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How AI Is Revolutionizing Financial Services

Companies that are successful at adopting emerging technology early tend to perform better than those that do not. This is especially true in fast-paced industries like financial services.

According to one index from FIS, the top 20 percent of performers saw better revenue growth than competitors. For example, 40 percent of these “readiness leaders” grew their global revenue by 5 percent or more; only 22 percent of other institutions did the same. Similarly, 47 percent of readiness leaders increased their assets under management by more than 5 percent; only 23 percent of other organizations managed to accomplish this feat.

This just goes to show how necessary it is to embrace new technological advances as they hit the market. As City A.M. reports, 37 percent of these “readiness leaders” had incorporated artificial intelligence (AI) or machine learning into their business operations—compared to only 6 percent of other organizations within the financial services industry.

How can companies within the financial services industry use AI and machine learning to improve performance? Here’s a closer look at a few of the most promising areas.

 

Improving the Customer Experience

Customers and clients have more options than ever when it comes to selecting the financial services companies with which they do business. One of the primary challenges for organizations within this sector is creating a connected customer experience.

As it stands, fewer than one-fourth of marketers in financial services believe their technology is extremely effective at facilitating collaboration across their company. So, customer service teams may have a different view than marketers, sales leads and more. Siloed information often leads to important insights slipping through the cracks, which in turn means organizations miss out on the opportunity to provide a seamless customer experience—one that promotes retention and loyalty over time.

Search- and AI-driven financial reporting makes data insights from many sources accessible to employees across an organization, empowering them to make informed decisions in real time. It’s clear that customers and clients expect an increasingly personalized experience. AI algorithms can drill down into stored data in seconds to uncover relevant insights, shaping the very way financial services organizations drive revenue and foster positive relationships with clientele. The result? Marketers can use data insights to fine-tune campaigns. Customer service managers gain a more comprehensive view of what’s working and what needs improvement. Sales teams gain a better understanding of clients’ wants and needs. Perhaps most notable of all, employees and partners across an ecosystem can collaborate using a single, full-stack, AI-driven analytics platform for streamlined communication.

 

Fraud Detection

Financial services are a huge target for fraudsters seeking a lucrative payday. And when an organization experiences a data breach, it risks losing its most valuable asset of all: customers’ trust. This is why organizations of all shapes and sizes are implementing AI as a fraud detection measure. Through a process called data mining, AI algorithms can actually identify patterns and anomalies that may indicate fraud is afoot. These “red flags” can be everything from multiple login attempts within a short amount of time to IP addresses with suspicious locations and timestamps. The system then elevates these potential security risks to security teams for further action.

The beauty of machine learning is that these AI systems, rather than merely acting upon a set of pre-programmed rules, actually learn and improve over time. As Banking.com writes, fraud detection used to be based on “specific hard-coded sets of rules and logic questions.” But machine learning is now capable of adapting to trends without need for explicit human intervention.

These are just two key examples of how AI is revolutionizing financial services. One thing is clear: Institutions who adopt tech advances earlier have an advantage over those that lag behind.

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