It was an ideal time for online lenders to arrive in Silicon Valley. After the financial crisis of 2008, banks who were the first choice as lenders for everyday people took a little bit of time to comprehend the way in which customers wanted to access credit and they were not ready to take any kind of risks. They failed to focus on the needs and demands of customers and instead they concentrated on capital constraints and other regulations that were proving to be a challenge for them. All these reasons contributed to the emergence of online lenders in the market.
Online Lenders’ Rise To Success
Getting a lot of customers appears to be a comparatively easy task. You can pay a good amount of money to get customers. Also by relaxing the underwriting standards, you may be able to win more customers. The venture capitalists who got attracted by the high and stable growth invested a huge amount of money into online lenders. But you also have to be spot on with the economics of lending and that is the most difficult part. Online lenders rightly judged the way in which customers want money and the most important thing is that they knew what the customers did not want. Customers dislike spending time in a branch with a loan officer to get a loan, they want to avoid any kind of delay in getting the money transferred into their accounts and the thing they hate most is being denied.
Downsides Of Online Lenders
With that said the main problem with online lenders lies with the economics of loans they sanction. Profitability from loans depends on the costs of acquiring a loan, the default rates of those loans and the spread. There is a big disadvantage for online lenders when they start- they have to depend on raising debt or expensive equity. Banks have the option of using inexpensive deposits to fund the loans. Banks are already in an advantageous position due to their reputation, brand identity, and loyal customer base. On the other hand, online lenders need to spend a huge amount of money on attracting new customers. There are many mainstream banks that turn away customers due to issues related to processing and the customers too may not be worthy of credit, online lenders use disparate data through their big data platforms to underwrite the credit risk in ways that common credit scores won?t be able to do. Online lenders developed proprietary algorithms that predict defaults better than a FICO score. They used the same data to attract specific customers in social media as well as dictate the terms of borrowing. That?s precisely why online lenders are able to reach out to customers that traditional banks can?t.
Changes In Bank Lending
Post the crisis, banks reacted quite quickly to the idea that they had to improve on their interaction with customers. Just a few years ago, middle-class customers criticized banks like Goldman Sachs for not offering clear borrowing terms, delaying to transfer money and dealing with them rudely. Nowadays, a lot of Americans are able to connect and interact with their banks using online mobile apps and their loans are sanctioned as quickly as the online lenders do. They are able to get multiple products and services from their respective banks; online money lenders lack this option. Banks also have several data touch points in case of deposit as well as lending products with customers. They are able to create data that online lenders fail to find. So far, the banks, utilizing their traditional underwriting methods continued to accumulate profit in their customer lending divisions and the online lenders continued to face huge losses. For example, JP Morgan makes profits worth billions of dollars and suggest that the US consumers are responsible for this, online lenders are facing a lot of defaults. Online lenders are trying to bring down their losses by developing their proprietary algorithms. The losses are taking place in one of the most congenial credit environments in the contemporary period.
Data For Lenders
For maintaining a level playing field, a group of companies that are new to the market concentrated on assisting large banks and also online lenders to sort through this data to drive value for consumers. There are several companies to offer unique data sets and provide institutions with a compliant and efficient way of finding and validating data, including the traditional sources of data. Banks can apply the insights from data and use it frequently to know their customers and launch new products. Banks can launch lending products that are entirely new by utilizing the data platforms and issue loans in less than 4 months. Companies like PeerIQ allows originators and investors to use both traditional and non-traditional data for analyzing and risk managing their portfolios. Other companies like dv01 help with reporting, data management, and analytics, this makes the lending market much more transparent. Usually, the credit goes to online lenders but these companies which are not that popular have contributed a lot in changing the lending market drastically.
Final Thoughts
To sum it up, we can see that in the battle between banks and online lenders, both have some advantages and disadvantages as mentioned above. In some cases, online lenders have an edge over the banks and in other cases, it is vice-versa. But people tend to ignore the precious role played by big companies that have invested in lending markets for analyzing and managing data. This has really brought a new dimension to lending in recent times. Data can be used by both online lenders and banks to attract new customers and also bring transparency and speed in the process. The software offered by these companies will help you to get insights from complex data and take decisions based on genuine information. The data also helps to fix the borrowing terms and policies. All these points demonstrate that in the battle between banks and online lenders, the ultimate winner is data that has helped in playing a level field between the two. Data has emerged to be the game-changer in the lending market and has also proved to be useful for customers. We hope for further advancements in big data management in near future.
