Three Ways Big Data is Impacting Financial Services
Companies across industries rely on complicated processes to generate the data they need to drive business. But all too often, these processes are slow and are limited by storage capacity. Today, many companies in the financial services industry are tapping into the power of big data analytics to help them overcome these challenges.
Big data is helping companies in the financial services industry in a variety of ways. For starters, it gives them more space for gathering and storing data. It also lets the companies analyze the new data and the old data, all in real-time.
When we talk about the financial services industry we specifically mean banks, credit unions, insurance companies, and investment institutions. Let’s take a look at three ways these firms are being positively affected by the advances in big data technology happening all around the world.
Banks and Credit Unions
Banks and credit unions rely heavily on loans and the interest they gain from those loans to finance their operations. They need consumers to not only get loans but to also pay them off in order to stay in business. It’s a relationship that both parties need and can benefit from if done in the right way. Consumers need loans and banks need interest.
The problem, however, is that banks and credit unions lose large amounts of money when people are unable to pay back their loans. Whether it’s repossessing a car or a foreclosure on a house, it’s not a good situation for the individuals or the banks. We saw the results of that in the last recession, and the impact is still being felt today. There were so many loans that weren’t being repaid that banks and credit unions were going under, which led to involvement from government agencies.
The importance of analyzing risk and getting customers who will pay back loans is paramount for these institutions. Big data technology makes this process quicker and more effective than ever before.
One lending institution–AvantCredit–takes in data from an applicant’s social media profile and other sources to determine how likely they are to pay back a loan. Those who may not have much credit history but get a good score based off of the big data collected will be more likely to get a loan.
AvantCredit has met with a lot of success due to this approach, which is also followed by many other startups like ZestFinance and LendUp. If that weren’t enough, the process of using big data saves enormous amounts of money, and those savings, are oftentimes paid back to the consumer through lower interest rates, and higher gain rates. In short, big data is proving quite beneficial for banks, credit unions, and their customers.
There are many different kinds of insurance — life, home, property, rental, car, and disability to name just a few. Insurance companies too, like banks and credit unions, rely on their ability to properly assess risk and then go forward in a way that will allow them to leverage that risk to bring in money, notwithstanding the claims that they will have to pay out.
Big data is important in allowing them to be more accurate and precise in how they assess risk and decide what to charge their customers. Insurance companies also rely heavily on sales forces to bring in new customers and new revenue. However, a lot of what those sales people do isn’t nearly as effective as companies would like.
For example, they have to go through numerous potential clients before finding two or three that will actually listen. Then from those two or three that do listen, maybe one will become a future client, and even then there are no guarantees. The end results it that the company and the salespeople waste valuable time with those who aren’t going to become future customers. If companies could better assess risk and be more effective in finding new customers, both the salespeople and the company would benefit.
Big data technology finally gives insurance companies the tools necessary for mining and analyzing this kind of data in order to improve sales techniques and client-finding tools. Big data turns insurance companies into more efficient and effective organizations, freeing up more resources for other pursuits and operations.
For both insurance companies and banks, the implementation of a big data platform makes it easier for them to market their products to current and future customers. With instant feedback through social media, mobile apps, and other tools, companies can be more precise and effective in their marketing. Instead of sending out mass emails, for example, they can target the individual, crafting a special message intended for that one person. That leads to a much better response rate.
One institution, US Bank, even used big data to generate more relevant leads for its numerous call centers. That in turn positively impacted the bank’s lead conversion rate by more than 100%, a staggering number based on just a few changes. Banks can also drastically reduce marketing waste and be more cost efficient. Better marketing is always going to help companies draw in more customers while keeping them around for a longer time. A customer that knows the company they frequent is meeting their personal financial needs and helping them toward a more independent life is more likely to stay loyal.
These are only a few examples of big data’s impact on the financial services industry. When it comes down to it, big data takes what these companies already have and builds upon it, serving both the institutions and the consumer.
About the author: Gil Allouche is the vice president of marketing at Qubole. Gil began his marketing career as a product strategist at SAP while earning his MBA at Babson College and is a former software engineer.