Optimize Loan Pricing Models With an Advanced Loan Origination System

When offering a loan term to customers, many financial institutions price out these loans to determine the risk of lending and, ultimately, decide what interest rates they set on each loan. The caveat to loan pricing is that financial institutions must remain competitive in today’s lending market, meaning they will likely need to optimize loan pricing models.

So, how can you optimize your loan pricing models? It all starts with modern tools like a loan origination system, which can help any financial institution achieve its revenue goals while providing customers with loan prices at competitive rates.

Below, we’ll explore the challenges of traditional loan pricing models and offer alternatives to streamline loan pricing for companies looking to remain competitive in today’s lending market.

Challenges in Traditional Loan Pricing Approaches

Before we dive into the challenges of using traditional loan pricing models to determine loan packages for your customers, let’s define what loan pricing is.

In general, the loan amount largely depends on factors like interest rate policy and the lending market. Financial institutions typically set interest rates as they wish, provided they comply with federal interest rate policy and the Federal Deposit Insurance Corporation (FDIC) requirements.¹

However, interest rates may also fluctuate based on market conditions. In a competitive market, customers will readily go to the bank or credit union that provides loans at the lowest interest rates. . Beyond these factors, financial institutions also price loans based on their customers’ credit.¹ As the common providers for consumers, an optimized loan origination software for credit unions and banks can help institutions streamline the loan approval process and increase their loan offerings.

Loan pricing then plays a crucial role in setting loan rates that appeal to your customers while simultaneously increasing your company’s revenue. A traditional loan pricing model tends to be less efficient when leveraging all these factors to determine the appropriate pricing for each loan an institution offers its customers.

These inefficiencies can cause the following challenges for financial institutions:

#1 Manual, Time-Consuming, and Error-Prone Processes

Traditional loan pricing models require significant time and human capital to operate, making them difficult to sustain in the long term. Typically, these models are determined using spreadsheet-based processes, which require manual data input and review to verify accuracy.

What would this look like in practice? Let’s take the example of a cost-plus loan pricing model, which determines the interest rate on loans based on:²

• Funding costs – Financial institutions incur expenses to gather funds from sources like money market funds or customer deposits before lending to customers.

• Operating costs – In regards to loan fees, financial institutions spend on application and processing fees, along with payroll expenses for the human capital that handles the logistics of loan origination.

• Profit margins – Banks and financial institutions must make enough profit on the loans they provide customers to achieve a sufficient return on their initial investments.

• Default risks – Every loan term has some level of risk attached to it. Financial institutions must be able to align the potential risk of lending to a customer with the actual risk of doing so.

Say a financial institution receives loan applications from thousands of customers a month; the institution must have sufficient time, human, or financial capital to evaluate the above factors on these loans. Doing so manually, such as within a spreadsheet, would be excessively time-consuming and subject to a considerable margin of error, such as an error in payment.

#2 Limited Data Visibility Resulting in Lower Accuracy and Efficiency

With a traditional loan pricing model, financial institutions can access large amounts of lending data but not in real-time. These institutions can become more competitive in today’s lending market if they make loan pricing decisions based on real-time data insights.

When using traditional risk-based loan pricing models, limited access to real-time data hinders accuracy and efficiency, especially when dealing with large amounts of customer data.

For example, factors such as credit scores and debt-to-income ratios typically determine the loan terms lenders offer customers. But risk-based pricing must be flexible as these factors change, or else borrower’s interest rates will remain the same month-to-month.³

In a competitive market, a lender who provides a lower interest rate to a borrower whose credit score dramatically improves after a month is more likely to earn the borrower’s business. However, lower visibility into borrowers’ evolving data can limit these credit approval opportunities and make the loan origination process less efficient.

#3 Regulatory Compliance Requirements Complicate Loan Pricing

Compliance with regulatory requirements adds another layer of complexity to loan pricing. It’s not just about meeting these requirements to the letter. It’s also about keeping your borrowers’ data safe at each step of loan origination.

Loan pricing is also complex when lenders must comply with several regulations. For instance, financial institutions that offer mortgage rates are required to follow regulations such as:

• Fair Housing Act (FHA)
• Truth in Lending Act (TILA)
• Real Estate Settlement Procedures Act (RESPA)
• Fair Credit Reporting Act (FCRA)

Each of the above regulations stipulates guidelines to protect borrowers from an unfair lending process and enables lenders to set legally- and regulatory-compliant pricing.

