Financial institutions are becoming increasingly reliant on big data analytics as the amount of data they collect and analyze balloons each year. Data has always played an important role in the financial services sector by facilitating more informed decision-making, but it has become so immense in variety and volume that it far surpasses a human’s analytical capabilities.
By taking advantage of increasingly complex computer algorithms, financial institutions are analyzing larger and larger datasets to address potential risks, identify growth opportunities, and make accurate, informed decisions. A gradual move to tech-driven commerce has provided the financial services industry with a treasure trove of data in an age where information is as valuable as oil.
Credit scores, transactional data, social media, browsing, and spending habits are just a few of the data points financial institutions now have access to. Artificial intelligence (AI) and machine learning technology can help them analyze vast amounts of this data in very small time frames, a feat even the best analysts couldn’t achieve by themselves, to optimize their operations and boost their profits.
Leveraging machine learning and AI can help financial institutions tweak their products and services to align with customer preferences, improving personalization and boosting customer experiences. According to McKinsey, banks that used big data to improve personalization cut customer churn by 15%, showing that big data-driven personalization can have tangible benefits for financial institutions.
Big data analytics can also help players in the financial services segment predict market trends, fluctuations, and, to some extent, the stock market. The larger the dataset, the more accurate these predictions will be, especially if financial institutions use advanced machine learning and AI to conduct the analysis. The ability to forecast future trends with increasing accuracy will help institutions such as banks predict market movements, potential new clients, real estate prices, the best loans to offer, and so much more.
While the majority of these big analytics features will only be available to institutions, consumers may also have access to some of them depending on the business they conduct with financial institutions. For starters, someone with a multi-currency account may benefit from advanced analytical models that use historical data to recommend the currency to keep.
Big data analytics could also help financial institutions make informed and accurate decisions in real time. Real-time data could allow banks to assess risk in nearly an instant and make trades or approve loans on the fly, rather than spend hours or even days analyzing historical data before making a decision. In a world where split-second decisions can be the difference between profit or loss, real-time data analytics is a godsend.
Entities like FingerMotion Inc. (NASDAQ: FNGR) are constantly making new big data analytics solutions available to their customers in various industries. As these tools are leveraged to their fullest, the benefits accruing could translate into cost-savings and other advantages to end users.
NOTE TO INVESTORS: The latest news and updates relating to FingerMotion Inc. (NASDAQ: FNGR) are available in the company’s newsroom at https://ibn.fm/FNGR
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