Data analytics has been a prevalent tool in the financial and banking industries since its inception in the 1990s. In recent years, thanks to emerging technology, the potential applications for analytics are greater than ever before. Data analytics utilizes technical tools to come to conclusions about large sets of data and has completely revolutionized the way datasets are manipulated and visualized. In recent years, it has transformed the financial and banking industries as a whole by reducing wasteful spending, identifying areas for improvement, and streamlining internal operations. Now, paired with artificial intelligence (AI), the industry is expected to grow substantially over the next 10 years, with banks increasingly investing in AI technologies to continue to enhance their operations. The global big data analytics market, valued at $348.21 billion in 2024, is expected to reach $924.39 billion by 2032 (Fortune Business Insights, 2024). Following the implementation of these tools, questions arise concerning how the job market will continue to adapt and evolve in the coming years.
The global big data analytics market is expected to reach $924.39 billion by 2032
The concept of analytics has been traced back to ancient Egypt, where clay tablets were used to keep track of both agriculture and livestock. Since its origin, it has evolved past the use of single statistics to more advanced analysis and machine learning. The use of forecasting has allowed businesses to spot and predict future trends, as well as patterns in customer spending and potential risks. With the recent integration of artificial intelligence, the capabilities of big data and analysis have increased drastically. With this revolutionary tool comes the possibility for companies to maximize efficiency, expedite the analysis of large sets of data, and hold a complete advantage over competitors.
As the use of data analytics continues to evolve, the impact on businesses prompts conversation about the future of the job market. One major concern is the potential for job loss as AI is implemented across varying business sectors. That said, it is expected that rather than decreasing the size of the job market, increased implementation of AI will cause a shift in available jobs. Consequently, a variety of new employment sectors will emerge. Although AI can help increase efficiency in the workplace, it lacks the social skills and adaptability of human workers. As such, it will be utilized more in the completion of routine, day-to-day tasks. With this, we may see the emergence of jobs, including Language Model Trainers, focusing on polishing pre-trained AI systems to work to complete certain business requirements. We may also see the emergence of API Integration Experts focusing on implementing AI into businesses and workflows. Employers may also seek out more AI-experienced candidates in order to concentrate on further improving and overseeing the business operations. With the increasing technicality of AI, employers may shift priorities to candidates who will continue to increase operational efficiency.
Internally, AI will bring about the biggest changes in fraud detection, customer experience, and banking efficiency. By using a combination of artificial intelligence and business intelligence, banks will be able to capture and analyze spending patterns quicker and use larger sets of data, leading to more accurate and effective data management. When flagging unusual activity, AI sends an immediate alert, allowing for fast and proactive protection against criminal activity. To achieve these tasks, AI utilizes machine learning algorithms as a set of rules and processes in order to predict how to work with and understand data (IBM). These algorithms can detect fake IDs and forged signatures and provide factors such as two-step authentication to protect against the use of these. A 2022 study by Juniper Research found that AI-driven fraud detection systems could save banks approximately $10.4 billion globally by 2027 (Juniper Research, 2022). Similarly, banks are using the technology to focus on tailored customer experiences. Over time, the value of customer service within institutions has continued to increase. A report published by Salesforce states that 84% of consumers think that customer experience is equally as important as the products and services offered by an enterprise, and 54% believe that companies need to innovate the way they engage with them (SalesForce, 2019). Through AI, banks will be able to improve satisfaction by providing 24/7 assistance to their customers and more personalized experiences, as well as predicting issues that customers may have regarding services. Additionally, a more tailored customer experience means more unique advice for customers, including investment advice, credit card offers, and loan opportunities. Finally, artificial intelligence provides opportunities for banks to increase efficiency in internal operations. By providing faster, more accurate information and data input, AI will catalyze a major shift in the financial and banking industry.
Large banks such as JP Morgan and Capital One are leading the market when it comes to research in data analytics and the applications of AI. The benefits of implementing AI in data analytics are astounding, and according to a 2020 survey from The Economist Intelligence Unit, it may be the main differentiator between whether a bank flourishes or falters in the coming decade (Economist Impact, 2020). JP Morgan has committed to harnessing the potential of AI and is pulling ahead of competitors in AI research. The research done by the company, focusing on both theoretical and applied knowledge, includes nearly 27% of all papers published by banks (Evident Innovation, 2023). Dedicating both time and human resources to this will prove to assist in the development of new techniques and models. Further innovating the production within the bank. The conversation surrounding AI research also extends to the investment sector. By investing more, banks such as Capital One open themselves up to the opportunity of innovation and advancement. Many times, banks that invest in the AI process are at the forefront of integrating new technologies, furthering their competitive advantage over others (Bain and Company, 2023).
As technology continues to advance, banks that are not willing to invest time and research into AI may find themselves falling behind the pack. This may further affect their opportunities to mitigate risk, streamline their internal processes, and affect their overall reputation from both customers and investors.
Financial institutions and banks are constantly evolving. The use of analytics and artificial intelligence causes this rate to continue to multiply, and the use of AI has become an essential function in day-to-day business operations. With this, we may expect to see a shift into AI oversight and tech-based jobs. Both AI and data analytics are extremely powerful tools, and investing in them may be the biggest decision banks make today. The relationship between banks, data analytics, and AI not only streamlines operations and internal processes but also moves the industry as a whole towards innovation and a better, more reliable customer experience.