How Fintech Big Data Plays a Valuable Role in Financial Evolution

By Timothy Partasevitch, Chief Growth Officer at Smart IT.

The emergence of big data in the late 2000s opened a lot of new ways of storing, processing, and managing information. This provided an opportunity to get more value from the data flowing into companies’ systems. Soon big data in Fintech became not only an irreplaceable tool but also one of the main drivers of financial industry evolution. Learn about the ways in which big data is making business strategies and decisions more precise.

What is big data exactly helping with

Big data is often billed as one of the most significant and promising financial technologies. It can be described as large amounts of structured, unstructured, and semi-structured data that are transmitted from a wide variety of sources. Big data often incorporates other technologies like artificial intelligence or machine learning to achieve greater functionality. 

The main purposes of data technology include the following:

  • storage;
  • management;
  • visualization;
  • predictive analysis.

Why is big data important for financial businesses?

COVID-19 pandemic fueled the increase of remote work and the use of online services. This forced enterprises to act decisively and swiftly, especially in the field of all data transfer operations. Since financiers learned how to extract large amounts of data, its sustainable use and processing became the defining issue of recent times. 

Hopefully, modern designs elevated the data managing process to a new level. Fintech companies analyse incoming data to develop appropriate spending and saving strategies. It helps them to overcome ongoing challenges and gain important insights to improve consumers’ experience. Unlike traditional financial institutions, fintechs focus more on providing customized financial services, and this is why big data is important to them. Tailored services and products also help to make better investment decisions.

big data

Digital transformation has changed the way banking structures and Fintech enterprises provide their services. Companies of all sizes are increasingly directed towards implementing big data technologies. They profited in the following ways:

  1. Reduction of costs. According to «Big Data Use Cases 2015 – Getting Real On Data Monetization» report, 47% of the companies surveyed noticed this benefit. Moreover, big data use helped them to identify more efficient business solutions.
  2. Data-driven decisions. Businesses are allowed to combine ongoing data gathering and analysis. They streamline decision-making and take action faster.
  3. Enlarge range of services. More companies are creating new products that are tailored to customers’ needs. Data analytics allows finding a reasonable balance between meeting demand and delivering a good customer experience.

Fintech companies use data created from different applications. Such apps could include the following: asset and wealth management, online payments, international money transfers, insurance, investment, and others. They gather and process very detailed information about all inner activities. That implied close communication with customers.

How big data helps to improve customer service

Our digital footprints fulfill companies’ databases with a never-ending stream of information. Purchase history and recent activity may provide marketers with valuable insights. The information received helps companies to know their customers better, to gain an understanding of their pain points, challenges and objectives. Therefore, big data has become a great base for customized advertisements. Here are several types of its sources:

  • buyers story and contact call center recordings;
  • financial transactions and credit history;
  • social media posts, comments, and other activities;
  • results of different surveys;
  • computer cookies and others.

Given a source of valuable clues, companies can improve their performance and even destroy some of their competitors. And this is not the only way big data technology redefines the competitive landscape of the financial industry.

How big data technology influences financial services

There are a number of advantages to offering big data solutions to financial institutions.

New products development

Financial services companies can offer new services based on a deeper understanding of their customers. This could be accomplished through a 360-degree customer view. It includes customers’ wealth and assets management, personal data entered via chatbots and digital assistants. Customized ai-powered dashboards offer deep insights and therefore provide for consumers automated loan approvals and specific insurance policies.

Risk mitigation

Financial institutions adhere to serious legal regulations. Compliance requirements are shaping the measures to protect against financial collapses. Legal rules also control innovations’ adoption, such as digital currencies, open APIs, and faster transfers and payments. In addition, they address privacy and digital security considerations. To meet global requirements, fintech development services companies must use intelligence to develop advanced risk models.

Fraud prevention

It is particularly important for finance-related organizations to evolve their business strategies to take effective anti-fraud measures. Authentication systems, transaction processing systems, payment and billing systems are always at risk of personal and financial data loss. Fraud prevention that is powered by big data is a cutting-edge way to detect and prevent suspicious activity in a timely manner. Consumer’s purchases or credit activity stays clear for a service provider. Therefore, any provider can be automatically informed about potential fraud. Machine learning and big data analysis enable those responsible to generate more precise risk scores.

A full outline of the customer

Customer interactions and expectations have changed quickly as remote work and online engagements become more critical. With ai-powered analytics and big data, financial services are morphing into a customer-centric business model, with personalized services using real-time, in-depth insights into customer behaviors, attitudes, and experiences.

Is big data worth being trusted in the finance industry?

big data

The fintech industry is a quickly expanding area that attracts an increasing number of entrepreneurs, startups, and established businesses every day. The ability of a financial services company to deliver a well-developed and well-protected product is critical to its success in such a competitive field. 

Moreover, user experience became a primary driver of consumers’ expectations. As a result, the data collected may lead to clients’ leakage from traditional financial institutions. No doubt, big data collection causes a lot of concerns over privacy, so fintech software development companies should bear that in mind while developing financial software.


Massive amounts of data and rapidly improved technologies are changing the way companies operate and compete. It’s hard to deny, big data is the future of finance-related businesses — and sooner or later, the majority of companies will have to implement it to stay competitive. 

Even though the most significant decisions will remain for human employees, organizations need to establish a strong innovation adoption framework. In the age of technology, it is possible to successfully integrate modern big data solutions into financial product offerings and benefit by increasing revenues while offering lower costs.

Authors bio:  

Timothy Partasevitch is Chief Growth Officer at Smart IT.

Tim is a sales and marketing specialist, who solves business challenges like an engineer by focusing on data insights, analysing what works, what doesn’t, and what can be improved from a technical and financial perspective. Over the years he has supported the transformation of new clients into long-term partners and expanded services provided in the work space, ultimately facilitating revenue generation and business success. Tim strongly believes that you can’t be in charge of the outcome and results. However, you are 100% in charge of the input.