In the early 1990's, the increasing popularity of automated teller machines (ATM's) revolutionised banking, lowering the number of tellers required for each branch and allowing thousands of new branches to be opened as a result.
Now, the banking industry is on the cusp of another technological revolution: big data and artificial intelligence are about to enhance nearly every aspect of banking, from improving the effectiveness of various marketing channels to helping consumers make more intelligent decisions about their spending and investments, preventing cybercrime, and more.
…but banks are always slow to embrace new technologies, right?
That may be the public perception, but the truth is that these new innovations are transforming the traditionally slow-moving industry into one that is truly innovative. Even industry behemoths like CitiBank are beginning to use a data-first approach to improve all aspects of their business, from spotting anomalies that could indicate fraud, to improving their customer experience and more.
Here are a few areas where business intelligence will have a major impact:
Forecasting consumer trends
In today's mobile world, each of us is generating swathes of data that, when combined, can allow future consumer behavior to be predicted with accuracy that was previously impossible. According to the Harvard Business Review, JPMorgan Chase & Co. discovered that consumer spending growth was declining after analyzing 12.4 billion debit and credit card transactions throughout 2014 and 2015. This helped to inform their ongoing strategy and uncover which offerings might be most suitable for a particular demographic.
Improving marketing effectiveness
The more you know about your customer base, the easier is it to acquire more customers and serve them better. By combining customer data with web analytics and powerful targeting tools (provided by major advertising portals such as Google and Facebook), banks are now able to reach consumers with offers that are likely to resonate based on a variety of demographic factors such as age, gender, location, and income. This means less advertising dollars are wasted. Furthermore, by analyzing the customer onboarding experience, banks can identify weak points and enable marketing, sales and IT to work together to improve their results.
Increase customer retention
At the end of the day, even if you can easily acquire customers, you won’t achieve consistent growth without retaining existing customers. Business intelligence can help here as well, by identifying areas for improvement in the customer experience. One European bank used machine learning to identify when current customers were likely to leave the bank or reduce their business. This enabled them to create targeted campaigns that reduced their churn by 15%.
One of the most valuable pieces of personal information cybercriminals can get their hands on is your banking data. With thousands or millions of individual accounts, banks themselves are a major target. This means that even small banks are being constantly bombarded with ever more complex attacks looking to exploit any vulnerability. Business intelligence can help by monitoring the traffic on your network for irregularities and quarantining known threats, allowing IT professionals to focus on higher-level cybersecurity priorities.
Modeling credit risk
Traditionally, credit decisions have been made based on a variety of factors, including balance sheets, cashflow statements, and credit scores. There's nothing wrong with this system, but what if you could take even more risk factors into account? It's likely that the availability of more data about consumer's spending habits, income stability, and other factors will soon make determining credit worthiness more accurate than ever before.
Key decision-makers at any firm need to be able to quickly understand what actionable insights can be gleaned from a data set without poring over endless spreadsheets or becoming an amateur data scientist. This is where dashboards become particularly useful; by using graphs, charts, animation and more, a carefully designed dashboard can convey the overall meaning of a data set in mere seconds instead of hours. Luckily there's no shortage of powerful business intelligence software that can help you move beyond simple spreadsheets into visualizations that make information more easily digestible.
Regulatory costs have dramatically increased in the years following the 2008 recession, outpacing banks' profit growth. As a result, ensuring compliance more efficiently is a chief concern for many executives of financial institutions. By helping to gather, analyse, and compile data, business intelligence can make regulatory compliance easier.
By measuring business performance by sector and individual, banks can better understand how time and resources are being allocated. This information can then be used to set departmental budgets and personnel goals, as well as to determine what sort of continuing education might be most beneficial for increasing efficiency and output.
According to a recent Bain & Company report, early adopters of big data analytics are garnering significant advantages over the competition. To be specific, early adopters are:
Twice as likely to be in the top 25% of financial performance for their industry
Five times as likely to make decisions faster than their peers
Three times as likely to execute their plans as intended
Whether it’s growing your customer base and revenues, combatting cybercrime, or keeping Uncle Sam happy by ensuring all regulatory boxes are checked and reports filed on time, business intelligence is going to continue to change the face of banking.
As a banking professional, you need to be prepared for your role to change with the coming technological advances. Just as the ATM made the cash handling skills of bank tellers less important than their marketing abilities, so too will business intelligence change the nature of many banking positions, even that of executives.