Salesforce has developed a lending solution built on its CRM platform. Financial services providers that have invested in Salesforce and want to start or improve lending will probably kick the tires on it. Let’s look at its pros and cons.
Loan Origination System: The Salesforce Approach
The big draw is for lenders invested in Salesforce. Tight integration with the CRM platform lets them:
- Apply marketing, lead generation, and pipeline development tools to build demand;
- Analyze data to discover potential lending prospects among current customers;
- Implement a nurture stream to progress leads;
- Monitor referrals to capitalize on the most productive sources; and
- Track and prioritize pipeline interactions until deal closure.
If your company has a years-long investment in Salesforce, that can sound attractive. Just make sure you don’t buy more software than you need.
What Does It Take to Build a Loan Origination System?
If you’re not already invested in Salesforce, or you want to make your loan origination system more efficient, consider other options that don’t involve paying for Salesforce-specific features—software code you won’t use but will have to run.
Like many platform software vendors with industry-specific solutions, the company excels in certain areas and falls short in others. For lenders solely focused on building or improving a loan origination system, Salesforce may not necessarily be the best choice.
Financial institutions that want a dedicated loan origination system should look at cloud-based LOS vendors. Using pre-integrated cloud-based lending services, machine learning, and auto-structuring, the focus is on increasing loan origination efficiency and reducing lending risk.
Powerful Pre-Integrated Lending Services
Dozens of specialized cloud-based lending services are available to increase process efficiency and improve decision quality. Loan origination solutions that pre-integrate these specialized lending services make it effortless for lenders to select and configure a system thats meets their unique lending needs.
Non-Traditional Information Resources Reveal Financial Strength
Non-traditional information resources give lenders a more detailed and accurate picture of an applicant’s financial viability. Credit scores from the big three bureaus are industry staples, but they don’t always tell the full story. Alternative credit data is an aggregation of payment information—utilities, mobile phone, cable, and rent, along with changes of address, real estate, or bankruptcies—that provide a better understanding of an applicant’s ability to pay. Trended credit data provides up to 30 months of tradeline data to reveal improving, declining, or stable credit habits that give a lender a clearer picture of an applicant’s current financial standing.
Automated Verifications and Valuations
Automated verification and valuation services allow lenders to instantly determine the accuracy of application data. In seconds, applicant employment and income can be confirmed or refuted. Used vehicle valuations can be verified using analytic models based vehicle inspection and sales data from major auctions, as well as historic and residual vehicle values.
Machine Learning Detects Fraud and Increases Approval Rates
Cloud-based, advanced machine learning techniques analyze loan applications and detect false identity, collateral inflation, and other subtle or obvious misrepresentations of information that strongly correlate with a high probability of default.
Machine learning analyzes thousands of variables obtained from bureau data, customer information, and lending products to predict applicant creditworthiness. Hundreds of credit and risk models can be replaced by a single machine learning credit module that increases approval rates and maintains compliant lending practices.
Auto Structuring for Automated Decisioning
In a digital lending environment, an ever-increasing number of underwriting decisions can be automated. With sophisticated applications of decision rules, lenders completely automate the process of structuring alternative deals for applicants that initially fail credit policies. Auto structuring iteratively makes sequential modifications to loan terms such as down payment, interest rate, or the number of months, in an attempt to match credit policies and respond with approved or conditionally-approved loan offers in seconds.
Loan Origination System: Salesforce vs LOS Specialists
The best loan origination systems are designed to give you flexibility in creating a process that matches the unique needs of your lending practice. While Salesforce-based solutions cover the lending cycle, the loan origination portion of the process may not be as efficient and profitable as solutions designed specifically for lenders. Specialists may have the edge in responding to some loan applications.
In a competitive lending environment, speed of response to loan applications strongly correlates with captured deals. Loan decisions supported by non-traditional information sources, instant verifications, and machine learning let lenders avoid risk, make better decisions faster, and approve more profitable loans. Lenders who are serious about improving the efficiency of their lending process and improving the quality of lending decisions will want to work with software vendors whose sole focus is optimizing the loan origination process.
defi SOLUTIONS‘ LOS gives lenders the complete set of capabilities to tailor the process to their unique needs and achieve the greatest efficiency while minimizing risk. Explore your options today by contacting our team today or registering for a demo of defi LOS.
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