Like ATMs and online banking before it, advanced analytics is quickly changing the playing field in the banking world. Banks are increasingly using analytics to gain a competitive advantage and to form conclusions and insights based on the information they have gathered through basic reporting and data collection. Advanced analytics can be used to predict customer behavior and preferences and to improve risk assessment. It can also shape business decisions and lead to increased profits and success.
Components of Analytics Solutions for Financial Institutions
Most advanced analytics solutions for banking are comprised of four different components: reporting, descriptive analytics, predictive analytics, and prescriptive analytics. Reporting turns raw data into information – it focuses on what is happening. Descriptive analytics, the simplest class of analytics, can then be used to process and summarize the information gathered in reporting, identifying patterns. Predictive analytics uses these patterns and histories to determine what could happen in the future—how customers might act, what services will be profitable, and so on. Finally, prescriptive analytics uses the results of descriptive and predictive analytics to determine what is likely to happen, why it is likely to happen, and how best to take advantage of future opportunities.
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Focusing on Customers is Essential for Success
Banking has become customer-centric: knowing customers’ needs and preferences are key to building customer loyalty and customer retention over the long term. Analytics allow financial institutions to target and engage customers constantly and not just when they physically enter a branch; their reach now extends to customers using mobile apps, ATMs, and online banking. By applying analytics to customer segmentation, customer profiles, and transaction patterns, banks have the opportunity to gain valuable insights into their customer base and can translate this knowledge into increased customer satisfaction and retention. They can also use analytics to offer customized products, services, and deals to customers based on their profiles and histories.
Advanced Analytics and Fraud Prevention
Analytics in the banking world also helps to identify and prevent fraud. Banks can use advanced analytics to compare customer usage patterns against their own fraud indicators and can immediately take action when potentially fraudulent activity is detected. For example, they can freeze the account that has had unusual transactions until the activity has been confirmed as legitimate by the account holder. The use of analytics to gain knowledge about customers’ banking and financial habits is of great benefit here: having data on the specifics of each customer’s profile can help banks identify fraud more efficiently and refrain from inaccurately identifying fraud. For example, high-income customers and low-income customers are unlikely to have the same transaction histories and habits. While a series of large transactions may be normal for a high-income customer and would not indicate fraud, this scenario would likely be different for a low-income customer.
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The Future of Advanced Analytics in the Banking World
The faster a financial institution identifies fraud, the faster it can move to stop it—and, through the use of analytics, banks can move to prevent fraudulent activities before it even happens. Predictive and prescriptive analytics can be used to identify fraud patterns and predict when it may be committed again (holidays, for example, are typically fraud-heavy periods). According to The Financial Brand, the majority of people are more concerned about the security of their financial information than they are about having obscene photos of themselves being posted online, so it’s safe to say that effective fraud prevention is an important factor for customers. Fraud prevention increases customer loyalty, customer satisfaction, and customer retention for banks.
The overall penetration of analytics in banking is still relatively low compared to its usage in other industries; however, banks using advanced analytics have a definite advantage over their competitors who do not. In the near future, banks’ use of analytics is expected to increase significantly on a wide scale due to the numerous advantages it offers in terms of customer retention, risk assessment, and improved business decision making.