The banking sector has always been data-driven. Banks record millions of business transactions daily. The volume of data generated by banks is not just large but also real-time in nature. While digital banking is used by almost half of the world’s adult population, banks and other financial institutions have enough data at hand to rethink the way they operate. In today’s digital world, the banking sector is striving to adopt a full-fledged data-driven approach for growing their business and increasing customer satisfaction, which can only be made possible with Big Data analytics. Although data analytics has been an integral part of the Banking, Financial Services, and Insurance (BFSI) sector for quite some time, the arrival of big data analytics allowed them to obtain a comprehensive understanding of customers, products/ services, markets, industry regulations, competitors, advertising channels and more. According to a report by Mordor Intelligence, Big Data Analytics in the Banking market is expected to register a CAGR of 22.97%, during the period of 2021-2026. Here is the impact of big data analytics in the banking sector. 

Improves levels of customer insight

This is one of the biggest impacts of big data analytics in banking sector. With the digitization of financial products and services, customers are now increasingly interacting with financial institutions on digital platforms. By leveraging big data analytics, banks can dissect the data derived from digital channels like social media, banking app data, and other data to enhance their quality of products and services. Big data analytics can also help the banks to understand the customer behavior based on the inputs received from various insights which include investment patterns, shopping trends, motivation to invest, and personal or financial background. This helps banks to gain a deeper understanding of customer pain points, preferences, and needs. Thus, big data analytics not only helps improve the customer experience but also helps stay ahead in the competitive market.

Big data analytics for fraud detection and prevention

The banking sector has long been the victim of fraud. As much as the technologies and strategies that protect the banks from fraud have advanced, the techniques and methods of hacks, breaches, and frauds have also upgraded and evolved to become more sophisticated and complex. This is why it is crucial to detect and prevent fraud by identifying patterns that indicate potential fraud. Big data fraud detection is a cutting-edge way to use consumer trends to detect and prevent suspicious activity. For instance, customers with a deposit, checking, credit card, and personal loan accounts have usage patterns that can be combined and analyzed for patterns indicating frauds and thus helps predict fraudulent activities and minimize financial losses to a great extent. 

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Advanced market trading analysis

One of the biggest drivers of the adoption of big data in the banking sector is the rapidly increasing demand for the speedy execution of market trading. With the advent of big data analytics, financial institutions can gain the speed and accuracy that they have been looking for. Moreover, with the improvement in big data analytics, banks can leverage sophisticated algorithms to trade financial markets rapidly. The data gathered from different markets can be fed into advanced big data tools to produce rich, hybrid data sets that can offer a real-time, 360-degree view of the market scenario. Thus, banks can analyze the market trends and can form decisions that align with their business goals. 

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Risk management

Managing risks, especially operational risks, fraud risk, and credit risk has been a challenge for banks ever since the beginning. This is where big data comes in. Big data analytics finds its application in various key areas when it comes to risk management. Advanced big data analytics tools and techniques can exponentially boost the predictive power of risk models, enhance the system response time and offer more extensive risk coverage. Big data analytics can also be very helpful for banks to comply with legal and regulatory requirements in the integrity risk and credit risk domains. Thus, the impact of big data analytics in the banking sector is huge, especially in terms of risk management. 

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The impact of big data analytics in banking sector has been revolutionary. It has not just transformed the landscape of banking but also the entire financial industry. The measure of big data analytics in the banking sector is quickly expanding and is giving numerous opportunities for banks to improve their business and deliver improved services at marginalized costs. Thus, the impact of big data in the banking sector has been huge. At Intone, we provide innovative expertise and capabilities needed to deliver the future of banking today. Whether we’re helping to transform and modernize core banking operations, enable a mobile banking experience to become a social one, create world-class payment and credit processes, or provide data monitoring, analytics, and quality assessment and compliance and assurance reporting, our banking consulting services empower our clients with data-driven insights and the right tools to excel in today’s digital landscape.

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