Market Size of Big Data Analytics In Banking Industry
Study Period | 2019 - 2029 |
Market Size (2024) | USD 8.58 Million |
Market Size (2029) | USD 24.28 Million |
CAGR (2024 - 2029) | 23.11 % |
Fastest Growing Market | Asia Pacific |
Largest Market | North America |
Major Players*Disclaimer: Major Players sorted in no particular order |
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Big Data Analytics in Banking Market Analysis
The Big Data Analytics In Banking Market size is estimated at USD 8.58 million in 2024, and is expected to reach USD 24.28 million by 2029, growing at a CAGR of 23.11% during the forecast period (2024-2029).
Based on the inputs obtained from numerous insights, such as investment patterns, shopping trends, investment motivation, and personal or financial background, big data analytics can help banks understand client behavior.
- The considerable increase in the volume of data generated and governmental requirements are the main forces behind adopting Big Data analytics in the banking sector. With the development of technology, consumers are using more and more devices to start transactions (such as smartphones), which impacts the volume of transactions. Given the current data growth rate, better data collection, organization, integration, and analysis are necessary.
- Government rules and considerable data gathering are affecting the banking industry. As technology develops, more consumers are using more devices to start transactions (such as smartphones), which boosts the volume of transactions. This motivates big data analytics, which gives data analysts a single location to see and quickly locate all data points. Thanks to this consolidated picture, team members can exchange insights that could enhance the banking industry.
- A Big Data Analytics solution offers the processing, persistence, and analytic capabilities necessary to unearth fresh business insights while enabling a company to store all its data in a flexible, affordable environment. An analytics tool for big data gathers and keeps track of structured and unstructured data and techniques for arranging enormous amounts of wildly different data from various sources.
- The majority of legacy systems are unable to handle the rising burden. The entire system's stability may be compromised if the necessary amounts of data are gathered, stored, and analyzed utilizing an obsolete infrastructure. Organizations must either improve their processing capacity or entirely redesign their systems to tackle the issue.
- Due to the rise in usage and adoption in banking sectors to analyze and research consumer data and implement efficient strategies, the COVID-19 pandemic has significantly impacted data analytics in the banking industry. Because of the rapid evolution of technology, data analytics in banking has seen tremendous growth.