Fintech: Auto Loan Software’s Place in the Industry

Most companies now use cloud-based services to host at least some of their data and applications. Per the RightScale Cloud Computing Trends: 2018 State of the Cloud Survey 96% of technical professionals surveyed already use cloud. AWS remains the leading provider of cloud services.

For the lender, the cloud offers numerous, proven benefits that lower costs, improve lending efficiency, and extend market reach. In comparison to legacy lending software, cloud-based solutions reduce CapEx by eliminating the need to purchase and install server, storage, and communications hardware on premises. Cloud also reduces OpEx. IT professionals no longer spend time installing, managing, or upgrading hardware. Eliminating on-premises hardware and infrastructure also saves on electricity, cooling, and real estate costs.

Cloud transforms the way software is implemented, integrated, used, and updated. Fintech auto lending software, hosted by a provider like AWS, is quickly provisioned and configured to meet specific lending processes and practices. There’s no need for costly, time-consuming custom programming. Configuration enables lenders to easily customize the software to deliver the needed functionality. The cloud also makes it easy to integrate with other fintech software and services (alternative credit data, fraud, valuation, compliance and risk) that enhance a lender’s ability to make better quality lending decisions.

The cloud lets lenders use the latest software. New features and functionality developed by the vendor are immediately available once software revisions are uploaded to the cloud, as are patches and bug fixes. The cloud is better for consumers, too. Loan applications can be made with any web-enabled device. Digital documents, business rules, alternative data sources, and automation all let lenders make loan approvals and offers quickly—often in seconds.

Fintech helps lenders make better decisions. The technology gives you a more detailed, accurate, and current profile of applicants based on a wider variety of data sources. Standard credit bureaus are great for quick decisioning on prime and better or subprime and lower scores. However, for applicants with borderline scores or applicants with little to no credit history, FICO scores are insufficient for quality loan decisioning.

To address this gap, ever-increasing volumes (“big data”) of consumer data (employment and income records, real estate, utility and mobile phone payments, rental records) are gathered, aggregated, and available to lenders as alternative credit data via cloud integration with loan origination software. Lenders can use these data, in addition to, or in place of FICO scores, to evaluate applicant creditworthiness and reduce risk in lending decisions.  

Alternative credit data also helps borrowers. First, a clearer picture of applicant creditworthiness from alternative credit data allows lenders to offer deals that closely match the borrower’s financial strength and reduce the risk of delinquency or default. Second, for the millions of consumers who have thin or non-existent credit files and may otherwise be denied credit, alternative credit data can be used to demonstrate creditworthiness and obtain funding. For lenders who previously overlooked thin credit file applicants, they could become new opportunities for greater profitability.

In addition to the volumes of big data sources that support better quality decisioning, lenders also generate a lot of applicant, borrower, process, and portfolio data. That data also helps improve lending process efficiency and portfolio performance. Insight derived from the combination of big data and analytics may be one of the greatest benefits of the fintech revolution.  

A modern loan origination system uses automation and produces operational metrics as applications move through the underwriting, funding, and servicing phases of the lending cycle. By applying analytics to these data, lenders gain insight into lending process efficiency. Analytic reports and customized dashboards can quickly show:

• Approval, book-to-look, and capture ratios by week, month, quarter, or year;
• Ranking of originations by dealer or channel;
• Originations by FICO scores;
• Number of applications by time period, region, or zip;
• Average auto-approval time for super prime applicants;
• Percentage of auto-declined applications;
• Number of overrides by underwriter; and
• Ranking of adverse action reasons.

Insights gained from analyses can be used to improve lending process efficiency by identifying underwriting bottlenecks, trends in application volumes, or credit policies that hinder lending opportunities.

Analytics applied to the loan portfolio allows lenders to evaluate current performance, based upon past credit policies, as well as adjust policies to optimize performance going forward. Analytics applied to the loan portfolio can reveal:

• Borrower attributes that correlate with a likelihood of default;
• Need to offer better terms to millennials with student loans to reduce risk of delinquency; and
• Interest rate increase for one segment has not impacted the number of bookings. Could other market segments tolerate a similar increase?

An auto lending system that incorporates analytics gives lenders unlimited opportunity to analyze process efficiency and portfolio performance. Fintech analytic capabilities don’t require data scientist expertise. Easily configurable reports and dashboards provide users with the concise information they need to assess process efficiency and portfolio performance.

Lenders who adopt a disciplined approach to applying analytics on a regular basis gain a detailed and accurate insight of their lending efficiency and portfolio performance. That insight confirms current credit policies and lending processes are on target, or allow lenders to continually make improvements as needed to remain competitive and profitable.

Some segments of the finance and auto industry may have been initially resistant, perhaps even threatened by fintech innovations. Now they’re seeing the financial benefits first-hand.

• Banks and fintech companies recognize their mutually beneficial relationships. Fintech providers deliver innovative solutions, to match with banks’well-established customer bases and proven business models
• Dealers, initially concerned that fintech solutions might reduce their roles in the auto buying process, acknowledge that a simplified, faster lending process equals a better customer experience.
• The wealth of big data available to direct lenders gives them detailed borrower information in comparison to going indirect through a dealer. Direct lending is gaining popularity with car buyers and customer satisfaction is high among direct lenders.
• Regulations are often considered hurdles to efficiency and productivity, but the CFPB announced a regulatory sandbox based on the Global Financial Innovation Network (GFIN) Consultation Document. The initiative is designed to help fintech firms develop new financial products and services.

Fintech innovation is transforming nearly every aspect of the financial services industry, including auto lending. To remain competitive and profitable, lenders must adopt fintech auto lending solutions that take advantage of cloud, big data, and analytics.