Using advanced technologies to navigate economic cycles

The mortgage industry is highly susceptible to economic fluctuations. Lenders struggle to maintain profitability, mitigate risk and operate efficiently through the instability of the boom-and-bust cycle. At the root of this issue is the labor-intensive nature of the underwriting process. Integrating automation and AI into mortgage underwriting processes is essential for financial institutions seeking to enhance their resilience and maintain a competitive edge. However, this needs to be done responsibly using technology and process transformation that address the multifaceted challenges of market volatility. To understand how to approach this responsibility, let's jump into the impacts of these technologies on underwriting capabilities, the benefits and the costs.

Lenders need a comprehensive automated underwriting solution

Given the market and economic variability, the challenge of enhancing legacy systems and the continual need to provide world-class customer experience, lenders need a safe and secure agile solution. For example, automation and AI can be integrated into mortgage underwriting processes to address industry volatility. Lenders need a solution that streamlines workflows, enhances accuracy, reduces costs, improves customer experience and strengthens risk management and compliance.

Critical capabilities of an automated underwriting system

These solutions must allow lenders to automate and enhance underwriting quality using APIs for quick integration into current processes or a platform that integrates with loan origination systems (LOSs) and other backend systems. Critical capabilities of an automated underwriting system include:

  • Streamlined workflow and enhanced efficiency by automating repetitive and time- consuming tasks, allowing underwriters to focus on complex decision-making processes. This reduces processing time and increases efficiency.
  • Intelligent data analysis and decision-making using AI and machine learning to analyze large amounts of data quickly and accurately, enhancing the accuracy of credit decisions.
  • Cost reduction and scalability by automating underwriting processes, reducing operational costs, enabling scalability and managing increased volumes without compromising speed or quality.
  • Enhanced customer experience by providing faster loan approvals and more transparent processes.
  • Improved risk management and fraud detection using AI-driven analytics, improving risk management and fraud detection capabilities.
  • Compliance and regulatory adherence by automating checks and audit trials.
  • Adaptability and future readiness are established through AI algorithms enhanced and customized to work with new data arising from changes in market conditions and regulatory policies.
  • Strategic insights and reporting provide comprehensive analytics tools for informed strategic decision-making and trend observations.

Improving scalability while enhancing efficiency and accuracy

Traditionally, mortgage underwriting involves extensive manual reviews. In times of prosperity, there’s a rush to hire and adequately take advantage of the surge in mortgage applications. But when inflation sets in and interest rates soar, trade publications announce layoffs by the thousands. These drastic but seemingly necessary cost-saving measures result in:

  • Reduced profitability
  • Hefty restructuring costs
  • Lower productivity and employee morale
  • Increased operational risk
  • Compromised competitive positioning

These conditions eventually subside, but the economy perpetuates this cycle, and staffing is always the primary symptom—too much or not enough. The truth is that there’s an underlying scaling deficiency to blame. By reducing the amount of manual intervention throughout the mortgage cycle, lenders can shift much of the burden of oscillating application volumes from personnel to technology and drastically improve business agility.

Helping lenders respond to market changes through AI-enabled systems

An organization’s ability to respond quickly to market volatility is critical, but it can’t come at the expense of efficiency or accuracy—especially for those in the financial services industry.

AI-enabled systems are designed to be adaptive, learning from new data and refining their outputs based on patterns. While AI can handle simple to complex tasks, it can also continuously improve its models with updated data; it requires oversight to ensure the accuracy and relevance of its insights. By leveraging these evolving models, AI provides timely information and recommendations, helping organizations respond more effectively to market changes and make informed, data-driven decisions.

The benefits of automation in mortgage lending

Automating routine tasks will streamline operations, reduce the need for extensive manual labor, and ease the burden of training new resources. In turn, lenders can expect reduced operational costs, lower processing times, fewer human errors and higher quality risk assessment and compliance accuracy. AI-driven systems can also process large volumes of applications simultaneously, enabling scalability that manual processes cannot achieve and increasing mortgage application pull-through rates. This scalability is especially crucial during periods of market instability.

