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Building Your Growth Plan: Key Metrics to Consider – The Lending Funnel

Sageworks
September 30, 2016
Read Time: 0 min

For many banks and credit unions, it is hard to feel anything but stuck between a rock and a hard place right now. In the current market, banks and credit unions are facing pressure on all fronts. Interest rate margins remain slim, and FinTech companies that compete directly with traditional banks and credit unions seem to pop up overnight. At the same time, the regulations governing financial institutions continue to become increasingly complex and demanding. For many banks and credit unions, the way forward is loan portfolio growth. As an Abrigo whitepaper noted, many financial institutions are having to make the choice to “grow or go.”

As banks and credit unions begin to formulate plans to grow their loan portfolios, they will face many challenges, including how to scale with existing resources and how to maintain the credit quality of their portfolios as they grow. As the leaders at financial institutions begin to formulate growth plans, there are some key metrics they can take into consideration to jump-start their growth.

The first metric that banks and credit unions should consider when developing their growth plan is their loan application conversion rate. This is the percentage of loan applications the institution receives in a given time period that is ultimately booked as loans. The loan application conversion rate measures the efficiency of the bank’s lending funnel, which is the process by which applications become loans. By understanding the funnel and the overall success of the funnel (the conversion rate), institutions can optimize the funnel and build realistic, actionable growth plans.

In order to build a solid growth strategy using the application conversion rate, it is imperative that an institution understands its own unique conversion rate and the dynamics influencing it. Depending on factors such as the local economic conditions or areas of specialization, some institutions may have quite high conversion rates, while others may have lower rates. The rate for any given institution can also change over time. Some institutions may find that their lending process is very cyclical or patterned from month to month. Likewise, some institutions may find that it is normal to have wider variations in their overall conversion rate from month to month, while others may have very steady rates.

In addition to studying historical conversion rates, institutions should also ensure that the lending funnel is optimized. Optimizing the loan funnel can be achieved by looking inside the funnel to determine what is working well and what can be improved. Just like the application conversion rate, the funnel and the length of time required to close an application will be unique for each institution, given their process, resources, and technology for loan applications. Additionally, different types of loans may have different funnels (and also different conversion rates). For example, mortgages would typically have fewer steps than complex CRE loans. The best approach is to focus on each loan type and its funnel one at a time.

The first step to optimizing the lending funnel is to identify the steps an application has to move through to become a loan, and at which steps applications tend to “fall out” of the funnel. For example, start with the first step in the funnel: what is the first thing that happens when a new application is received? Does the loan need to be assigned to a loan officer, or does the applicant need to be contacted for additional information? Proceed through each step of the funnel, asking what can happen at each step that would prevent an application from moving to the next step. Some common obstacles in the lending funnel include:

  • The applicant doesn’t qualify. Some portion of the applications submitted to the institution simply won’t meet the requirements for the loan, like Loan to Value.
  • Invalid applications. These are applications that are automatically tossed out, perhaps because the loan type or industry is not one the bank handles.
  • The application process is too long. How long does an applicant have to wait for a decision on loan? If the process is too slow they may leave for faster service.
  • Abandoned applications. When an incomplete application is submitted, but the applicant never responded with the requested additional information.
Once the weak areas of the funnel have been identified, the institution can begin to identify solutions to optimize the funnel. For example, if the problem is large numbers of unqualified applicants or abandoned applications, then one solution might be to provide applicants with more information about the process and the requirements upfront. Alternatively, if the problem is a too-lengthy application process, then it might be time to consider implementing an automated lending solution to help speed up turnaround time on applications.

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By taking the time to optimize the loan funnel, banks and credit unions can be confident that their application conversion rate is as high as possible. Using both historical observations to analyze the conversion rate and optimization to boost the rate, financial institutions can begin to build a portfolio growth plan that helps them deal with industry challenges while making the best use of existing resources and maintaining credit quality.
About the Author

Sageworks

Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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About Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

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