Loan operations are an integral part of the revenue for a banking system. It’s imperative that organizations dedicate sufficient time to improve this aspect of the operation. By taking advantage of new technologies, fintech companies are helping improve lending and operational efficiency in the banking sector. Loans operations include all the processes involved between the submission of a loan application and the disbursement after approval. It often involves:
- application processing
The goal of these processes is to evaluate the risk level (credit worthiness) of a customer who has applied for a loan in order to make quality decisions as regards approval or denial of the application. However, the lending process for many banks is surprisingly prolonged – especially given the current state of technology. Even with banking startups springing up left and right, offering mobile deposits and internet-based experience, the world of retail lending hasn’t caught up quite as quick.
Today’s borrowers want a loan decision process that is quick, accurate and comes with as little risks as possible. If a bank’s lending process fails in one of those elements, they lose out on more potential customers. Banks can implement OKRs to evaluate their ability to provide quick, low-risk loans to borrowers. Effectiveness in this regard can be evaluated with the following metrics, which can be used as KPIs in your key results:
- Unit Cost of Indirect Loan Application: This is the division of the total cost of processing indirect loan applications by the total number of indirect loan applications processed over a particular period of time.
- Consumer Lending Employee Headcount Ratio: This is derived through the division of the number of company-wide employees by the total number of consumer lending employees (loan officers, underwriters/credit operations, loan processors).
- Average Mortgage Loan Value: The average value (in dollars) of a mortgage in the bank’s loan portfolio over a certain period of time.
Loan Process Improvement Ideas For Bank Lending Optimization
Using OKRs, financial services and bank employees can optimize their lending process. Below are some methods for improving loan operations in a financial institution:
Set Targets For Improvement
According to Timothy Reimink of Crowe LLP, a consulting firm for financial institutions, the most important strategy for improvement is the desire to improve. If you don’t see any reason for change, you will not be able to take any significant steps towards improvement. To improve its loan operations, a bank should set specific targets for improvement. For example, a bank can decide to work on processing customer loan applications faster. If the average period for processing mortgage loans has been two weeks, the bank can set a target of making it a week. This increased efficiency will help customers get quicker responses and help customers who get denied make the necessary steps on time. This method is a great way to think about what your organization’s objectives are when you begin to develop your OKRs and think about what really needs to be improved.
Optimize Every Channel
We recommend you always take the time to evaluate the different channels through which customers interact with the bank, whether it be in person or digital. Customers’ channel preferences change and you have to be ready to respond to them effectively regardless of their preference. You should also take advantage of new metrics for the analysis of your branch performance and value. Making sure that you reach the customer in the most convenient way possible will help contribute to a successful customer experience, which will only contribute to your organization’s success.
Business Realignment requires you to take stock of your loan operations from time to time. You have to think about ways you can abandon or improve redundant methods of going about your operations. Move to business lines that are more effective and cheaper instead of getting stuck with business lines that have low margins. Leading banks have a culture of approaching things deliberately and strategically that makes them stand out among competitors. This might mean you have to make some investments and spend money, but it will certainly be with it in the end.
In a hyper-competitive market place, one of the most important predictors of lender performance is time-to-funding. This is the time between an application’s submission and access to funds. Consumers would go for convenience and speed over price any day – even when it comes to their finances. The 2018 PACE Insights report reveals that customers are frustrated with a slow application review process, and their top three criteria for choosing a lender are reliability, speed, and convenience.
That is why many lenders strive to deliver instant approvals and 1-day transfers. They are training borrowers to expect quick action with every application. With several digital lenders promising 1-day and 2-day time-to-funding in their advertising headlines, how can your bank adjust to this new norm?
You could throw more people at the problem, but more hands won’t speed up the process. The only way to catch up with the pace is to automate your lending process with technology platforms, automated systems software, and advanced credit scoring software.
Understanding that speed and ease are priorities for the customer, it’s important for employees to emphasize the importance of automated lending and make any necessary adjustments to their current system. By including automation as a key result on one of your OKRs with an objective to “Improve Loan Automation”, the bank will show signs of understanding the importance of the customer’s needs, which is crucial to your bank’s success.
Replace Paper With Digital Document
The auto loan application is still a paper-heavy, protracted process that has several inherent problems. Some of them are delivery delays, the cost of copying and sending documents, and lost or incomplete paperwork. The use of lending software made available via cloud-based services provides digital documents in the form of electronic forms or PDFs that would capture applicant information. The automated steps easily guide the applicant through the data entry process, verifying data as it is entered, and notifying the user in the event of an error.
By replacing paper with digital documents, your banks will get to:
- Accurately process a great number of applications
- Avoid potentially losing documents as they are secure and accessible online by both your bank and the applicant
- Receive documents within hours or even minutes instead of days
- Meet compliance and retention requirements without the need for voluminous paper storage
The Use of Analytics to Analyze Lending Process and Portfolio Performance
Lenders have overwhelmingly large volumes of process and portfolio data; however, legacy lending systems makes it difficult to apply modern analytics. Modern lending systems use analytics to gain insight into process efficiency throughout all phases of the loan lifecycle, as well as garner a greater understanding of the factors affecting portfolio performance. With the use of analytics specifically tailored to their business needs, banks can:
- Identify process steps that are needlessly complex or time-consuming
- Determine which consumer or economic factors contributes to defaults
- Monitor productivity trends using historical metrics
- Compare portfolio segments to identify risk, opportunity and underlying factors
Having a complete understanding of how you can improve your loan operations allows you to evaluate what changes need to be changed within your own organization. After you’ve determined what’s most important to focus on, you can use these improvement tips to construct an OKR that will help put you on the path to success. For instance,
- KR1: Reduce loan decision cycle time from 10 business days to 2 business days
- KR2: Complete integration of automated loan application process
- KR3: Complete the testing of the newly developed loan decision engine on all applications for the past 3 years.
Objective: Improve loan operations
Banks jump into automation with a pinch of salt. To establish correctness, automation models have to be double-checked and so it is best to test models on past decisions. Based on the outcome of the test, the automated engine based on data-driven assessments and a structured credit “decisioning” framework was better at predicting default risk than the subjective human assessments had been—and far more consistent, which was a key factor in approving the model for use in new cases.
The goal of improving your organization’s loan operations is to ultimately deliver a great customer experience. For that reason, the OKR mentioned above could align with a corporate OKR to “Improve the Brand’s Reputation” or to “Improve Customer Experience.”