How Big Data Can Improve Transparency For Commercial Lending

Technology has played an essential role in promoting transparency for most businesses, especially for commercial lenders. In the past, lending institutions used the ‘high-touch’ method, which involved personal attention and service by lending institutions to assess the credit capacity of low-income earners.

In this article, we will be looking specifically at the introduction and impact of big data on commercial lending. Here’s what you need to know about its role for lending companies.

Role of big data for lending companies

For lenders, accuracy and predictability are all crucial to success. The ability to predict when the borrower is able to repay is a critical determinant of whether or not the business will be a success. At the heart of gauging the strength of the borrower is through big data.

Traditionally, lenders gauge the strength of the borrower on their credit score and other financial factors such as their income and any other existing debt. While the traditional method still works in some cases, lenders feel that the conventional way may be short-sighted. Most lenders are now reaching beyond the usual restricted methods, and relying more on data before borrowing.

Here are some of the key features of big data for commercial lending.

1. Big data speeds up the loan application process

Many people take up payday loans occasionally as a quick cash solution. For them, the cumbersome loan approval process and long waiting time can prove to be costly. This is where big data can prove beneficial, as it uses methods like algorithms and advanced scoring, which is able to quickly acknowledge the borrower’s actual risks.

This speeds up the loan application process as those that require a short term loan will be able to receive it without going through a complicated hassle. As the big data scoring is cloud-based, many lending and insurance companies have begun to use it for their loan processes as they can easily access the stored information.

2. Operation optimisation

Big data improves the predictive power and the response of the system, which provides more extensive risk coverage for its clients. As the system is automated, the operation costs are also significantly reduced. Some of the critical areas where big data adds value to commercial banks and licensed moneylenders include credit management, operational risk, market, industrial loans and integrated risk management. Big data can provide companies with a global vision in areas related to financial risk.

3. Lenders enjoy better insights

While we are still miles away from achieving the perfect system, big data is slowly pushing us in the right direction. Big data continues to help licensed moneylenders receive more crucial information about their customers to make the best decisions.

The biggest worry for any licensed moneylender is when the borrower fails to pay back the loan. With big data, it can help licensed moneylenders identify whether a customer is creditworthy and if they are able to make repayments on time.

4. Employee engagement

Another significant impact of big data on commercial banks and licensed moneylenders have to do with the employee experience. When done right, the system can help track and analyse employee performance metrics. Through this system, the company can identify and acknowledge not only the top performers but also underperforming workers. Using such a system is accurate as all the information is based on real data and not human memory.


Big data is all about gaining insights into your company to make accurate decisions and reduce overall risks, which is beneficial for lending companies. By aligning big data into their systems, commercial banks or lending companies will be able to inject analytics expertise into their business for maximum benefits. Companies will also be able to obtain a better grasp of running day-to-day operations and improve their relations with their customers. The company’s service to their customers will also be timely and accurate.

Thus, the sooner commercial banks and licensed moneylenders can incorporate big data into their systems, the better it will be for themselves and their customers.

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