions generate and handle a large amount of data, and Data Analysts assist banks and financial services in efficiently storing data, analyzing it, and improving scalability.
Why Do Banks Need Data Analytics?
The relationship between customers and banks is often deceitful. The trust of the customers is built on the services and loyalty provided by the banks. However, the increasing sophistication of banking services and products has increased the demand for effective decision-making tools that enable better decisions to be made based on data insights.
The banking industry must use its data for analysis and better decision-making. Banks will be able to figure out how to increase their profits while also improving their business relationships and customer service.
Leverage of Data Analytics in the Banking Sector
The usage of Data Analytics has made the banking sector furthermore efficient and controlled. The advantages that data analytics bring to the banking sector are the following.
- Banks use Data Analytics to detect customer behavior based on their activities such as investments, shopping trends, or financial history. Banks can find ways to retain customers while also attracting new ones by providing personalized solutions.
- Through Data Analytics, banks can boost their performance and reduce their operating expenditure.
- Banks can identify the unsatisfactory credit score of their customers and can deny their loan sanctions.
- Banks have innumerable data, so managing huge amounts of data is a task that is easily handled by Data Analytics tools.
- Data Analytics can assist banks in obtaining the information they require to improve their services and meet the expectations of their customers. Based on the transactional data and the customer’s purchasing habits, banks can predict which products are suitable for their customers. This is required to stay ahead of the competition and to expand the customer base.
Growth and Trend Forcast of Data Analytics in the Banking Sector
The amount of data generated by banks is rapidly increasing, and this rapid growth necessitates improved acquisition, organization, integration, and analysis.
Data solutions enable a company to store its data in a cost-effective and flexible environment while also providing the processing, persistence, and analytic capabilities needed to uncover new business insights.
The digital disruptions have increased and with technological advances such as edge computing, the internet of things (IoT), and artificial intelligence, the BFSI industry has embraced cloud data deployment. Furthermore, COVID-19 accelerated cloud data deployment in the BFSI market due to increased demand for greater computing power among banks and the fintech sector.
Asia-Pacific Would Exhibit the Highest CAGR of 22.8% between 2022-2031
Asia-Pacific is considered to be the fastest-growing region in Data Analytics in Banking Sector. This signifies that the Asia Pacific region has actively contributed to the fact that they have adopted predictive analysis for increasing the revenue of the companies and their decision-making capabilities. The key players who operate global data analytics in the banking sectors are AWS, Adobe Inc., Google, IBM, Dell, LLC, Zoho Corporation, SAP, etc.
Data Analytics Skill-Set on Demand
According to IBEF reports, the Indian Data Analytics market will play an important role in driving the future of the fourth phase of industrialization. It will also aid in the creation of new job opportunities.
According to the study, the industry is expected to create over 11 million jobs by 2026. By the end of this year, investments in AI and machine learning will increase by 33.49%.
As per various industry reports, there has been a 30% increase in Data Analytics and Data Science jobs this year compared to last year. According to LinkedIn’s Job on the Rise 2022 report, ML Engineer and Data Science Specialist are the fastest growing segments and the most in-demand job roles in 2022.
The banking industry can finally say goodbye to its antiquated system of customer guesswork. Big data analytics has enabled the monitoring of customers’ financial health and needs, including small business clients.
Banks can now use big data analytics to detect fraud and assess risks, as well as personalize banking services and create AI-powered customer resources. As more people create and use data, the volume of data will only increase over time. As more industries adopt big data analytics tools, the amount of information will grow, but so will its profitability.
Some popular B-Schools offer PGDM courses in Data Analytics. These programs assist students in making data-driven decisions by providing valuable insights. They engage in holistic learning with a strong emphasis on management across all analytics disciplines. The learners will also have the opportunity to gain hands-on experience with a variety of tech-driven integrated tools and analytic platforms, which will supplement their theoretical knowledge.
