AI-driven solutions are changing consumer expectations across industries. Consumers looking for loans are also looking for the speed and efficiency that they experience with other verticals like online shopping or ordering a cab. With social media, consumers are aware of the possibilities of AI-driven business models. So when they come across pioneers of change offering easy-documentations and quick turnaround time as features of loan products, they will sign up for one.
The banking and lending industry is rich when it comes to consumer data and insights. Given the volume of applications they receive for new accounts, loans, or other banking products, they have a rich mine of data. Using AI and ML, few banks and most fintech companies are changing the landscape of lending business with the help of a digital lending platform.
Using machine learning banks can get a competitive advantage over other major players if they learn to process these business insights to add value and increase revenue. Let us look at why and how digital loan software that depends on artificial intelligence and machine learning gives an edge to lenders:
Unbiased without human intervention
Legacy lending involves tons of paperwork that needs to be processed manually. It is time-consuming and highly dependent on human intervention. As a result, both the speed and results were impacted, giving rise to biased credit decisions and approvals. The underwriting process is limited to the employee’s perspective and is prone to be either approved or rejected. Often higher/lower interest rates are applied to certain loans. These practices led to dissatisfied customers and losses for the lender.
Contrary to legacy banking, machines apply algorithms to search for data integration and populate the results transparently and efficiently without any bias. There are no human emotions involved and a seemingly nice family business that has goodwill but ill-managed cash flows will not get its loan approved just because they have a long-standing with the bank. Since the credit decision report is transparent such applications will get recommendations about the areas they need to work on before reapplying for a loan.
Consumer awareness demands change
In the last fifteen years, the access to information is fast and the number of users accessing the internet to search for information is only increasing by the day. Every individual who is good at something is showcasing their skill. If patisserie chefs can woo customers through blogs and vlogs, so are fintech blogs and financial enthusiasts writing about innovative products that include content about AI-driven automated loan products. This awareness is creating a demand for loans that have hassle-free document submission that can be processed just by scanning the documents using a smartphone and uploading them. As data is verified through API integration, credit decision, and loan disbursal are also expedited through automation, and the preference for quick loans is increasing.
Legacy banking’s barriers of opacity and lengthy loan origination process is an inconvenience that borrowers are not willing to endure in the future. They have alternative options offered by fintech companies and other early players who realized the potential of AI early on. Most times the old lending system also approves and declines to lend for wrongful reasons. In such cases, often the consumers feel deluded and dump their business with the entity. The estimated opportunity loss cost of such transactions to the lending industry is often in the billions.
Competition is gearing up
The rise in fresh entrants in the lending business will keep legacy banks in a vulnerable state if they don’t pull up their act and go digital pronto. Fintech companies have focussed on the loan-seeking SME community that has been long neglected by banks and other big lending institutions. Fintech eliminated the roadblocks that made small business loans a difficult proposition earlier by understanding their needs and requirements. Small businesses find it difficult to understand their book-keeping, human resource management, and audit requirements that are essential for their business growth. As a result, despite good turnovers, SMEs find it difficult to hold on to positive cash flow or track their overheads.
Fintech companies have been able to resolve these issues by working with SMEs to address these issues by providing business support services for a small fee. As a result, small businesses are making a comeback with structured financial statements and can professionally manage their units. Their lending requirements are not just met but overseen in a way that is a win-win situation for both the lender and the borrower.
Digitize for standalone merit
Even if a bank is not worried about gaining dominance over other players or the consumer’s changing expectations it should digitize its lending operations and other banking services just for the sheer benefits that come with automation. Digital business is increasingly seen as the most compelling and practical way to scale as the acceptance of digital business is its prime. This is an opportunity that should not be missed as digital banking offers a single-stand platform that can be integrated with all the channels of service like POS, Web portals, and apps. Through multi-faceted channels, banks can extend their loan products and engage new borrowers.
The innumerable benefits of automation, considering that the potential of AI-driven solutions is still at a nascent stage of this disruptive revolution, should be the primary reason to transition to digital LOS.
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Conclusion:
Technological innovation has varied benefits that cannot be ignored for the growth and retention of business. New businesses can be developed using the biggest data pool of consumer information that banks have through meaningful insights generated through ML and serve customers what they need. To understand what a customer needs, banks need not employ an army of analysts. Machine learning through its neural networking can process all the information in one go. In this manner, strategic business models can be developed that are a radical disruption by offering products that address the needs of the consumer and gauge the pattern to improvise their products even as the consumer expectations start changing.
