The finance industry is transforming as it moves from traditional brick-and-mortar branches to online and mobile channels. While this shift has been beneficial for consumers, it also presents many challenges for financial institutions. One of the primary challenges is financial organizations need to keep up with the ever-changing needs of their customers. As a result, banks need to leverage business analytics software to produce aggregated data that highlights and predicts customer behaviors and preferences. These insights are crucial to developing new products and services that best meet customer demands.
Let’s take a look at how this software can help financial organizations thrive in the modern era.
Benefits of Business Analytics Software
Business analytics is the practice of collecting and analyzing data to identify trends and patterns in business operations, customer behavior, and the marketplace. The goal of business analytics is to gain insight into the business to make better decisions. With this information, companies can be better at predicting the future today.
Thanks to modern improvements in speed and accuracy, financial companies can now apply this technology more broadly across various areas of their businesses to increase their chances for success.
Here are the top benefits of this technology for financial services.
1. Smart Decision Making
Using business analytics software, financial institutions can analyze data and make better and faster decisions at any point in time.
For example, banks can use it to predict future behavior based on historical data sets. Suppose a banking customer has previously missed payments on loans or credit cards in the past. In this case, the software will alert the bank, and they may decide to deny their loan or increase their interest rate since there’s a higher likelihood of default.
This is an example of how machine learning algorithms can help banks make smarter decisions about granting credit and deciding interest rates for customers who may be prone to late payments.
Financial organizations can use predictive analytics to identify customer data patterns, allowing them to improve their products and services.
They can also use business analytics software to offer personalized financial advice or investment portfolios based on customers’ needs and risk appetite. For example, a bank might use artificial intelligence to analyze a customer’s spending habits over time, allowing it to make recommendations on how they should invest their money — whether that means opening a new 401k account or investing in mutual funds.
3. Fraud Detection
A recent study shows that credit card fraud costs US consumers $10 billion annually. With aggregated data banks and other financial services brands are able to identify fraudulent transactions, assess the risk associated with transactions, and gauge exposure to loss based on these analyses.
Credit card companies use artificial intelligence to detect fraudulent transactions before they reach consumers’ accounts. For example, Visa uses machine learning algorithms to detect patterns in spending behavior based on online purchases and offline transactions made by cardholders. This helps see unusual spending patterns that could indicate fraudulent activity or identity theft.
4. Enhanced Customer Care
Banks can use business analytics software to predict customer behavior, which helps them provide better customer experiences. Customer centricity is critical to success in an industry with fragmented customer loyalty, customer centricity is vital to success.
For example, a bank could use machine learning algorithms to predict how likely a customer is going to switch banks based on things like account history, spending habits, payment behavior, and demographic information. This enables them to offer incentives or rewards when customers are most likely to stay with the bank or open new accounts.
5. Reduced Risk
Investment firms, including hedge funds and private equity firms, are increasingly turning to business analytics software to help them make better decisions.
These tools help investment firms predict trends in the market and help them plan for the future. The software can also be used to analyze an investment portfolio and determine if there are any risks involved with certain investments or companies that have been added to the portfolio recently.
Business intelligence software can also help investors analyze their performance over time and compare it with that of other investors in similar industries.
Internally business analytics can help financial firms with operational efficiency. Business analytics software can enable finance teams to analyze business performance across all departments, identifying bottlenecks, inefficiencies, and opportunities for improvement in real-time.
For example, a credit union might find that they have an increasing number of customer complaints about the speed at which their mobile banking tickets are processed.
By analyzing data from previous years, they may be able to spot patterns that highlight issues with quality control or training needs among staff members responsible for processing these tickets.
The world of finance is changing. Big banks and corporate monopolies are dwindling as boutique finance technology companies disrupt a conservative industry. Pandemic lockdowns that forced all digital banking advanced a convenience-forward trend that’s been building for years. Customers are no longer loyal followers or brands but opportunists waiting for the next best thing.
To survive the uncertainties of the economy and customer preferences, financial brands utilize business analytics software to predict future results based on past data, make data-driven decisions, personalize offerings, prevent fraud, boost customer care, and minimize risk. Financial providers can also benefit internally from operational enhancements.
The above are just some of the benefits of business analytics software, yet the possibilities are endless. Businesses can use software to achieve goals that they never thought possible before. With the ability to ingest over 250 million events hourly from hundreds of data sources, Live Earth’s operational analytics platform helps eliminate data silos, remove data latency, and avoid data fatigue. Contact us to make informed decisions when it matters most with Live Earth.