The fintech industry is one of the fastest-growing sectors in tech. It has evolved from a niche and elusive industry trend into a transformative force in the global financial landscape, with over 10,264 fintech companies operating in the US.
As the fintech industry evolves, so too does the technology that it uses. Today, Biometric Authentication in Fintech has been adopted to improve security, prevent financial losses, and improve customer service. Another technology that is having a massive impact on the fintech industry is AI and machine learning, which can optimize and automate services that will redefine the practices of finance and chatbots. A result of this integration of new technology is that fintech companies now have access to large amounts of data that they can use to improve their services, spot consumer trends, and tackle fraud. In order to fully take advantage of this data, fintech companies are investing in document databases that can handle the data demands of modern technology.
What is a Document Database?
A document database is one of the four major types of NoSQL databases, the others being key-value, graph, and wide-column databases. As per its name, a document database stores data in a record called a document. A document stores information about one object and any of its related metadata and stores the data in field-value pairs. MongoDB’s document databases show how the values can be a variety of types and structures, including strings, numbers, dates, arrays, or objects. Documents can also be stored in formats like JSON, BSON, and XML.
There are several key features of a document database that have made them popular across industries. They are very flexible and can store structured, semi-structured, and unstructured data, which makes them compatible with mobile and web applications. Documents can also map to objects in most popular programming languages, and this allows developers to easily develop their applications. With the fintech industry expanding at a rapid rate, the ability of document databases to rapidly scale through distributing data is why they are used by many fintech companies.
How the Fintech Industry Uses Document Databases
Real Time Data Analytics
The success of a fintech company depends on its ability to keep up with developing market trends, provide accurate risk management, and show enhanced decision-making. Because of their flexible nature, document databases can store the different datapoints required for data analytics, and most databases will have an analytics feature built in. A fintech paper on ResearchGate titled Real-Time Analytics in FinTech: Leveraging NoSQL Databases for Faster Insights outlines how document databases have fast enough data processing and data retrieval speeds to be able to provide real-time data services compared to more traditional databases. This allows them to get faster insights without any issues with performance. Fintech companies that use real-time data analytics backed up by document databases are able to be agile and competitive.
Fraud Detection
Alongside spotting market trends, fintech companies employ document databases to help prevent fraud. Document databases can handle large volumes of data in real time, which allows them to be used to spot patterns and anomalies that point to fraud. They are also suited for handling unstructured data like images, PDFs, and JSON documents, which are commonly used in identity verification to spot fraudulent activity. As we mentioned in the introduction, more fintech companies are using biometric authentication, and document databases are able to store this information and support the authentication applications to increase security protocols.
Customer Data Management
More and more people are using fintech in their daily lives, with the digital payments segment of fintech used by 3 billion people globally. In order to handle this massive customer base, the fintech industry uses document databases to store customer information as key-value pairs. The key will represent specific attributes such as names, addresses, and emails, and the value is the corresponding data. As not all documents in a document database are required to have the same fields, this makes it easy to store and organize customer data in one place.
As the fintech industry grows, the ability to effectively store and manage data will become increasingly important. Being able to handle a wide range of data types, as well as provide real-time analytics services, has made document databases widely used in the fintech industry.
