Big Data plays a pivotal role in FinTech. It offers valuable insights to support FinTechs in decision-making. However, working with a vast volume of data also presents many challenges.
According to the report, Essential Big Data In FinTech Statistics In 2023 by Zipdo:
Data plays a vital role in the success of FinTech applications. FinTech firms can make data-driven decisions, optimize operations, and enhance client experiences by analyzing vast datasets.
Here is some valuable support that data provides to FinTech firms:
- Enables precise risk assessment.
- Allows for more accurate lending decisions.
- Aids in fraud detection
- Helps to safeguard against financial crime
- Enable personalized services and recommendations
- Enhance user satisfaction and loyalty.
- Allows FinTech firms to streamline operations, cut costs, and improve efficiency.
- Assist in ensuring regulatory compliance.
For the FinTech, it helps to:
Build client profiles: Big Data can help FinTechs understand client needs and expectations.
Analyze client behavior: Big Data can help FinTechs predict client behavior and make better strategic decisions.
Create tailored services: Big Data can help FinTechs recommend products and services based on client spending behavior.
Broaden their client base: Big Data can help FinTechs identify potential users and their spending habits.
Identify potential errors: Big Data can help FinTechs identify inaccuracies within the system.
Provide seamless support: Big Data can help FinTechs create a digital log of a client’s banking activity.
However, despite being the backbone of FinTech, Big Data and its handling can pose some challenges for financial companies. Here are a few:
- It can become a trouble for existing infrastructure.
- It can lead to performance issues and slower processing.
- Data security is a key concern with the sensitive nature of financial data.
This article discusses these and more challenges posed by Big Data in FinTech. It also shares solutions that can help FinTech firms meet these challenges.
Challenges and solutions of Big Data in FinTech
Unmanageable Data Volume
The sheer volume of financial data can overwhelm systems, leading to slower processing and performance issues. In many cases, especially for companies with legacy infrastructure, computing power is inadequate for managing Big Data analysis. This defeats the purpose of collating it for market insights.
Solution: Investment in robust data management systems, high-performance servers, and storage solutions to handle large volumes of data. Upgrade of existing legacy systems to allow for higher computing power. Or, plain and simple, adopting SaaS cloud services provides add-on power to analyze the gold mine of Big Data.
Common sense dictates that the larger the data stored, the higher the security vulnerability risk. Especially today, when attacks have become smarter than ever before. Storing and moving data between apps, networks, or storage devices poses huge risks.
Protecting sensitive financial data from cyber threats is paramount to maintaining trust and compliance with regulations.
Solution: Implement robust encryption techniques to protect sensitive financial data in transit and at rest. User authentication and multiple-level encryption may be the only way to protect this data.
While collating data, especially if it has started manually, there are high chances of error. Even with digital collation methods, data can be unstructured, not clean, and difficult to work with. Ensuring the financial data accuracy is crucial, as errors can lead to incorrect financial decisions.
Solution: Data cleanup, structuring, and fragmenting applications are necessary to ensure the data collected can be useful. Deployment of data validation and cleaning processes to maintain data accuracy and reliability.
Given the risky financial and cyber security environment, there are huge risks for data security. Governments and regulatory bodies are constantly revisiting privacy laws and tightening them for better usage and customer protection. Under the ever-changing laws, Big Data can be difficult to handle and use.
The FinTech industry, in particular, faces complex and ever-changing regulatory requirements, challenging data management and reporting.
Solution: Utilize RegTech solutions to automate regulatory compliance, streamlining reporting and adherence to rules.
Adapting data infrastructure to accommodate the continuous growth of financial data is a persistent challenge in FinTech. Extra infrastructure is necessary to work on it. The value of the data lies only in the insights it can offer. So, if scalable analytics is unavailable, its analysis will be inadequate.
Solution: Leveraging scalable and cost-effective cloud computing platforms to handle growing data volumes and reduce infrastructure costs.
Combining data from various structured and unstructured sources for complete analysis can be complex. Disparate data is difficult to work with or keep secure.
Solution: Use specialized data integration tools and platforms to seamlessly combine data from multiple sources.
Striking between utilizing data for business purposes and respecting client privacy is a sensitive challenge. The regulations for data privacy globally are constantly ensuring that customer data stays safe. But it’s a tall ask for all organizations to meet these compliances. It costs to manage them and buy the tools required to maintain privacy as needed.
Solution: Implement consent management frameworks and transparent data handling practices to address privacy concerns.
Storing, processing, and managing large datasets can be a big cost to FinTech firms. Opting for on-prem or cloud storage, virtualization of Big Data to make it amenable to the cloud- and using analytics tools- all come at a hefty price.
Solution: Adopt cost-effective techs such as serverless computing and open-source data analytics tools. It will help to optimize data management expenses while maintaining efficiency and performance.
In FinTech, conquering Big Data challenges ensures innovation. The solutions outlined provide a roadmap for FinTech firms to excel in the era of Big Data. It will foster trust and deliver exceptional financial services.