Technology has significantly changed the lending industry over the last decade, and the process doesn't seem to stop soon. We don't know what banking will look like in ten years, but at least we know which trends are here to stay this year and beyond. Some of them are already widely used by banks and lending services. Some have only started to appear recently. But all of them mark the era of total digitalization of the lending industry.
Smaller loans
We expect the lending market to become more inclusive, with lending companies offering young adults with little to no credit history to
Blockchain technologies
Blockchain, which mainly revolved around cryptocurrencies, is now changing things in finances and making many processes more efficient and secure. It also decreases the amount of bureaucracy involved, which is another trend in every industry — Gen Z is not here to tolerate excessive formalities. What blockchain can do in the lending business is to help:
- Connect borrowers and lenders
- Increase the speed of the loan approval process
- Provide real-time transactions data
- Give borrowers more control over their loans
- Track and manage installments
And, of course, a vital advantage of blockchain technologies is the security of borrower-lender communication. We've never been able to keep the clients' personal and financial information as safe as we can do now with blockchain.
Rapid digitalization
The digitalization of lending processes started anew in 2020 with the outbreak of COVID-19, and it's here to last, gradually turning most of the lending processes into digital ones. We can already observe the decrease in physical distribution points and the quick rise in the number of private lenders accessible online by filling out a simple application form.
Mobile apps and convenient websites aside, there is also a more state-of-the-art technology such as optical character recognition. OCR is among the most promising technologies for lenders today as it can significantly decrease the amount of manual work while increasing the precision of data recognition.
We're talking about parsing all the relevant data from various documents coming into lenders' hands, whether these are loan applications, account statements, document scans, or else. While it was previously done manually by bank employees, taking a lot of time and effort, digital solutions can now pull out the relevant data automatically and sort it out.
Self-service lending
The digitalization of lending services might eliminate the very need for in-person communication. Today, potential borrowers can go through every stage of getting a loan, from sending an application to getting the money on their account, without leaving their homes and speaking with anyone.
Soon, we'll see the introduction of interactive chatbots that users can consult on various topics, including complex issues. We can also expect the spread of omnichannel communication, i.e., a possibility for the customer to use any communication channel they want, including social media, text messages, mobile apps, etc.
Integrative microservices
Classical loan management involves a lot of paperwork, with a massive amount of time spent verifying those papers manually. While automation of such processes is possible, replacing the legacy systems with new digital solutions might be pricey and take a long time.
And this is where another trend comes — the use of integrative microservices that allow lenders to digitize one step at a time by modules that they need most. Besides, such an approach enables companies to stay flexible and quickly adapt to regulatory changes, which are frequent in the financial industry.
Credit scoring systems
Conventional credit scoring systems used by traditional banks do not work that well for smaller lending enterprises. Modern financial technologies can provide alternative scoring systems which will use not only bank details but also data-driven models, including:
- Personal information, such as age, sex, name, and contact details
- Behavioral data, such as spending patterns
- Business information such as POS transactions, bank statements, and cash flows.
That way, lenders will get more information about potential borrowers than just a traditional credit score. At the same time, borrowers can expect more accurate loan approval decisions made in a shorter time.
Artificial intelligence
The list won't be complete if we don't mention an increased use of machine learning at every stage of the lending process. Below are the ways in which AI can help both lenders and borrowers:
- Assessment of the borrower's solvency. Analyzing the entire digital footprint of a potential customer can help predict repayment. The accuracy of machine assessment is higher than that of manual evaluation done by a bank employee.
- Better marketing. As AI can help us get more data about people applying for loans, it allows marketing specialists to create personalized offers and deliver them directly to potential borrowers.
- Fraud prevention. AI algorithms can detect suspicious transactions and prevent credit card fraud and other cybercrimes. They can also help customers detect suspicious emails and fraudulent ads.
Similar to other technologies mentioned in this article, artificial intelligence will help automate the processes previously done manually, increase their efficiency, and make them more convenient for both sides.