Big data in financial services: 9 companies to watch

The financial services industry is ripe for innovation. Technologies ranging from artificial intelligence, fintech, and even blockchain all pose an opportunity to disrupt a very large and important industry. However, not as much perhaps as big data, the massive technology changing every industry in the world.

In a place where data and data analysis is everything, financial services needs big data more than almost any other industry. Countless man hours are spent analyzing and reanalyzing information, work that can easily be done in the background by a machine.

Consider the lending space as an example: an entire industry based on loaning money with the expectation that the loan plus interest will be paid back in full. If every person who applied for a loan was automatically approved, the results would be horrible. Every bank offering up money would dry up within months.

With so much money on the line, financial service providers such as banks, accounting firms, credit card agencies, and plenty others need to focus on how to make your dollar go the furthest. Questions about loan security and risk assessment have been asked so many times already that big data can provide the answers.

Instead of pushing financial experts to reinvent the wheel, big data can free them up to focus on what they do best. Newer companies that are bringing big data to the financial services sector are transforming the landscape to be more forward thinking and better prepared for the future of finance. This brings us to our list of the top nine companies using big data to disrupt financial services:

Kreditech 

The most used method of assessing someone’s risk for loans is through their credit score. The problem is, there are millions of people without credit scores unable to be qualified. Kreditech is changing that. They’re using big data to create tens of thousands of data points on people that through machine learning can determine someone’s eligibility for loans and help them establish a line of credit. The process is so refined it can be done in a matter of minutes.

PeerIQ 

Plenty of times you’ll ask someone if they invest and their immediate response is, “I don’t like to gamble.” Investing doesn’t have to be risky – not if you know what you’re doing. PeerIQ is using big data to take the risk out of investing and put more money in your pocket. With their use of predictive analytics, they gather data points relevant to investment decisions and give investors actionable insights into what they’re buying.

ZestFinance 

ZestFinance brings you ZAML, the automated machine learning platform that gives lenders the information they need. Zest says that most lenders are working with fewer than 50 data points on their average borrower when making their decisions. Many times those borrowers are leaving and finding capital elsewhere with another lender. Zest brings thousands of data points to the table with big data and machine learning, allowing lenders to make more informed decisions and not miss out on real opportunities.

AppZen 

A big part of the financial sector is auditing. It’s easily the most grueling part of working in the finance sector and it requires a lot of man hours. AppZen doesn’t see it that way. Today automation can handle a surprising amount of tasks so they’ve put it to work on one of the most mundane cost sinks in business. With their machine learning platform backed by a network of big data, they are able to automate your audit process and reduce your costs by up to 50%.

Tala 

Mobile phones are in the hands of just about everyone in the industrialized world. The amount of data that passes through them is unquantifiable. Tala is taking that data to make better credit evaluations for everyone. The biggest issue in financial lending is lack of data on a customer or simply lack of credit. Tala is taking the biggest data mine in the world – our phones – and using it to make better evaluations of who is a risk-free borrower and who isn’t.

DemystData 

One of the biggest issues for financial service firms is having centralized data. Information is abundant, but sorting it is a business all on it’s own. That’s why DemystData has made it their business to centralize data for financial service firms. They’ve created a big data platform that gathers information and puts it on a gateway with simple-to-use sorting and filtering options that make sifting through data easy for anyone. This drastically reduces the manhours spent digging up customer information or finding data relevant to them across hundreds of places.

Qineqt 

The world is evolving with new technology, and finance isn’t immune to that change. Investors are working with every tool they have to enjoy the best returns, and to compete at that level, you need to work with the best. Qineqt is already on the job. They’re building the world’s largest deep learning technology to keep up with the evolving demands of investing. Qineqt’s platform is able to make associations relevant to trading that a human would never recognize. It’s changing the way trading is done.

Grow 

Grow is giving financial institutions a superior digital platform and big data insights to go along with it. On top of bringing them into the digital world, Grow is providing big data to financial service firms to have a real grasp on what their customers need. They can make predictions based on banking fees, investments, mortgage information, and more. All of this data is used to help financial institutions better serve their customers. Knowing what someone needs before they need it is the ultimate sales pitch, and Grow makes that possible.

Flowcast 

No one can explain what Flowcast does better than them: “Flowcast is building an API to allow suppliers on any B2B platforms quickly get access to affordable financing option.” Their service is pretty straightforward, but delivering on it is the real trick. That’s where big data comes into play. Having the right information allows Flowcast to point suppliers in the right direction. Acquiring capital has always been a difficult task, but Flowcast has made it incredibly simple by using data that already exists and putting it into action.