Forecasting and Rates and Compliance, Oh My! Pricing Strategies in Consumer Lending
Lenders must navigate a complex matrix of consumer behavior, competitive shifts and tech advancements to foster sustainable growth. And with increased delinquencies and declining affordability, today's lending landscape also has heightened margin pressures and rising loan risks. With high interest rates shaping the sector, understanding how your loan pricing strategies stack up against the competition is essential.
A 2024 survey of lending executives shows room for improvement in how loans are priced and sold. The survey revealed several areas of opportunities:
· Many lenders aren’t using forecasting models. Two-thirds of respondents say they have invested in advanced analytics for risk-based pricing, yet only 20%-30% report using demand or price sensitivity models in their pricing decisions.
· Rate changes are taking too long. More than one-third of survey respondents report taking a week or longer to update their rates, leaving them flat-footed against competitors while simultaneously increasing interest rate risk.
· Compliance and loan profitability are keeping lenders up at night. Dealing with compliance issues (46%) and ensuring loan profitability (44%) are the top challenges when pricing personal or auto loans/leases.
· Lenders want to optimize for profitability and forecast it right. The most critical capability in a pricing analytics solution is pricing optimization (53%). Forecasting models (40%) and real-time pricing capabilities (37%) round out the top three.
Powerful pricing solutions leverage advanced data analytics and artificial intelligence (AI) to help lenders make data-driven decisions faster. Additionally, agile pricing operations can help break an overall project into smaller tasks and start with small changes that bring powerful results, including:
· Faster, more precise price adjustments. AI-driven price optimization allows lenders to dynamically adjust pricing with high precision and speed in response to fluctuating market conditions, minimizing the risk of unprofitable loans and lost business volumes.
· Navigating challenges with scenario simulation. Scenario simulation allows lenders to project pricing scenarios and outcomes, helping to navigate declining loan profitability, compliance issues, and inflexible pricing structures.
· More accuracy around customers and pricing. The integration of alternative data into the lending process enriches lenders' understanding of customer behavior and creditworthiness, leading to more accurate risk assessments and informed pricing decisions.
It’s clear that technology can help with decision-making, optimizing pricing models, targeting lower-risk borrowers, and maintaining profitability amidst challenging market conditions, but choosing technology solutions can be overwhelming. To improve your organization’s lending, you should look to:
Use predictive modeling to make individualized lending offers. Your Pricing Analytics solution should include a wide set of optimization algorithms geared to handle various pricing structures, regulatory and business requirements, and market scenarios. The algorithms must also support solving for complex portfolios, Customer Lifetime Value (LTV), multi-product variants, rank, and customer-centric optimization problems.
Gain competitive advantage with advanced analytics. Analytics provides lenders the ability to craft offers in real-time, with predictable outcomes. By employing world-class data science, AI, pricing optimization algorithms, and machine learning, lenders can deliver the best-priced and most-personalized product to every customer, every time.
Adjust pricing and present offers at the point of decision. Markets are highly dynamic. Prices change often – due to seasonality, changes in competitor pricing, fluctuating interest rates, or other variables. Developing and implementing the best pricing strategy for personalized lending no longer needs to take weeks or months.
Get seamless with systems integration. Once an offer is delivered and accepted by the customer, their loan information must be passed seamlessly to the lender’s loan origination system (LOS), so the completed loan application can enter the workflow, document management, and compliance tools already in place. And with API-based architecture, transitions to legacy applications and infrastructure can take place in steps, so software can be replaced or augmented over time.
Don’t let your lending solution be a “black box.” It must be open and transparent, with an audit trail for all transactions, ensuring compliance with fair lending rules and regulations, backup for decisions and offers, and immediate access to a transaction history that can be reviewed both internally and externally.
The rapidly changing dynamics of consumer lending demand that lenders adopt pricing strategies that can keep up. By embracing predictive modeling and real-time pricing adjustments, lenders can better compete while effectively managing compliance and loan profitability. As the industry continues to face challenges such as rising interest rates and fluctuating market conditions, leveraging data-driven insights will be crucial for making informed pricing decisions and maintaining customer trust. Ultimately, a commitment to transparency and agility in pricing operations will empower lenders to not only survive but thrive in an increasingly complex landscape.
About Author
Will Ely is Global Banking Solutions Manager at Earnix. An expert in pricing analytics, Will brings deep experience in advanced statistical modeling, machine learning, and cloud-based SaaS deployment. He has worked with some of the world’s largest financial institutions, helping them utilize pricing and product personalization to enhance revenue, growth, and customer experience.