Big Data Trends in the Financial Services for 2023 and Beyond

Over the past few decades, there has been rapid technological advancement the world over with individuals and organizations alike having to adopt technologies to stay relevant and thrive. Big data is one of the technologies that have arisen from the advancements in technology.

The Oxford English dictionary defines big data as extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.

Traditionally, data collection was done by humans and decisions made based on deductions made from calculated risks and trends. In recent times, however, due to advancements in technology, computers are now used much more to gather data which offers unlimited potential for data. The data collected by computers is very large, making it impossible for traditional data processing methods to manage them. This is where big data comes in.

These volumes of data, if well processed and managed, can be used to address business problems more effectively than would have been possible before.

By investing in big data analytics technologies, organizations can better harness their data and use it to identify new opportunities, leading to better, data-driven business decisions, increased operational efficiency, happier customers, and increased profits.

Big data technology practices are a must-have for organizations that are looking to grow and stay ahead of their competitors. The advantages of using big data include; increased efficiency, better decision-making, application of best practices for managing big data, and more data insights. Big data trends can help businesses make better decisions, provide a better customer experience, overcome challenges, and increase efficiency.

Digitization in the finance industry has enabled penetration and transformation of how financial institutions are competing in the market. More and more companies are embracing these technologies to accomplish digital transformation, consumer demand and increase profit. Although most companies today collect and store data, many are unaware of how to use it to maximize their potential. Here are some ways in which big data can be used in financial services sector:

• Studying consumer patterns
• Monitoring financial market activity
• Analyzing customer data, along with behavioural data to create detailed customer profiles that can be used to create content for different target audiences, recommending content based on the customers’ tastes and measuring how a product or service is performing.
• Using data to spot gaps in the industry and create innovative ideas to fill those gaps and make their customers’ experiences better.

Since big data entered the financial scene, its use has evolved significantly across different industries, and the financial services sector has not been left behind. Some of the current big data trends in the financial services sector include:

Stronger Resilience on Cloud Storage.

Big data comes from many different sources, and with the growth of technology, increased knowledge of how contrasting data can be used strategically is an issue. In most businesses, traditional data storage is no longer enough. Therefore, cloud and hybrid cloud solutions are preferable because of their simplified storage and scalability. With increased dependence on cloud storage, companies have begun to implement other cloud-based solutions like cloud-hosted data warehouses and data lakes to keep up with the large amounts of data.

Ethical Collection of Customer Data.

All the data collected comes from consumers, and data regulations require all organizations to handle the data they gather from their customers with care and compliance. However, it becomes complicated when companies do not know where their data is coming from or if sensitive data is stored in their systems. As a result, more companies are relying on software that prioritizes the ethical collection of customer data. Businesses today are opting for first-party data sourcing to ensure they comply with data laws and maintain data quality.

Artificial Intelligence Automation.

Financial services providers are increasingly using big data to power AI, both for customers and for their internal operations. Without big data, AI would not have the data necessary to replace human actions. The automation and workflow shortcuts that AI has made possible in businesses have changed the game. With the growth of artificial intelligence solutions, more predictive and real-time analytics in everything from workflow automation to customer service chatbots are revolutionary.

Growing Data Fabric Technology.

Data fabric is an emerging approach to handling data using a network-based architecture instead of point-to-point connections. Financial organizations that need additional space and increased accessibility for their growing pools of big data are  progressively adopting data fabric technology which allows them to easily store and retrieve data sets across distributed on-premises, cloud and hybrid network infrastructure.

The Vector Similarity Search

The Vector Similarity Search involves representing pictures or bits of text as embeddings. It is a new approach to finding and retrieving data through deep learning and state-of-the-art algorithms to find items by their conceptual meanings rather than keywords or properties. It improves results for text, image and audio search, recommendation systems, feed ranking, fraud detection and other applications. Businesses can use the vector similarity search to improve their customers’ experience while using their websites or social media sites.

Cybersecurity.

Data breaches are more common today than ever before, and there is no sign that they will stop anytime soon. Organizations that want to stay ahead of the curve must invest heavily in cyber security. A comprehensive cybersecurity strategy, governed by best practices and automated using advanced analytics, artificial intelligence and machine learning, can fight cyber threats more effectively and reduce the impact of breaches when they occur.

In a bid to grow their business venture, organizations seek to better understand their customers and their needs in order to offer good services as well as grow and stay ahead of the competition. Swift and timely adoption of big data technologies to harness the true potential of the data organizations collect and store can help them make better data-driven decisions.

Article by Sally Akoth and Juliet Hinga

Would you like to share an article? Write to us at sbscommunication@strathmore.edu