3 Ways Financial Services Businesses are Using Data to Drive Innovation

Businesses produce data every second, while some of it can help an organization make data-backed decisions about business activities, much of it will sit in data warehouses never to be seen again. But some companies have become data masters and found ways to use data not just to innovate but create change within their industry.

While data has millions of potential uses and is being used in many applications, here are three ways that financial services businesses are using data to innovate within the industry:

Using Data to Decision Loans Faster and Improve the Customer Experience

We live in an ‘on-demand’ generation, where instant food, instant entertainment, and instant answers aren’t just possible, they’re expected. This is one area where financial institutions are still lagging behind, as many financial services applications still take days or weeks to be processed. Whether it’s securing loans for purchases or applying for a mortgage there is frequently a long wait for approval. By maintaining this slow system loan providers run the risk of clients securing a loan through another provider before they’ve even processed the paperwork.

Many businesses are challenging this process by harnessing the power of data throughout the application process. Take Lenda for example, their mortgage application process is currently two weeks from start to finish and relies on data integrations to establish risk levels and meet compliance needs.

Another business using data to decision loans in minutes is Instabank, a challenger bank based in Norway. Instabank has developed in-store loan applications that can be completed in under two minutes and provide applicants with instant access to funds. The process relies on information from multiple data sources to rapidly assess an application and provide an exceptional consumer experience that is replacing traditional in-store loans.

Using Data to Expand Loan Approvals to the Underbanked

The Consumer Financial Protection Bureau reported that in the US alone there are 45 million individuals who do not have sufficient credit history to generate an accurate credit score. The demographics of people within this group are broad, from recent college graduates to high earning immigrants. While it’s easy to argue that these aren’t the ideal candidates for credit, especially if you base the risk factor on their non-existent or unacceptably low credit score, many of these individuals are strong candidates for credit when the risk analysis looks beyond traditional credit scoring.

Banking for the underbanked, or credit-invisible, is something that traditional banking institutions have steered away from, as assessing the risk of issuing credit to people in these circumstances is more than their decisioning processes could handle. So, for many, the only credit solution was high-interest loans from non-bank institutions. However, numerous fintech businesses are successfully bringing fairer banking solutions to the underbanked, including Lendup, who offer both loans and an unsecured credit card to underbanked individuals.

In a recent press release, LendUp credited both powerful data analytics and machine learning for their ability to, “identify potential customers who may be more credit-worthy than their score might indicate”.

With a focus on data and technology, LendUp has been able to bring credit options to the 56% of American’s previously underserved by traditional banking services and help them develop the credit scores needed to expand their future options.

Using Data to Power the Growth of Small and Medium Businesses

SME business loans have always been a tough segment for the financial industry, with businesses often lacking adequate financial history or the necessary capital to secure funding through traditional risk decisioning processes. The use of data in decisioning SME loans is no longer restricted by available technology, in fact just about any data source can be integrated into a risk decisioning process, from online business reviews to transactions on third-party sites. With a talented risk team and the right decisioning technology, data can significantly improve the accuracy of a business’ risk-decisioning process without creating delays.

Iwoca is a fantastic example of a business using data to innovate within the SME industry. Iwoca is a London based business that underwrites loans to small and medium enterprises throughout Europe. Instead of relying on traditional data for risk analysis, Iwoca has pioneered an alternative credit scoring method that relies on a wide range of alternative data including transactional information from Alibaba and Amazon Marketplace. Using this information Iwoca is able to analyze the risk a loan poses and determine a loan rate for businesses that would have been rejected through traditional channels. Accessible SME loans empower the growth of these businesses who would have been stuck in limbo without extra funds.

Using Data to Benefit Your Business

The businesses mentioned in this article have 3 key things in common:

  1. They’re using data to reduce risk
  2. They’re using data to grow their business
  3. They’re using data to improve the customer experience

If your business is yet to harness the full power of data to help drive growth, without sacrificing compliance, watch our short Data Integration video to learn how easily data can be integrated into your credit decisioning processes.  Watch now.