How NoSQL Databases Are Being Used in the Fintech Industry

Those who have been following the latest tech trends will know that two areas that are seeing the biggest developments are fintech and data management. Both sectors have evolved to keep up with modern technological innovations such as smart devices, the Internet of Things, and the rise of artificial intelligence and machine learning.

In the past decade, fintech has seen an explosion in usage as more people use smart technology to manage their finances. A recent fintech report from the World Economic Forum and the Cambridge Centre for Alternative Finance found that customer growth rates averaged above 50%. As more people use fintech, more data is being created that can be used to improve financial services. This has led to more fintech companies using NoSQL databases to keep up with the increasing amount of data that fintech applications collect.

What is a NoSQL Database?

A NoSQL database is different from a traditional SQL database because it is much more flexible in how it stores data. While SQL databases will store and organize data in tables, a guide to MongoDB’s NoSQL databases details how a NoSQL can store data in four different data models. These are document databases, key-value databases, wide-column stores, and graph databases. Each NoSQL database has its own unique features while also being flexible, scalable, and able to distribute data across multiple databases. NoSQL databases also allow developers to store huge amounts of unstructured data. This data doesn’t have a fixed schema and can include text, images, video, and data from social media posts, emails, and smart devices. This allows the database to create massive datasets consisting of different types of data that can then be collated together to find patterns and recommend services. The fintech industry is effectively using these advantages of NoSQL databases.

Data Collection 

The fintech industry is constantly evolving in terms of how people can pay for products and services. A recent innovation was the Singapore Quick Response Code. This allowed merchants to receive payments from multiple payment networks and apps at the same time, eliminating the need for multiple QR codes. While these apps are revolutionizing how people pay, they are also changing how the fintech industry stores the users’ financial data. Most of the data from these apps is unstructured, whether it be financial transactions from mobile finance apps or search preferences from web-based solutions, and a NoSQL database can store it on one of its data models, depending on the fintech company’s needs. This is especially useful for fintech applications that deal with analytical and exploratory data, such as risk management, as it allows the application to find patterns.

Fraud Detection

As more people conduct their finances online, the risk of fraud has also increased. NoSQL database systems are better able to detect fraudulent activities than relational databases due to their ability to leverage multiple data sources and perform advanced real-time analytics. A Research Gate paper on fraud detection in NoSQL database systems outlines how these databases can use machine learning to determine patterns pointing to anomalies. For example, a graph database, which is used to find contextual relationships between data points, can uncover discrepancies in a dataset. This is vitally important for fintech applications where only the smallest shifts in client behavior patterns can point to fraudulent activity.

Personalization

As we outlined in our post on the Evolution and Future of Accounting Software, customers are looking for personalized experiences. In fintech, this means a service that doesn’t cater to the wider population but instead offers solutions matching their individual financial needs. Financial organizations that collect a wide range of information about their customers can create comprehensive user profiles of the individual on a NoSQL database. Because a NoSQL database has a very flexible schema, financial companies can collect and store data from multiple sources. This allows them to collate different pieces of a client’s data to recommend the best services for the individual. This information can then be used to provide loans or offer financial services based on the individual’s financial history, risk aversion, and spending habits.

As the fintech industry grows, more fintech companies will use NoSQL databases to efficiently collect client data and use it to prevent fraud and provide personalized services.