But, for financial institutions, keeping track of all these regulations is challenging when doing so manually. Additionally, it’s much easier for your staff to make errors when completing paperwork, resulting in potential non-compliance penalties.

Streamline Loan Pricing With an LOS

For many financial institutions that offer loans to their customers, loan origination might seem like a complex process because of the many hurdles involved in pricing the loans and competing with other lenders. But this shouldn’t be the case.

Using a loan origination system (LOS) simplifies loan pricing in the following key ways:

Flexible Loan Pricing Processes

Today’s financial market is highly complex, competitive, and regulated, meaning the more rigid a lender is, the higher the likelihood of being out-competed by other, more flexible lenders.  

Although traditional processes help lenders determine loan pricing, they are much slower and more rigid within a dynamic lending market. Each lender also has a unique set of processes for originating loans, meaning a one-size-fits-all approach to loan pricing will work for some lenders but not others.

A much better and more realistic solution is to customize aspects of the loan origination process to your specific needs as a lender, but also to those of your customers—the borrowers. For instance, a small institution that serves an elderly community will likely require tailored loan pricing models compared to a large city-based bank that caters to much younger loan applicants.

Predictive Analytics

Adopting an LOS like Fuse also provides optimized loan pricing models driven by data-based trends and insights. Gaining a competitive edge in today’s market requires lenders to comprehensively understand the trends in their borrowers’ data so they can accurately determine the prices of loans.

But it’s not just about collecting real-time data. To get the most value out of a loan pricing model, lenders must analyze the data and capture the trends so that the data speaks—and guides loan pricing decision-making. Developing optimized loan pricing models also requires leveraging historical data to understand unusual trends or anomalies.

For example, certain traditional loan pricing models may influence lending decisions using rigid data like credit scores and may not capture the holistic picture of borrowers’ qualifications. Predictive analytics can help your company better understand the behavior of borrowers whose risk profiles differ from the norm before deciding on what prices to assign their loans.

Benefits of Optimized Loan Pricing

So, what are the benefits of optimized loan pricing? Broadly speaking, optimized loan prices result in higher revenues and attract more borrowers. But that’s just the beginning.

Using an LOS to achieve optimized loan pricing can help you:

• Fast-track your growth – By pricing loans competitively, you can effectively stay ahead of the competition while simultaneously meeting the needs of more customers. As such, you can increase your customer base, resulting in more referrals—which then drive up revenue in the long term.

• Appeal to your customers – When your customers understand that the interest rates on loans are based on their updated credit scores, credit history, or other such real-time data, they are more inclined to become repeat customers when taking out additional loans.

• Increase efficiency – Advanced analytics tools within an LOS can detect anomalies during loan origination, which improves how fast customers’ loans get approved and reduces the troubleshooting calls your staff will take from customers.

• Match market pricing – As the market evolves and interest rates increase or decrease, optimizing loan pricing via an LOS ensures you remain flexible and competitive, keeping up with the competition while satisfying your customers’ needs.

Optimize Your Loan Pricing Models with an LOS From Fuse

Equipped with a next-gen loan origination system, you can dramatically streamline loan pricing to match your customers’ needs while maintaining a high level of operational efficiency.

The Fuse LOS is designed for optimization, meaning it’s:

• 95% faster at integrating partners into your pipeline, improving speed and efficiency
• User-friendly and can be used by anyone on your team, regardless of coding experience
• Flexible to your unique processes, giving you the competitive advantage
• Compliant with SOC 2 Type 1 and 2, helping you secure your customers’ data
• Scalable, whether you’re deploying it on-premise or on the cloud

Ready to optimize your loan pricing and increase revenues? Request a demo today to learn how the Fuse LOS can streamline your operations.

Sources:

1. Investopedia. How Banks Set Interest Rates on Your Loans. https://www.investopedia.com/articles/investing/080713/how-banks-set-interest-rates-your-loans.asp
2. The Definition. Cost-plus Loan Pricing. https://the-definition.com/term/cost-plus-loan-pricing
3. Investopedia. Risk-Based Pricing: What it Means, How it Works. https://www.investopedia.com/terms/r/riskbased-pricing.asp/