Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconBig Databreadcumb forward arrow iconTop Big Data Applications in Finance: How it is Revolutionizing The Finance Industry?

Top Big Data Applications in Finance: How it is Revolutionizing The Finance Industry?

Last updated:
30th Apr, 2020
Views
Read Time
5 Mins
share image icon
In this article
Chevron in toc
View All
Top Big Data Applications in Finance: How it is Revolutionizing The Finance Industry?

Introduction 

Big Data is quite a buzzword in modern times and influencing not only the IT sector but other key industries as well. These include big data in finance, big data in government, banking, healthcare, education, agriculture, telecom and the list goes on. The International Data Corporation’s Worldwide Semiannual Big Data and Analytics Spending Guide anticipates that the worldwide investment on big data analytics will grow to more than $203 billion in 2020 compared to $130.1 billion in 2016

What is Big Data Analytics? 

Big data is a collection of large and diverse data sets consisting of structured, unstructured, as well as semi-structured data from various sources. Traditional data processing and management tools are inadequate for handling this vast repertoire of data and, thus, require advanced tools. Therefore, big data analytics is the use of advanced tools to analyze and process large data volumes for building predictive models and guiding strategic decision making.

Big data is characterized by complexity, high volume, wide variety and high velocity. Large scale big data is generated in real-time from different sources like social media, web, devices, sensors, log files and transactional applications. Advanced analytics techniques such as data mining, statistics, machine learning, predictive and text analytics are used by researchers, analysts and businesses to tap the potential of previously inaccessible information for better decision making.

Know more: Critical Big Data Skills

Ads of upGrad blog

Explore Our Software Development Free Courses

Critical Use Cases of Big Data Analytics 

  • Healthcare – The healthcare industry has to deal with vast volumes of data. Big data analytics has made it possible for medical practitioners to efficiently harness the data, be it developing personalized medicines or detecting unusual disease patterns.
  • Agriculture – Farm data collection and processing have been made possible with the use of sensors and automatic machines, which in turn has contributed to better farm management practices, increased crop yield and protection against environmental risks.
  • Education – Be it developing academic skills or evaluating teacher and student performance, big data analytics has transformed the education sector in more ways than one.
  • Entertainment and media – Big data has enabled the entertainment industry to optimize content, suggestions, ads, and broadcast timing to attract maximum viewer attention. 
  • Telecom – Big data has enabled the telecom industry to deliver hassle-free connectivity to users. 

Also Read: Why to Become a Big Data Developer?

Explore our Popular Software Engineering Courses

Big Data Analytics in Finance 

With the evolution of technological innovations, big data has emerged as an integral part of the banking and financial sector, and as such, big data in finance is becoming an essential aspect of human activity. Financial services such as digital banking, asset management, and wealth management platforms, online peer-to-peer lending, SME finance, crowd-funding platforms, mobile payment platforms, and cryptocurrency create vast volumes of data that have to be managed efficiently and carefully with no damage to information.

Since the functioning of any financial organization relies on data and its protection, big data analytics has brought the much-needed fluidity and transparency in the finance industry. Be it risk analysis, fraud detection, customer satisfaction, or algorithmic trading, big data has empowered the financial system to focus more on improved service delivery rather than worrying about security issues.


upGrad’s Exclusive Software Development Webinar for you –

SAAS Business – What is So Different?

 

Top Applications of Big Data Analytics in Finance 

  • Fraud detection – While the rapidly growing digital world has proved quite beneficial, it has its share of frauds and scams. The biggest challenge faced by the banking sector today is the increasing number of cyberattacks that have rendered sensitive customer information vulnerable. But thanks to big data analytics and machine learning algorithms, unusual user activities and spending patterns have enabled financial organizations to detect frauds and scams on time.
  • Risk Management – To prevent significant revenue losses, the banking organizations must establish a robust risk management system, and this is where another application of big data in finance emerges. Real-time risk detection and protecting customers from frauds has been made possible with big data analytics.
  • Customer relationship – Maintaining satisfactory customer relations is the biggest challenge faced by the banking sector. From collecting and analysing customer data to providing beneficial offers and ensuring the safety of transactions, big data analytics has transformed the way banking organizations interact with customers.

In-Demand Software Development Skills

How has big data analytics influenced the financial sector? 

In a nutshell, the impact of big data and analytics on the financial sector include the following:

  • The information furnished by big data influences crucial success and production factors in the financial services.
  • Financial analysts can make better and more informed investment decisions.
  • Financial industries use data-based predictive models to monitor spending patterns.
  • Big data analytics has increased our understanding of financial markets.
  • Tax reform, trade, investment, risk analysis, automation, fraud detection, and management have been revamped with the availability of useful data sets.
  • The use of big data analytics in the finance industry has helped in overcoming various challenges and provided valuable insights on how to improve the banking experience while meeting the needs of customers.
  • Lastly, big data has created transparency and has significantly impacted economic analysis and modeling. 

