How data technologies are reshaping the consumer credit landscape

AI, cloud-services and big data are making banking more accessible for customers and creditors


The financial services industry is riding high on the digital wave as it has transformed from a traditional paper-based loan system to completely online discourse. This has been made possible with the advent of innovative technologies and growing interest of consumers toward the internet. Technology providers are quick to collaborate with financial institutions or banks to offer them smart solutions for carrying out lending services besides other facilities. Banks and non-banking institutions are even more willing to leverage technology to improve their offerings. Automated banking interface and other digital lending solutions have become customer-centric providing them with end-to-end solutions.

All of this has been possible with the deployment of technologies such as big data, cloud and AI. Modern credit systems are powered by specific alternative credit scoring algorithms have disrupted the lending scenario. Moreover, the perennial issues of information symmetry have been particularly taken care of. On the other hand, changing data usage policies make it more difficult for banks to make informed decisions.

Cloud-based loan origination

Cloud-based services do more for banks than just provide security by moving away from legacy systems. With the advent of the reliable internet network, the loan application process is moving from a manual process to cloud-based service. This process is also called digital loan origination, whereby a loan origination software needs to be installed by the financial institution. Through this software, banks can securely perform high-volume banking activities at a faster pace and can deal with customers on a daily basis smoothly.

Its universal applicability provides several benefits to the applicants. One of the key benefits is that it lowers cost by allowing lenders to install the loan origination software without having to invest in any specific information technology software. It also eliminates the need for incurring overhead costs such as electricity charges and systems administration. Automation enables a faster loan processing system which offers a competitive advantage for a lender. Further, the web-based user interface allows bank employees to access the platform from virtually any location.

Artificial intelligence

A report by Autonomous projects industry savings totalling  $1 trillion by 2030 due to the increase in the role of AI in the industry. These savings are not only resultant from cuts to staffing costs. Through AI, financial institutions can unleash the untapped potential of their core business. The machine-based neutral networks enable the banker to read through the humongous amount of data and comprehend the same into actionable insights.

For instance, while taking a mortgage loan an applicant is generally accessed with respect to its credit history, property owned, income generated, besides other insurance and tax information. This involves manually skimming through numerous transactions. This is where AI chips in, by collecting data and automatically updating the same. Through a programmable algorithm, essential parameters can be monitored faster and to a higher degree of accuracy before approving a mortgage.

Another area where AI could significantly improve lending services is by enabling alternative credit scoring strategy. A Singapore-based startup LenddoEFL is leveraging AI to analyze alternative data points to understand if the borrower will be able to repay loans. Instead of the conventional way of determining a credit score, alternative credit scoring uses data such as behavioral traits (based on how one writes the subject of an email) and smartphone usage habits to build models of creditworthiness of customers.

Though unconventional, AI helps responsible borrowers who lack a credit history to secure loans by sorting those data points that can be relatable to financial responsibility. According to Automation Anywhere, AI-assisted processes can improve productivity in the industry by 20%.

Big data

In traditional banking, client servicing has never been a strength. Standardized services were provided to all customers irrespective of their actual needs or preferences. Lenders have to go to individual banks and file applications to get loans approved. This is where big data has stepped in: By analyzing a large amount of data which historically had never been of interest to banks. Now, with the analytical services offered by big data platforms, financial institutions are able to provide customized financial solutions to each customer without great expense – a crucial metric when 80% of potential customers prefer to work with businesses that offer personalized experiences, but only 6% of banks self-profess to offer advanced personalization solutions to consumers' problems.

At the same time, platforms have been developed which provide one-stop information about all types of loans available with their respective interest rates, simplifying the entire process for customer and business alike.

Clearing the asymmetry

Earlier, information asymmetry was quite evident as financial institutions failed to assess and monitor each and every aspect of the client or borrower. In such cases, skepticism looms in case a borrower turns bankrupt. Also, there is more to a borrower than just his/her creditworthiness. Creditors do not always have a 360-degree view of the borrowers and there are other aspects about a borrower that is somewhat hidden. For a banker to understand these aspects, the aforementioned technologies have helped a lot. The perennial issues of information asymmetry are somewhat eliminated. Machine learning, neural networks and bid data are enabling the banking companies to get a deeper insight into the lending landscape.

Customers becoming master of data

While the technological changes that are happening are noteworthy, a paradigm shift is taking place. Consumers are becoming the master of their data and fully control who, when and how their financial and personal data can be accessed. One consequence is that it is more difficult for banks to make informed decision about their customers, because their access to vital data is limited. To solve this, regulatory reforms such as the Open Banking introduced by the United Kingdom have to be replicated in the US. These regulations mandate the banks to release the data in a secure manner and also allows the customers to control their access: Customers retain control over their data, but they can opt to provide their data to secure better credit deals or voluntarily allow third parties to use the data in new applications and products.

How can marketers achieve 11 multichannel marketing small

Read next:

How can marketers achieve 1:1 multi-channel marketing?