Introduction
The Banking and Financial Services Sector has progressed, making digitisation synonymous with customer satisfaction. It brings more auto-regulated services to the customers. As per statistics, data analytics in India continues to grow steadily. It is expected to reach US$ 118.7 billion, creating over 11 million jobs by 2026!
Data Analytics in India has seen robust growth in the past few years. Pushing digitisation and establishing data-driven decision-making in the banking and financial services sector. This explosive growth is due to the rise of internet consumers in the past decade. This translates into a booming opportunity for data analytics.
Today, data analytics is more focused on productivity rather than cost-cutting. It facilitates by enhancing customer service through data-backed decisions, innovating steadfastly towards maintaining an omnichannel presence. Furthermore, it has transformed the banking and financial services industry, improving operational efficiency and profitability.
Therefore, in this article, we will explore the key applications of data analytics in the banking and financial industry and closely examine how data analytics has refined the BFSI industry.
Benefits of Data Analytics in Banking and Financial Services
Intense competition in the tech-advanced banking and financial services sector has led almost every organisation to switch to digital platforms, making work more efficient. Data analysis has reached unprecedented heights throughout this tech race, making almost every process cost-effective and efficient. It offers a multitude of benefits to the BFSI industry and has improved the productivity of day-to-day operations.
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Risk Mitigation:
Risk assessment is one of the main hindrances for the banking and financial services sector. With new technologies evolving now and then, the risk of fraudulent activities increases simultaneously. Data analytics can reform risk management practices and enable better risk mitigation by conducting predictive analysis to identify potential threats.
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Operational Efficiency:
Banking and Financial Services have modified their workflow by improving operational efficiency and automating regular tasks. Optimisation of repeated functions with the help of data analytics has replaced the traditional paperwork hassle and translated into cost reduction and minimisation of manual errors, leading to greater operational efficiency.
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Customer Insights:
Data Analytics help closely understand customer choices and preferences and create more personalised products as per their choice to boost customer lifetime value. Leveraging advanced data analytics practices lets financial organisations know more about consumer buying patterns. This is essential for the banking and financial services sector to improve their profit margins.
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Enhanced Customer Experience:
Another factor that can improve revenue is enhanced customer experience. Data analytics enables the BFSI industry to offer customers the right product at the right time and make necessary structuring to provide customers with a more personalised experience. Minutely assessing every detail of the consumer is the key to generating more revenue in the banking and financial services sector.
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Key Data Analytics Applications in Banking and Financial Services
Adopting a more data-driven approach has led the BFSI industry to meet changing customer needs. The abundant data the banking and financial services receive is fragmented and structured. Analysing this data can generate more focused business insights to improve customer satisfaction and identify avenues for generating more revenue.
Below, we will look at the key data analytics applications in banking and financial services:
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Data-driven decision-making:
Data Analytics has improved work efficiency and productivity and also catered to BFSI institutions making more strategic and data-driven decisions. It enables them to make more informed decisions and provide quicker insights for prompt actions and changes in market patterns.
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Personalised Marketing:
Understanding the customer before targeting any marketing communication is necessary. Customers today get flooded with various product offerings all at the same time. Hence, personalising marketing communications helps build trust and showcase the organisation’s dedication towards customer needs.
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Market Analysis and Risk Management:
Data Analytics insights help understand the market trends and customer sentiment to make more strategic decisions. Additionally, implementing dynamic risk models with advanced data analytics makes significant changes in the risk management system, allowing banking and financial services firms to prevent fraudulent activities.
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Credit Monitoring:
Credit monitoring uses data analysis techniques and tools to figuratively track and assess the customer’s creditworthiness and potential risk factors. Data analytics are crucial in monitoring the individual’s credit-related data, credit scores, financial history and more detailed insights about the customer’s financial health.
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Conclusion
A career in data analytics can be an ideal gateway to more rewarding opportunities in the long run. As more and more industries adopt a more data-driven approach to cut operational costs. Making day-to-day functions more systemised, there is a growing demand for dynamic data analysts in the banking and financial services sector.
Whether you are inclined towards banking, finance or fintech careers, the changing patterns in the industry are amongst the core essentials. Those aspiring to carve a thriving finance career must be well-informed about the tech trends in the industry.
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Frequently Asked Questions
Data analytics plays a fundamental role in the BFSI industry by enabling organisations to analyse and make necessary reforms as per the insights gathered from complex datasets, improve risk management, detect fraudulent activities and enhance customer experience and operational efficiency.
Data analytics is vital in the BFSI industry as it links to various operations that help in increased efficiency. It facilitates financial and banking institutions to identify risk factors, mitigate them, optimise operational efficiency and enhance customer satisfaction by personalising services.
A career in data analytics requires professionals to be adept in programming languages like SQL, Python, and MATLAB, along with due knowledge and proficiency in finance and risk management. Skills like problem-solving, business intelligence and communication are also equally essential.
Owing to technological advancements in recent times, careers in data analytics have strong growth prospects. Professionals can progress into advanced roles like senior data analysts, data scientists and other managerial positions. As the BFSI industry relies more on data-driven decisions, the career prospects for data analysts look bright and offer excellent growth potential.
With the BFSI Industry taking active strides towards data-driven decision-making, the future for data analytics is robust and directed towards an advanced career trajectory. It promises ample opportunities for growth and development in the long run.
