Big data has transformed businesses in every industry. Banks now use data acquired from nearly every step of the loan origination process. The reward: Detailed insight that can be applied to continuously improve lending efficiency and profitability.
With the wealth of loan origination data, banks are looking for efficient methods to analyze these data and deliver that insight to lending professionals with the goal of continuous process and portfolio performance improvement. A modern loan origination solution with natively-integrated loan analytics software can be ideal to address those needs.
Benefits of Loan Analytics Software for the Banking Industry
No Need for a Data Scientist
The analytics approach of a modern loan origination solution brings immediate benefits to lenders in two ways. First, with analytics natively-integrated with the loan origination process, there’s no need to spend time and money on custom integration of analytical tools. Second—and this is particularly beneficial for small- to medium-sized banks—there’s no need to have a data scientist on staff or work with consultants to create the specific analytic reports required. Let’s review some examples that show the value of integrated loan analytics software and how it improves both the lending process and profitability.
Identify Areas of Lending Process Inefficiency
With integrated loan analytics software, banks can identify areas of lending process inefficiency using quantifiable metrics, determine the underlying causes, and make process and policy changes that eliminate the inefficiencies. Integrated analytics also enables a detailed understanding of loan applications received and the lending decisions made, identifying historical and emerging trends. By effortlessly capturing process information, banks can quickly analyze the associated data to monitor trends over time and continually make process improvements, staying competitive in any lending environment.
Of all bank lending functions, the loan origination process may be the most critical, as decision speed affects the ability to capture a loan, and decision quality affects overall loan portfolio performance. Out-of-the-box, integrated loan analytics software let banks:
- Compare performance metrics week to week, month to month, quarter to quarter, or year over year;
- Evaluate average underwriter turnaround times, using the time between application submission and the first significant underwriting decision, such as approval, conditional approval, or decline;
- Track the frequency overrides by underwriter to determine if any of these decisions increase lending risk or demonstrate savvy decision skills;
- Monitor auto-decline and auto-approval ratios based on credit scores, origination or any other borrower attributes of interest; and
- Summarize weekly capture, book-to-look, and approval ratios.
Below average underwriter turnaround times may correlate with their experience or the complexity of applications being reviewed. With that insight, improvements could be made with better training. A noted increase in capture ratios may be the result of overrides or exceptions that are increasing portfolio risk. Well-reasoned modifications to credit policies can bring about a greater number of auto-approvals, resulting in increased capture rates and reduced loan processing costs. Only with regular reporting and comparison of performance metrics can banks hope to achieve lending efficiency gains.
Assesses Portfolio Profitability
In the current lending climate influenced daily by demographic trends, politics, global economics, and disruptive technologies, banks must be mindful of subtle trends and respond by fine-tuning credit policies to maximize profitability. Analytics provides detailed reporting on lending decisions—trends and individual loans—that ultimately determine a bank’s profitability.
A representative sample of the range of analyses that can be conducted out of the box include:
- Reporting portfolio averages such as APR, term, debt-to-income, payment-to-income, and amount financed; and
- For auto loans, reporting detailed metrics such as loans booked by vehicle type, vehicle average mileage, average term, and credit tier.
Regular analyses let banks monitor these metrics over time, providing insight into past credit policies and their effect on current portfolio performance. With the ability to examine performance at this level of detail, banks can continuously fine-tune credit policies to improve capture ratios, reduce lending risk, and improve overall portfolio profitability.
It’s All About Process and Portfolio Performance
We’ve provided only a handful of analytical examples, but the wide applicability of loan analytics software and real-time reporting can reveal insight into every facet of the loan origination process. With configuration menus, knowledgeable banking employees can easily create dashboards and reports that provide timely analyses relevant to their specific areas of interest—all without a data scientist. Banks can now implement regular analyses and reports to ensure optimum loan origination processes, lending decisioning, and portfolio performance.
defi SOLUTIONS’ loan origination and loan analytics software experts welcome the opportunity to discuss how analytics can improve your lending process and loan portfolio performance. Take the first step toward greater efficiency and profitability by contacting our team today or registering for a demo of defi LOS.
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