Key Challenges of Big Data in the Finance Sector


Finance companies and banks today think of data overload, which is beneficial to gain actionable insights and competitive advantage in today’s digital age. With the inception of big data and business intelligence (BI), unorganized, ineffective data now make sense to the finance sector.

Thanks to big data technologies! Therefore, it is no surprise that why big and small financial service companies are adopting big data analytics to provide better customer service and achieve business growth. 

Today, banks and online lenders can make the best out of customer data to figure out buyers’ likes and dislikes, shopping behaviour, demographic factors, and related aspects to customize their financial products or services and enhance the overall customer experience.

That does not mean big data does not have any challenges. The issues are information overload and sets of unstructured data to process.

According to an article published on, in this age when big data has taken the world by storm, banks face new challenges. Verifying, securing, and managing loads of data is essential for financial companies and banks because they are the centre stage of all business activities and have access to all types of customer data. So let us talk about some of the challenges of big data implementation in the finance sector.

Importance of data synchronization 

In this age when all businesses are going digital, data sets are huge, diverse, and getting bigger daily. The huge challenge is the inclusion of mission-critical bank or finance company data into an investigative and systematic platform. If such problems are overlooked, it leads to performance issues of financial companies, thus resulting in incorrect data interpretation, information, and actionable insights.  

Data storage and quality

The finance sector is growing fast. With spectacular development and expansion of big data, banks, finance companies, online lenders, and Fintechfirmsproduceloads of data every day. The challenge is in storing volumes of data without compromising on integrity.

There are numerous data storage choices like data warehouses. It helps to amass and collect loads of structured and unstructured information in its original form.

The problem crops up when these data warehouses try to combine unstructured and inconsistent data from different sources. The outcome is dealing with multiple errors or mistakes. 

Disjointedinfo, mislaid data, duplication of information, and discrepancy in logic all result in poor data quality.

When it comes to the banking and finance sector, inconsistency in customer data is a grave issue leading to loss of customer trust and business.

For instance, if you are planning to take out a loan from companies like, you need to ensure that they comply with data security and compliance. 

Privacy and protection of customer data

When banks use big data analytics, it offers many prospects and opportunities in abundance. However, the finance industry is rife with numerous challenges concerning big data, which is data privacy and protection.

The online lenders and Fintechs use tools for storing and assessing information, especially customers’ personal and financial data to utilize them and gain actionable insights from various sources.

Now, these sources should be secure and financial companies must ensure 100 per cent security of confidential customer data such as names, address, contact numbers, bank account details, and debit or credit card information. 

If proper data security measures are not in place, it often leads to data threats and breaches, thus making sensitive customer data as well as business data vulnerable.

With a multitude of information generated, privacy issues, data threats, and information security issues arise with the data that Fintechs handle. 

Did you know that in a few automated sectors such as in the telecom sector, stolen data is frequently misused to make automated spam calls, a real nuisance these days! The finance sector is also embarrassed when bank details or credit card info is stolen to withdraw funds illegally. 

Big data is growing bigger every day

With so numerous types of data and loads of information, it is no wonder why finance companies struggle hard to deal with the information burden. The problem lies in segregating the useful data from redundant information. 

Though the share of useful data is increasing daily, there is much irrelevant information that banks and financial companies must filter out to improve performance, speed, and efficiency.

It implies that the finance industry should now gear up and strengthen their tactics for evaluating voluminous data, and, if likely, look for some unique application for the information that is not relevant and lead to confusion. 

In spite of the cited challenges in this article, the benefits of big data in finance and banking outweigh the problems.

The actionable insights it gives to the finance companies and customers, the resources it helps in freeing up, and the enormous cost-saving it does, big data is that catalyst that helps finance companies to grow and offer the best customer experience today.

You need to use big data to its full benefit for the best results. 

More data means more risks 

More information means more risks. The finance sector must ensure that the volume of data they are dealing with should remain secure. They cannot compromise with customers’ financial information at any cost.

Did you know that only 38 per cent of companies have the means to cope with data breaches and pilferage of customer data, as per the findings of ISACA International? That is the reason why cybersecurity is one of the hot topics of discussion in the financial sector. 

That is the reason why data security compliance is getting rigorous daily, which is good for customers. The use of GDPR has imposed a set of limitations on not only banking and finance but also other businesses as well, all over the globe. It is meant for those organizations that collate and use consumer data. 



The banks and finance companies need to overcome these challenges for smooth and seamless business operations. It is imperative for the safety of customer data. The online lenders and Fintechs are dealing will loads of consumer info, both personal and financial and therefore, ensuring data security is their top priority.