What Are the Top 7 KPIs for a Mortgage Lender Business?

As a small business owner or artisan, understanding the key performance indicators (KPIs) specific to the mortgage lending industry is crucial for gaining insights into marketplace performance. In today's competitive market, having a clear grasp of these KPIs can make all the difference in driving growth and success. This blog post will delve into seven industry-specific KPIs that are essential for mortgage lenders, offering unique insights and actionable strategies for optimizing performance in the ever-evolving marketplace. Whether you're a seasoned lender or just starting out, this comprehensive guide will provide valuable information to help you make data-driven decisions and achieve your business goals.

Loan Application Volume

Definition

Loan application volume is a key performance indicator that measures the number of mortgage loan applications submitted to HomeTrust Mortgage Partners within a specific period. This KPI is critical to measure as it provides valuable insight into the demand for mortgage lending services and the overall health of the business. By tracking the loan application volume, the company can assess market trends, identify potential opportunities, and make informed decisions about resource allocation and business strategy.

How To Calculate

The formula for calculating loan application volume is straightforward. Simply count the total number of mortgage loan applications received within a given timeframe. This can be on a daily, weekly, monthly, or annual basis, depending on the business's reporting needs. By tracking this metric over time, HomeTrust Mortgage Partners can gain a comprehensive understanding of the ebb and flow of loan applications and make data-driven decisions.

Example

For example, if HomeTrust Mortgage Partners receives 150 mortgage loan applications in a single month, the loan application volume for that month would be 150. By consistently tracking this metric, the company can identify seasonal trends, marketing campaign effectiveness, or shifts in the competitive landscape.

Benefits and Limitations

One of the primary benefits of tracking loan application volume is the ability to gauge market demand and identify potential growth opportunities. However, a limitation of this KPI is that it does not provide insight into the quality of the loan applications received. Therefore, additional KPIs may be needed to assess the overall health of the mortgage lending business.

Industry Benchmarks

According to industry benchmarks, the average loan application volume for mortgage lenders in the US is approximately 1,500 applications per month. However, top-performing mortgage lenders can receive upwards of 3,000 applications per month, indicating a high level of market demand and strong brand presence.

Tips and Tricks

• Invest in targeted marketing campaigns to drive loan application volume
• Streamline the application process to encourage higher volumes
• Monitor industry trends to adjust loan application volume goals accordingly
• Implement customer referral programs to generate new loan applications

Approval to Close Time

Definition

Approval to Close Time is a key performance indicator that measures the average time it takes for a mortgage lender to process and approve a loan application from the initial submission to the final closing. This KPI is critical to measure because it directly impacts customer satisfaction, operational efficiency, and overall business performance. The ability to efficiently close loans not only improves the borrower experience but also affects the lender's ability to generate revenue and maintain a competitive edge in the market.

How To Calculate

The formula for calculating Approval to Close Time involves determining the average number of days from the receipt of the loan application to the final approval and closing. This includes the time spent on underwriting, processing, and any other necessary steps in the loan origination process. By adding up the total number of days for each loan and dividing it by the total number of loans, the average Approval to Close Time can be calculated.

Example

For example, if a mortgage lender processed 10 loan applications with the following number of days from submission to closing: 25, 30, 40, 20, 35, 28, 42, 50, 45, and 22, the total number of days would be 337. Dividing this by 10 (the total number of loans) results in an average Approval to Close Time of 33.7 days.

Benefits and Limitations

The benefit of measuring Approval to Close Time is that it allows the lender to identify bottlenecks in the loan origination process and implement strategies to improve efficiency. However, a limitation of this KPI is that it may not account for external factors such as regulatory requirements or market conditions that could impact the approval timeline.

Industry Benchmarks

According to industry benchmarks within the US context, the average Approval to Close Time for mortgage lenders is approximately 45-60 days. A highly efficient lender may aim for an average Approval to Close Time of 30-45 days, while exceptional performance may be reflected in an average Approval to Close Time of under 30 days.

Tips and Tricks

• Implement automation and digital tools to streamline the loan processing and underwriting
• Establish clear and efficient communication channels between internal teams and with borrowers
• Regularly review and optimize the loan origination process to eliminate unnecessary delays
• Invest in training and development for staff to enhance skills and expertise in loan processing

Customer Satisfaction Score

Definition

The Customer Satisfaction Score (CSS) is a key performance indicator that measures how satisfied customers are with the services provided by HomeTrust Mortgage Partners. This KPI ratio is critical to measure as it directly correlates to the success and sustainability of the business. By monitoring customer satisfaction, the company can identify areas for improvement, strengthen client relationships, and ultimately drive repeat business and referrals. It also provides insight into the overall customer experience, which is crucial for maintaining a positive brand reputation and competitive edge in the market.

How To Calculate

The Customer Satisfaction Score is typically calculated through customer surveys or feedback forms that inquire about overall satisfaction with the mortgage lending experience. The formula for CSS involves aggregating responses and calculating an average satisfaction rating, which can then be translated into a percentage or numeric score to represent overall customer satisfaction.