Regulatory compliance and fraud detection

Automated systems equipped with AI can help ensure adherence to regulatory requirements by continuously checking transactions and flagging potential non-compliance and fraud issues. AI’s advanced pattern recognition capabilities detect anomalies and suspicious patterns early, allowing financial institutions to prevent fraud and safeguard their assets and reputation.

Improved risk management

Lenders might lower their credit standards in competitive markets to attract more borrowers. This can lead to lenders approving higher-risk loans, which may increase default rates overall. To mitigate the increased risk, lenders need more sophisticated risk assessment models to manage larger volumes and accurately identify high-risk applicants.

With increased scrutiny in banking due to bank closures, mergers and acquisitions, there is a critical need to improve risk management. When intelligently designed and implemented, AI and machine learning models enhance risk management by offering more profound insights into borrower profiles. By ending the traditional “stare and compare,” these technologies can analyze vast datasets, identify patterns and predict potential defaults with higher precision than conventional methods. Furthermore, by incorporating alternative data sources, advanced analytics enables the creation of more comprehensive risk profiles, enabling lenders to make better decisions, reducing the likelihood of default and mitigating financial risks in order to quickly react to trends in the marketplace.

Enhanced customer experience

The benefits of AI and automation are not limited to the back end. Customers are looking for faster lending processes that empower them to act quickly when selecting a mortgage product, locking in rates or making an offer on a house in a market with extremely low supply. Integrating AI and automation transforms the customer experience by providing personalized mortgage product recommendations, quicker loan approvals and improved customer satisfaction. This can be accomplished in several ways with varying degrees of solution complexities. For example, chatbots and virtual assistants offer 24/7 support, answering queries with personalized responses and guiding applicants through the process, improving accessibility and convenience for potential borrowers. This ability to establish a seamless, efficient process attracts more customers and fosters loyalty to drive repeat business.

Legacy technology and process adaptation

It is no surprise that during periods of market stability, lenders are more likely to invest in advanced underwriting technologies. However, during downturns, the focus is on cost-reduction measures, such as automating manual processes and improving efficiency. Current market projections indicate lenders will be experiencing continued difficulties and, as a result, need a technological solution that provides the flexibility necessary to address this volatility. This includes the need for intelligent systems and associated business process transformations that facilitate onboarding new talent, decrease learning curves and maximize talent productivity.

Additionally, lenders are beholden to legacy loan origination systems that are difficult to configure and inhibit their ability to leverage innovative technology that brings the agility and cost-effectiveness needed to respond adequately to market instability. Change costs are high for many legacy solutions, and lenders need the ability to quickly introduce AI and automation into their systems and processes without implementing huge system modernization and platform investments. AI and automation-enabled APIs are practical and can eliminate costly solutions while delivering the capabilities lenders need.

Next steps to integrate AI and automation in financial institutions

The mortgage industry is still experiencing the bust period following the pandemic-induced boom, with no indication of another upswing in mortgage activity. The Mortgage Bankers Association forecasts a bleak economic outlook featuring a decline in real gross domestic product and a rising unemployment rate through the end of 2025.

In 2024, the mortgage industry saw mass layoffs and associated cost-cutting measures. Lenders ought to make this the last time they’re so heavily impacted by such a cycle. By integrating automation and AI, financial institutions can enhance efficiency, accuracy and scalability before thousands of employees are onboarded to handle the next flood of mortgage applications. Embracing these advanced technologies is crucial for securing a competitive edge and ensuring long-term sustainability in the mortgage industry.

CGI AccuLender stands out as a powerful tool in this transformation. It equips lenders with the capabilities needed to thrive in a volatile financial environment by improving operating efficiencies and overall pull-through rates to bring in additional revenue. Connect with our team today to learn more.