5 Banking Sectors Being Redefined by Big Data

This post was published on the now-closed HuffPost Contributor platform. Contributors control their own work and posted freely to our site. If you need to flag this entry as abusive, send us an email.

As the big data revolution continues, the financial sector is poised to be the next to benefit. The banking sector is already sitting on a minefield of personal data like like spending habits, places and patterns of purchases. More importantly, the data is accessible and constantly updated.

Indeed, a recent Alacer group report revealed that US banks manage over one exabyte of data stored on their systems. How much is that? Think of all the information on over 275 billion (yes, you read that correctly) digital music players. This is also a good indicator of just how much personal information financial institutions know about each of us. But, don't panic. All that data is going to strengthen the banks to benefit you in a number of ways in the near future.

Security and Fraud

Understanding the purchasing history of each customer makes it possible to know when abnormal spending is taking place. This has traditionally allowed banks to freeze credit cards when they're suddenly used in a peculiar location or for unlikely purchases.

Big data now means a bank can undertake far more sophisticated fraud prevention by analyzing a customer’s spending habits in the context of other customers who have similar incomes and history. As we continue to migrate toward a world dominated by online (mobile) shopping, behavioural analysis will be essential.

Risk Management

Risk management is an area where banks can most definitely benefit from big data analysis. A challenge for the investment sector, for example, has been customers defaulting on loans and bad investments. Up until recently, lenders had to rely on current data, often provided by the borrower. Big data permits monitoring borrowers for key events that may indicate a likelihood of default. Factors like payment history, interactions with banks, data supplied by major credit bureaus, and even social media activities, could all contribute to a behavioural model that could better inform a potential lender.

Big data is also playing a role in risk assessment of markets. One thing is certain, the markets are now more interconnected than ever. And information is travelling those connections more rapidly every day. As a result, when the markets are volatile, they can shift from tepid to to a tempest in a moment. Big data allows the financial sector to ensure that such issues are dealt with at an early stage.

Customer Service

A thorough analysis of a customer’s data allows a bank to identify and resolve problems almost immediately. In the past, a bank’s interaction with a customer was predicated on a number of questions in order to ensure that the problem was correctly identified. But with the correct use of big data, a bank can see that a problem exists and proactively contact a customer as soon as an issue emerges. Or, respond quickly when a problem is brought to their attention by providing a customer service representative all the relevant information in real-time.

Big data will provide better customer service by analyzing unstructured customer data from many fronts: email, telephone calls, social media, discussion forums, and more. The deeper and broader the analysis, the better the bank can understand each customer’s unique needs, and appropriately address them.

Personalized Offers

Gone are the days when a generic offer and impersonal plan will attract new bank customers. In 2017, people expect tailor-made offers designed with their special needs in mind. This is particularly true for Millennials, who want more personalized interaction with their service providers. Banks are no different in this regard. By analyzing a customer’s details and spending habits and even social media accounts, a bank can target a customer with an offer they themselves may not realize they are looking for, but will appreciate.

According to a recent bank innovation report from Forrester, only 50% of bank customers are willing to keep their existing level of business with their bank. Many cite a desire for "richer and more personalized digital experiences" as a factor. That's a big problem for banks that have "relied on a lifetime loyalty factor, assuming that an initial checking or savings account as a young adult predicts a future buyer of auto loans, mortgages, home equity lines, and investment services," says Forrester.

Banks need to use all the tools at their disposal to secure loyalty.

Investment Advice

A clever analysis of data will inform a bank about various milestones in each customer’s family. When a customer’s child reaches the age of ten, for instance, a bank could advise on good investment opportunities for a university fund. Or, if a client is considering buying a home, the bank is best placed to take advantage of a potential mortgage opportunity.

Overall, the banking sector has not yet taken full advantage of the revolution, but this is sure to change over the next year. We’re already seeing a number of approaches to managing the huge amounts of data the banking industry is accumulating.

Hewlett Packard Enterprise (HPE) claimed this week to have introduced the world’s largest single-memory computer, which contains 160 terabytes (TB) of memory. Companies such as SQream, on the other hand, have a software-driven approach that harnesses currently available systems using a cost-effective GPU. SQream says its system is usable by anyone with even basic SQL knowledge. This may well be the better solution for the banking industry which can’t wait for the next-generation of computers to hit the market.

Either way, the promise of faster, more personalized banking service is right around the corner.

Before You Go

Popular in the Community