Do we drive the same type of cars as we did in the late 1950s? Are we using analog mobile phones to dial or send a message? When consumers have benefitted from upgraded technology in the way we commute, communicate, experience movies, listen to books, talk to smart-assistants, order cab or a pizza, how long is it before they voice their demand for an efficient loan process?
Legacy Lending Versus Digital Loans
Access to credit was a tiresome process till the millennials realized, about possibilities of alternative finance options like peer-to-peer lending or crowdsourcing platforms.
Fintech platforms use commercial loan origination software to tap the underprivileged segment of small and medium businesses. But the question is when new platforms can verify the documents of a prospective loan applicant and disburse quick-business loans, why can’t legacy banks with an abundance of economies of scope and scale consider the potential of this market?
There is a stark difference between automated loans and legacy processes used by traditional banks. Legacy banks are big institutions that have been around for decades. Trillions of dollars pass through the payment channels of legacy banks every day. Adopting new systems is challenging and the reason for a risk-averse approach of legacy banks in adopting new technology that can automate the banking functions.
The Future Of Banking – Automation
A feature-rich loan origination system will attract a new generation of banking customers. Although there are options for new players like alternative funding and fintech companies, people still like to bank with a legacy institution if they can embrace game-changing technology.
Three factors are broadly defining and reshaping the future landscape of lending, namely:
1. Efficient technology
Imagine the case of a mid-size furniture shop that crafts vintage furniture that needs to stock up on inventory and is looking for a bridge loan to pay the timber vendor. They have paperwork in order and are eligible for a small business loan at a competitive rate. However, the loan approval will take two weeks, and the vendor will not wait till that period. If the business decides to wait for its legacy bank to approve, it does not serve its purpose. If they forgo the loan, the opportunity-cost risk is detrimental to the growth and operations of the entity.
The above example iterates the need for automation in loan origination and the use of LOS software that completes an end-to-end cycle of loans within a few hours from the initiation.
The following benefits LOS will establish the efficiency of the process:
- Borrowers can fill out applications from multi-channels without walking into a bank
- Information needs to be scanned and uploaded and is paperless
- If data is insufficient, the automation tools create an immediate prompt alert explaining the next step. Chatbots with FAQ clear all relevant doubts at any time of the day
- Once the loan application is completed by the customer, verification of data with third-party API and other web portals is automated. The authenticity of information is checked and the system generates an alert if data is not true.
- After verifying the data for its truth LOS automates the process of credit analysis and underwriting and recommends the credit assessment decision to approve or reject the loan.
The time taken for the loan origination is not weeks but just a few hours. Along with automation, the software is secure and resilient against cyber attacks, works in line with risk and regulatory metrics, and processes loans without errors.
2. Business intelligence
It is more cost-effective to retain existing clients than new acquisitions. But when a bank’s clients have to take decisive steps for a better customer experience, they will not remain loyal based only on a long-standing relationship. Two factors that influence the decision of a borrower when choosing a lender are:
- Easy-application
- Fast approval and disbursal of loan
Traffic has to be driven through innovation and customer-centric solutions if banks don’t want to lose their existing customers and would like to attract new ones simultaneously. With competitive platforms breathing down the necks and customers vying for loans that serve their purpose in time, banks cannot afford to lose further time. Business intelligence insights suggest scaling technology to support automation in banking products.
3. Operational growth
With changing times, any organization is as good as its last feat. If a bank wants to retain its market share and positions in the lending business, then it has to opt for growth drivers that are relevant to the current transformations.
A loan origination software uses cloud-based technology and the latest AI tools to understand the feedback of customers and employees. Leadership can work on the feedback and develop products that are easy to access and customer-focused.
A LOS reduces the time taken to process loans, gains the confidence and trust of customers who will bank again with the institution, and help employees focus on elevating their roles through client engagement. As the number of loans processed through automation increases without broadening risks, the growth and profitability scale new highs.
Closing Note–
To stay relevant and enjoy the market share of the lending business banks and lending companies have to automate their loan origination process. It is not the case of ‘if’ but ‘when’ banks embrace technology to stay ahead of the race or be left out as an institution that once existed.
Change is constant and a good thing for business and economic growth. The merits of a legacy bank challenging its biases and accepting new changes can be a smooth affair if deliberated properly. A phased roll-out helps the organization streamline the process and start working on new systems within a short time.
A loan origination software is developed to integrate with the existing system within a short time and will accommodate customizations. As a large share of customer touchpoints will be through digital channels, lenders will have access to a large pool of situational data. Inference of customer insights through logic and semantics can help enablers preempt what customers are looking for in the future.