Example

For example, if HomeTrust Mortgage Partners receives 100 customer responses with an average satisfaction rating of 4.5 out of 5, the calculation of the Customer Satisfaction Score would be as follows: CSS = (450/100) * 100 = 90%. This means that the company has achieved a high level of customer satisfaction based on the feedback received.

Benefits and Limitations

The primary benefit of monitoring the Customer Satisfaction Score is that it provides valuable insight into customer perceptions and preferences, allowing the company to address any issues and continually improve the quality of service. However, it is important to note that customer surveys may not always capture the complete spectrum of customer experiences and sentiments, and therefore the CSS should be complemented with other customer feedback mechanisms to ensure a holistic understanding of satisfaction levels.

Industry Benchmarks

According to industry benchmarks, the average Customer Satisfaction Score for mortgage lenders in the US typically ranges between 85% to 90%. This indicates that a CSS above 90% would be considered above-average performance, while exceptional satisfaction would be represented by a score of 95% or higher.

Tips and Tricks

• Regularly solicit customer feedback through surveys and review platforms to gauge satisfaction levels.
• Implement a client-centric approach by providing personalized support and guidance throughout the mortgage lending process.
• Address any negative feedback or concerns promptly and transparently to demonstrate commitment to customer satisfaction.
• Leverage positive customer testimonials and reviews to showcase the company's dedication to client satisfaction.

Pre-Approval Conversion Rate

Definition

The pre-approval conversion rate is a key performance indicator that measures the percentage of pre-approved mortgage applications that result in actual closed loans. This ratio is critical to measure as it provides insight into the effectiveness of the pre-approval process in converting potential leads into actual business. In the context of mortgage lending, the pre-approval conversion rate is important as it directly impacts the overall loan origination volume and revenue generation. A high pre-approval conversion rate indicates a successful and efficient pre-approval process, which can contribute to improved business performance by increasing the number of closed loans and revenue. Conversely, a low pre-approval conversion rate may indicate inefficiencies in the pre-approval process, leading to missed opportunities and reduced business performance.

How To Calculate

The formula for calculating the pre-approval conversion rate is: To calculate the pre-approval conversion rate, you need to determine the total number of pre-approved applications that have resulted in closed loans and divide it by the total number of pre-approved applications. Multiply the result by 100 to express the ratio as a percentage.

Example

For example, if a mortgage lender processed 200 pre-approved applications and 140 of them resulted in closed loans, the pre-approval conversion rate would be: Pre-Approval Conversion Rate = (140 / 200) x 100 Pre-Approval Conversion Rate = 70%

Benefits and Limitations

The advantage of measuring the pre-approval conversion rate is that it allows mortgage lenders to assess the effectiveness of their pre-approval process in converting leads into closed loans. By identifying areas of improvement, lenders can optimize their pre-approval process to increase conversion rates and generate more business. However, it's important to note that the pre-approval conversion rate does not take into account the quality of the loans originated, and a high conversion rate does not necessarily indicate the profitability of the closed loans.

Industry Benchmarks

In the US mortgage lending industry, the typical pre-approval conversion rate ranges between 60% to 70%. Above-average performance would be considered a pre-approval conversion rate of 75% or higher, while exceptional performance would be reflected by a pre-approval conversion rate of 80% or higher.

Tips and Tricks

• Implement a streamlined and efficient pre-approval process to minimize delays and maximize conversion rates.
• Provide comprehensive guidance and support to clients during the pre-approval stage to increase their likelihood of proceeding to closing.
• Leverage data analytics to identify trends and patterns that may impact pre-approval conversion rates, allowing for targeted improvements.

Loan Processing Cost

Definition

Loan processing cost is a key performance indicator that measures the total cost associated with the processing and origination of mortgage loans. This ratio is critical to measure as it provides insights into the operational efficiency and cost-effectiveness of the mortgage lending process. By tracking this KPI, mortgage lenders can identify areas for improvement, optimize resource allocation, and enhance overall business performance. Understanding the loan processing cost is vital as it directly impacts the bottom line of the business and influences the competitiveness of the mortgage lender in the market.

How To Calculate

The formula for calculating loan processing cost involves summing up all the expenses related to loan origination and processing, including personnel costs, technology expenses, and overhead costs, and dividing it by the total number of loans processed within a specific period. Each component of the formula contributes to the overall calculation by capturing the direct and indirect costs incurred in facilitating mortgage loans.

Example

For example, if a mortgage lender incurs $100,000 in loan origination and processing expenses over a quarter and processes 200 loans during the same period, the calculation of the loan processing cost would be as follows: Loan Processing Cost = $100,000 / 200 = $500 per loan. This illustrates that the average cost of processing and originating each loan is $500.

Benefits and Limitations

Effectively measuring loan processing cost allows mortgage lenders to identify opportunities for cost reduction, streamline processes, and improve operational efficiency. However, a limitation of this KPI is that it does not account for the quality of the loans processed, and it may not provide a complete picture of the overall value created by the mortgage lending activities.

