Like every major industry, banking is seeing a shift to be more digitally dependent and tech savvy. Technology has invaded traditional financial institutions and their processes, causing them to have to find effective technology to provide better service and products to their customers.
At the recent Financial Brand Forum in Las Vegas, Nevada, experts in the field of banking came together to discuss the trends that are changing the way we do banking. Services are changing, the landscape as a whole is changing, and financial institutions are developing thoughtful and effective strategies to make sure they are on top of the trend. Two components in particular that are being researched and implemented are artificial intelligence and machine learning.
When people hear the term “artificial intelligence,” they may think of science-fiction. But this form of machine learning has already become part of our everyday lives, even in banking. This is just the latest application of what technology can do to collect data and use it to predict activity, making processes more efficient.
Minimizing decision-making is one thing that banks can benefit from. Artificial intelligence is helping to more accurately help processing banking duties for customers and streamline the time it takes to operate. Data-fueled predictions are becoming commonplace in banks, and utilizing data to achieve greater efficiency and provide better service is an easy decision to make.
Another way in which AI is helping banks is by providing predictive analytics, which, when used correctly, is a great tool to detect unusual activity and protect sensitive information. An additional way in which banks can protect data and information is by investing in insurance for banks, which guards financial institutions against new forms of threats. AI gives banks views to consumers and access to data on new levels that will only continue to bolster efficient and modern services.
Many banking decision-makers still think that machine learning is irrelevant in the banking world. This subset of artificial intelligence is, in fact, vital for financial businesses when it comes to data. Spending money on machine learning–which isn’t cheap–in fintech is set for a big growth over the next five years. And with the development of analytics in this field, machine learning will help unsecured consumer loans will jump almost %1,000, a global haul of neary $17 billion, according to a recent study by Juniper.
Machine learning technologies applies algorithms to dissect and analyze datasets, and pinpoints patterns to create customer insights. This kind of technology can be seen on Google Maps, Netflix, or Amazon, recommending routes, products or shows to watch. How can machine learning be used in the banking industry? There are many ways including high-accuracy tasks like underwriting, and taking care of back-office functions and repetitive work.
In the coming years, more banks and those in the know of the financial industry will see these two components reach to more sophisticated levels and common usage.
Check back next week for more information on trending topics for banks and financial institutions.
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