“As retail banks gradually digitalize their activities, much of the lending arena, with the exception of credit cards, has taken a back seat.” As a result, many new fintech competitors have arisen to take advantage of the opportunity and optimize digital lending processes. Increased competition and the loss of revenue due to changing regulations and technologies are forcing banks to shift their focus towards how they digitally process loans.
A “sluggish pace of modernization leaves banks vulnerable as lending comprises more than one-third of retail bank revenue.” Thus, automating lending procedures and improving digital processes for marketing, selling and servicing loans, to individuals, corporations, and businesses is increasingly becoming an important topic for banks.
One interesting sub-sector development within the lending sphere is the emergence of instant loans. As you might be able to tell from the name, instant loans are loans that are essentially approved or rejected pretty much instantly. Traditionally, it has been rather difficult for certain subsets of the market to have access to quickly approved loans. Due to different risk factors, banks routinely took a long time to approve loans for customers with untraditional risk markers.
For certain customers, such as small and medium-sized enterprises (SMEs), long wait times for loans were catastrophic and potentially even deadly. Post-2008 financial crisis, there has been a strong regulatory shift to help small businesses get back on their feet. Part of this has been ensuring that they have better access to loans. In response to these economic pressures, new technologies have emerged that significantly speed up the approval process of loans.
In response to these economic pressures, new technologies have emerged that significantly speed up the approval process of loans.
How Does Instant Lending Work?
Well, thanks to the emergence of machine learning capabilities, “automated decision engines use data and rules to optimize business decisions, adjusting as new information emerges. These tools work best for decisions that need to be made frequently and rapidly with information that is available electronically. Automated, real-time decision making can help a company test and learn from new customer experience efforts, with less human intervention… Banks [then] use these tools to make faster credit decisions, a repetitive process that relies on uniform criteria and available consumer credit data.”
Thus, computers are able to take a specific set of criteria and make a decision about the validity of a loan’s risk profile, all without the need for human intervention. This allows decisions to be made in a matter of minutes as opposed to weeks or even months.
On the one hand, some banks have been trying to change their old legacy system processes to speed up loan waiting times. However, it is far more common that much smaller and more flexible startups are able to develop and offer effective solutions, either directly to consumers (B2C) or to banks (B2B) who then offer the instant lending solutions to their customers. One very well-known real-life example of this type of innovation and cooperation is the Kabbage and ING collaboration.
A Real-Life Example of Instant Lending: The Kabbage and ING Collaboration
The partnership between ING and Kabbage is threefold.
Firstly, ING is in charge of managing and running the whole process, from initiating and issuing the loan to keeping the loans on its balance sheet. They also remain the point of contact for the customer should there be any issues.
Secondly, Kabbage runs the instant loan part of the transaction. “Using the Kabbage platform, clients can get approval for a loan up to EUR 100,000 within 10 minutes.”
Lastly, “key aspects of the offering have been farmed out to third-party firms, including digital onboarding from VI Company and e-signatures for legal approvals from InfoCert,” as well as disbursements by Ginger.
The collaboration between these various players is a great example of how B2B and B2C companies are working together to provide innovative solutions to old problems for consumers. “This [process] reflects the way ING believes collaboration should look: select the specialists that can help you develop the solution the customer is really waiting for.”
As the fintech ecosystem continues to develop and respond to the market, more and more creative solutions are being designed to respond to old problems. Specifically, within the sphere of lending, the development of more accurate machine learning systems is digitally transforming how financial risk is evaluated. Within this, instant lending is increasingly becoming a solution of interest to banks and merchants.
While there has been some progress in improving lending processes in particular with personal and credit loans, many more complex types of loans, such as mortgages and small business loans, continue to lack digital solutions. Learning from successful case studies such as the collaboration between ING and Kabbage, is what is going to lead major financial institutions into the digital future!