Industry Benchmarks

According to industry benchmarks, the average loan processing cost in the mortgage lending industry ranges from $500 to $900 per loan. Exceptional performance is typically defined by keeping the loan processing cost below $500 per loan, while figures above $900 may indicate opportunities for cost optimization and process improvement.

Tips and Tricks

• Implement automation and technology solutions to streamline the loan origination and processing workflow.
• Regularly review and negotiate vendor contracts to reduce technology and service costs.
• Train staff to improve productivity and efficiency in loan processing activities.
• Establish key performance indicators for individual components of loan processing to identify cost drivers.

Rate Lock Expiration Percentage

Definition

The Rate Lock Expiration Percentage KPI measures the percentage of mortgages for which the locked-in interest rates expire before closing. This ratio is critical to measure as it provides insight into the effectiveness of the mortgage lender’s ability to secure and maintain favorable interest rates for borrowers. In the context of the business, this KPI is essential for identifying potential bottlenecks in the mortgage approval process and understanding the impact of rate fluctuations on the lender's performance. It plays a crucial role in ensuring that the company can manage interest rate risk and minimize the potential negative impact of expired rate locks on business profitability.

How To Calculate

The Rate Lock Expiration Percentage is calculated by dividing the number of expired rate locks by the total number of rate locks issued within a specific timeframe, and then multiplying the result by 100 to express it as a percentage. This formula provides a clear and concise representation of the lender's ability to maintain interest rates for clients during the mortgage approval process.

Example

For example, if a mortgage lender issued 200 rate locks within a month and 15 of these rate locks expired before closing, the Rate Lock Expiration Percentage would be calculated as follows: (15 / 200) x 100 = 7.5%. This means that 7.5% of the rate locks issued during that month expired before the mortgage closing.

Benefits and Limitations

Effectively tracking the Rate Lock Expiration Percentage allows the mortgage lender to identify areas for process improvement and implement strategies to mitigate the risk of expired rate locks. However, it's important to note that this KPI does not account for the reasons behind expired rate locks, which may vary and impact the overall assessment of the lender's performance.

Industry Benchmarks

In the mortgage lending industry, a typical Rate Lock Expiration Percentage may range from 5% to 10%, with above-average performance falling below 5%. Exceptional lenders may achieve a rate lock expiration percentage of less than 3%, demonstrating a high level of efficiency in managing interest rate fluctuations.

Tips and Tricks

• Implement a robust rate lock management system to monitor and track the status of all rate locks.
• Establish clear communication channels with borrowers to ensure timely submission of required documentation for rate lock extensions.
• Regularly review market conditions to anticipate potential interest rate fluctuations and take proactive measures to mitigate the impact on rate locks.
• Offer rate lock extension options to borrowers to prevent unnecessary expiration of locked-in interest rates.

Post-Closing Client Retention Rate

Definition

The post-closing client retention rate is a Key Performance Indicator (KPI) that measures the percentage of clients who return to the mortgage lender for additional services or repeat business after their initial mortgage has closed. This ratio is critical to measure as it directly reflects the satisfaction of clients with the company's services and their likelihood to continue doing business with the lender in the future. In the context of the mortgage lending industry, maintaining high post-closing client retention rates is crucial for establishing a loyal customer base, generating repeat business, and building a positive reputation. Essentially, this KPI indicates the strength of the lender-client relationship and directly impacts business performance by influencing revenue growth, referrals, and overall market positioning.

How To Calculate

The post-closing client retention rate can be calculated using the following formula: The formula essentially divides the number of clients who return for additional services or repeat business by the total number of clients whose mortgages have closed and then multiplies the result by 100 to express it as a percentage. This calculation provides insight into the ratio of clients who continue to engage with the mortgage lender after their initial transaction has been completed.

Example

For example, if a mortgage lender has closed 100 mortgages in a year and 30 of those clients return to the lender for additional services or repeat business within the same year, the post-closing client retention rate would be calculated as follows: [(30 clients who return for additional services or repeat business) / (100 total clients whose mortgages have closed)] x 100 = 30% This would indicate that the mortgage lender has a post-closing client retention rate of 30%.

Benefits and Limitations

Maintaining a high post-closing client retention rate is beneficial as it fosters customer loyalty, generates repeat business, and can lead to positive word-of-mouth referrals. However, it is important to note that this KPI may not capture the reasons behind client retention or non-retention, and may not account for external market factors that could impact client behavior.

Industry Benchmarks

In the US mortgage lending industry, the typical post-closing client retention rate hovers around 68%. Above-average performance in this area would be considered a rate of 75% or higher, while exceptional performance would be reflected in a rate of 80% or more.

Tips and Tricks

• Establish a robust post-closing client communication strategy to maintain regular contact with clients and address any ongoing needs or inquiries.
• Offer additional value-added services such as financial education, homebuyer resources, and personalized advisory to encourage client engagement and loyalty.
• Solicit feedback from clients to gauge their satisfaction and identify areas for improvement in post-closing services.
• Implement a customer loyalty program or incentives to reward repeat business and referrals.