Read our Popular Articles related to Software Development

Conclusion

Ads of upGrad blog

The availability of vast amounts of data has opened endless opportunities for businesses and industries to improve their services and increase profits. The banking sector has benefited significantly, and needless to say, big data in finance has emerged as the most promising field where big data analytics has found several applications.

From detecting frauds to improving customer relations, the financial sector is leaving no stone unturned to tap the potential of big data. Big data analytics has revolutionized the online banking industry and continues to impact the most crucial aspects of banking and finance across the globe.

If you are interested to know more about Big Data, check out our PG Diploma in Software Development Specialization in Big Data program which is designed for working professionals and provides 7+ case studies & projects, covers 14 programming languages & tools, practical hands-on workshops, more than 400 hours of rigorous learning & job placement assistance with top firms.

Learn Software Development Courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs or Masters Programs to fast-track your career.

Profile

Utkarsh Singh

Blog Author
Get Free Consultation

Selectcaret down icon
Select Area of interestcaret down icon
Select Work Experiencecaret down icon
By clicking 'Submit' you Agree to  
UpGrad's Terms & Conditions

Our Popular Big Data Course

Frequently Asked Questions (FAQs)

1What is the use of Big Data in finance?

Every sector has a vast amount of data in structured and unstructured forms, and so does Big Data in finance. These diverse and complex sets of data contribute immensely to dealing with business struggles. Moreover, they also help provide solutions to companies to tackle their financial challenges worldwide. Financial sectors are in their hybrid mode where they want to leverage the financial services to the maximum. This will incur transformation in their industry, culture, and process. The business operations are undergoing transitions due to the spike in increasing technology and growth in data generation. In such cases, financial sectors are the most data-intensive sectors. As promising as they look, with the help of Big Data, finance is bound to bring wealthy potential in the future.

2What are the big data challenges in finance?

With the increasing volume of structured and unstructured data sets, there is a constant need to manage it. Since the volume and velocity of data also rise due to this, relying on effective solutions and technologies is the way to go. However, there are specific challenges. Data security is the first challenge primarily because of hackers. To resolve issues in the financial industry, data governance measures need to be implemented. Using a Big Data management tool, risks such as these can be mitigated. It ensures data is secure and protected. Plus, it detects any fraud or suspicious activity.

3How to begin with big data in finance?

Financial organizations must function in a way to withhold data transformation effectively. First of all, create a data strategy keeping a business goal in mind to g. Companies should know the path their data is traversing through instead of focusing on mere fixes. Secondly, choose the appropriate platform that is scalable and flexible. For the finance industry, choosing a security specialist platform is mandatory. Finally, solve one problem at a time. Big Data opens the door to possibilities and helps solve challenging problems at a time.

Explore Free Courses

Suggested Blogs

13 Best Big Data Project Ideas & Topics for Beginners [2024]
101370
Big Data Project Ideas Big Data is an exciting subject. It helps you find patterns and results you wouldn’t have noticed otherwise. This skill
Read More

by upGrad

29 May 2024

Characteristics of Big Data: Types & 5V’s
6802
Introduction The world around is changing rapidly, we live a data-driven age now. Data is everywhere, from your social media comments, posts, and lik
Read More

by Rohit Sharma

04 May 2024

Top 10 Hadoop Commands [With Usages]
12257
In this era, with huge chunks of data, it becomes essential to deal with them. The data springing from organizations with growing customers is way lar
Read More

by Rohit Sharma

12 Apr 2024

50 Must Know Big Data Interview Questions and Answers 2024: For Freshers & Experienced
7884
Introduction The demand for potential candidates is increasing rapidly in the big data technologies field. There are plenty of opportunities in this
Read More

by Mohit Soni

What is Big Data – Characteristics, Types, Benefits & Examples
186666
Lately the term ‘Big Data’ has been under the limelight, but not many people know what is big data. Businesses, governmental institutions, HCPs (Healt
Read More

by Abhinav Rai

18 Feb 2024

Cassandra vs MongoDB: Difference Between Cassandra & MongoDB [2023]
5509
Introduction Cassandra and MongoDB are among the most famous NoSQL databases used by large to small enterprises and can be relied upon for scalabilit
Read More

by Rohit Sharma

31 Jan 2024

Be A Big Data Analyst – Skills, Salary & Job Description
899868
In an era dominated by Big Data, one cannot imagine that the skill set and expertise of traditional Data Analysts are enough to handle the complexitie
Read More

by upGrad

16 Dec 2023

12 Exciting Hadoop Project Ideas & Topics For Beginners [2024]
21210
Hadoop Project Ideas & Topics Today, big data technologies power diverse sectors, from banking and finance, IT and telecommunication, to manufact
Read More

by Rohit Sharma

29 Nov 2023

Top 10 Exciting Data Engineering Projects & Ideas For Beginners [2024]
40520
Data engineering is an exciting and rapidly growing field that focuses on building, maintaining, and improving the systems that collect, store, proces
Read More

by Rohit Sharma

21 Sep 2023

Schedule 1:1 free counsellingTalk to Career Expert
icon
footer sticky close icon