3 Ways Analytics Solutions Help Banks and Credit Unions

You may be surprised to know that every day, financial institutions generate terabytes of data. Hidden among this data is critical information that can help banking institutions analyze and streamline their business processes, create outcome-driven marketing campaigns, and gain a competitive edge. But the question is how to get that information? Because this information doesn’t come in nicely wrapped packages.

The answer lies in advanced banking analytics.

Advanced banking analytics starts by helping you gather disparate data from multiple sources. Once consolidated this data is processed using AI and machine learning to offer you new insights into how your business is doing and how you can improve your core business processes.

Here are three examples of how advanced banking analytics is helping top banks and credit unions today:

Data Analytics for Risk Management

Every time a bank offers a loan to a customer, there is some risk involved. But with advanced analytics banks can gain key insights into each transaction, customer behavior and habits, and key account associations; predictive insights mitigate risks and lower the risk of fraud or default.

Advanced analytics can help financial institutions analyze factors that lead to loan default and plan a new strategy to address those factors. They can also use advanced analytics to detect fraudulent activities by identifying past patterns of fraud and associations between accounts difficult to uncover through manual means.

Marketing and Sales Automation

Today, advanced analytics in banking has made it possible to collect useful information about each customer, from their needs and buying habits to life events to interests and business relationships.. This information can be used to create marketing strategies that target the needs of each customer, offering the right solution at the right time. This not only results in growing wallet share, but also helps with customer satisfaction and retention.

Employee Experience = Customer Experience

For the past few years companies have been focusing on the importance of customer experience to business success. More recently, companies have recognized the link between employee experience and customer experience. It seems simple, happy employees make for happy customers (and happy customers do more business and stay in the fold) but measuring and then improving employee experience has been a challenge. Even more so in this new age of remote work.

Luckily there is advanced analytics to mine data hidden in disparate sources. This way banks can now reliably measure employee experience and understand the drivers behind it. Since all employees are not the same, machine learning can segment your workforce so that your HR team and management can develop plans for improving employee experience levels that target the needs and priorities of each of these groups.

Final Note

Advanced banking analytics solutions can address challenges across the enterprise. If you run a banking business, consider incorporating AI and machine learning into your business and reap the benefits they have to offer.

Author’s bio: The author is a blogger, and this article is about 3 ways banking analytics solutions help banks.

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