It’s impossible to tell precisely how much a used vehicle is worth without detailed historical data. You can kick the tires or take a peek under the hood, but this only gives you a small fraction of the information you need. For instance, it doesn’t tell you how many people have owned the vehicle or whether the airbags have ever been deployed. These factors can significantly impact a used vehicle valuation.
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.
As of this writing, there’s no pending recession, though there’s frequent speculation of a downturn, perhaps in 2020. When that downturn eventually arrives, competition for lending will be intense. Lenders will have to employ every method to minimize lending risk and operational costs. Regardless of the type of your business—bank, credit union, or finco, the biggest factor in maintaining profitability during a recession is likely to be your lending software.
For many lenders, credit risk management depends on years of experience. Their credit risk expertise is a mix of shrewd loan portfolio analysis and an innate intuition about borrower risk. While that may have worked in the past, credit risk management is shifting from human judgment to automated, data-driven lending decisions that assess credit risk far more accurately.
Large lending institutions often have personnel dedicated to analytics. These professionals have backgrounds in statistics, knowledge of SQL query language, and can mine volumes of data for insights to improve lending performance. Smaller lenders rarely have such luxury.
Decision rules are a big reason why modern, cloud-based loan origination solutions are so efficient. Decision rules may be used in nearly every step of the process. They are the foundation for loan origination automation. Unlike legacy lending software, decision rules don’t need in-house programming skills or outside consultants to make loan origination process modifications. Instead, they are created and managed by using configuration menus.
Advancements in fintech are transforming loan origination into an increasingly-automated process. Loan applications are now often turned into booked loans with little to no intervention from an underwriter. Underlying this automation is a set of loan origination business rules.
If you can’t remember when your current auto lending platform was originally implemented, it’s probably time to consider an upgrade. Technological improvements in recent years deliver functionality that dramatically improves loan origination efficiency, lowers overall processing costs, and supports well-informed lending decisions.
Automation is continually improving auto lending process efficiency, along with the quality and consistency of lending decisions. Replacing manual, mundane tasks and decisions with workflows and rules accelerates loan origination and enforces consistent decisions. Automation lets underwriters focus on activities that truly require their expertise.
Fraud has many faces. Auto dealer loan fraud isn’t as frequent as income, employment, or identity fraud by individuals and fraud cartels. Still, an application from a less-than-honest dealer can show up in the underwriting queue anytime.