“They already know what the consumer has gone through, and they can pull up a recent order by the customer automatically,” Viola said. “The caller has already been verified, so there is no need for them to repeat themselves or their information, and the agent can immediately begin helping the customer.”
Automation also boosts efficiency by minimizing the risk of mistakes in routine tasks. Plus, because automated processes run around the clock, turnaround times are accelerated; for instance, a report generated overnight could be waiting for an employee’s review in the morning.
According to McKinsey’s report, automation has the potential to increase productivity in banking by 2.8% of the industry’s annual revenues to 4.7%, which translates to an extra $200 billion to $340 billion.
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2. Big Data: Transforming Analytics
In financial services, data is king, and there are exabytes of it flowing through IT systems every day. Big Data technologies allow organizations to securely manage and analyze the staggering volume, velocity and variety of information and increase productivity.
Big Data analytics allows for quicker and deeper insights into business operations. Instead of manually gathering and analyzing data to understand trends, employees can lean on analytics to consolidate the information in real time and then use artificial Intelligence tools to surface insights that allow for better decision-making.
For example, Big Data can make sense of information on customer demographics and behaviors so that teams can be more efficient in tailoring marketing efforts and personalizing services. Also, large-scale data analytics can help automate the aggregation and reporting of transaction patterns for regulatory compliance, saving time and lowering the risk of errors.
The speed of analytics from Big Data makes it possible to switch from a reactive posture to one of proactivity and efficiency, allowing a bank to predict when a customer might default on a loan, for example.
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