Transforming Loan Origination with AI: Our Approach
Looking for a way to benefit from AI without replacing your existing software stack and processes? Our API-first approach helps you do just that. Discover how it works.
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Introducing artificial intelligence into established businesses can be daunting, especially if it requires changing your existing processes, moving to a new software stack, or retraining your employees.
To help you overcome these challenges, we an API-first approach. It allows you to combine your existing loan origination systems with AI in the most seamless way possible.
We’ll share what works the best, what our approach is, and how businesses can integrate AI into existing loan origination systems to improve operational efficiencies and drive innovation.
Loan Origination in the 2020s: The Software Landscape
The loan origination software landscape in the 2020s is marked by technological advancements. The strong emphasis is on the integration of artificial intelligence to enhance decision-making and operational efficiency.
For example, Encompass leverages AI to automate underwriting, ensure quicker loan approvals, and reduce manual processing errors. Finastra’s Mortgagebot is an AI integration that provides a personalized lending experience with accurate risk assessment. Black Knight’s Empower system incorporates AI-driven advanced analytics to optimize quality and compliance.
All of these providers showcase a trend toward adopting AI technologies. We’ve also recently discussed the use of AI in mortgage lending operations with Thomas Shaw, CMO & CTO at LS Mortgage, in our podcast.
AI can automate routine tasks, analyze large datasets, improve risk assessment, and enhance customer interactions with personalized recommendations. Most modern LOSs utilize AI to automate operations and improve decision accuracy, but the extent of AI integration still varies.
Software like Encompass and Calys Software provide APIs that can integrate into existing systems. However, software like Mortgage Builder doesn’t integrate into existing systems using API. Even though it’s great software, it makes integration with existing systems and other software a lot more difficult, risky, and cost-effective.
Regardless, there’s a clear shift towards AI systems in the software landscape. Digital transformation drives better accuracy, faster speeds, and improved customer experience in the lending industry. We are also noticing how AI reflects a broader transformation for financial institutions.
AI Opens up New Possibilities in Loan Origination
AI has the potential to transform the lending process, which opens new possibilities for lenders and borrowers.
Areas where AI benefits and transforms loan origination the most include:
Loan origination automation
Automated document and data processing (e.g., bank statements)
AI excels at automating repetitive tasks, which speeds up the loan origination process. This can result in several benefits: Lenders can get notified in a matter of hours or even minutes if they qualify for a loan rather than waiting for days. This leads to:
Improved customer satisfaction
Fewer human errors
Minimized bias
Fairer loan and credit decisions
We confirmed this with Andy Mattingly, Chief Operating Officer at FORUM Credit Union, when discussing AI-driven lending.
Another thing that improves the lending process experience is personalization. AI can analyze customers’ data and information to suggest customized loans based on individual financial behavior.
There are also highly intelligent chatbots and advisors with natural language processing capabilities. They can provide 24/7 support with an interactive customer service experience.
Where Can AI Help the Mortgage Industry?
Three areas where artificial intelligence and machine learning can help companies include:
AI can analyze unstructured documents and non-traditional data sources like social media behavior, spending patterns, and educational background. Using this information, AI builds sophisticated risk assessment models that can help identify and eliminate potential risks.
Traditional methods can hardly compete with AI’s detailed risk assessment.
Using similar models, AI can also detect fraudulent patterns, which enhances the security of the lending process. AI also frequently updates systems according to law changes to ensure compliance.
Still, many mortgage companies are still on the fence about implementing AI—and they have good reason to be cautious.
Replacing Loan Origination Systems Is Painful, Time-Consuming, and Expensive
Replacing loan origination systems is a painful process for a few reasons:
High costs
Complexity
Time investment
Risk of data loss
Employee training and adjustment
The biggest challenge is data migration. Existing LOS contains vast amounts of sensitive and historical data that need to be safely and accurately transferred to a new system.
This is a time-consuming and risky process that can lead to data loss, corruption, or breaches if not handled properly.
Another potential issue is integrating AI with other software a company uses (such as CRMs and underwriting tools).
This is crucial, as a lack of integration can lead to many painful issues—such as:
Data becoming inaccessible. When AI systems are not integrated with existing software, data can become fragmented across different platforms. This isolates it and makes it inaccessible to other parts of the organization, hindering comprehensive analysis and decision-making.
Inefficiency and redundancy. Non-integrated AI systems often require separate processes and workflows. For example, employees may need to manually move data between systems, which is labor-intensive and error-prone.
Increased operational costs. Managing multiple non-integrated systems can lead to increased operational costs. It requires additional resources for maintenance, support, and training.
Scalability challenges, security risks, and user frustration caused by the constant switching between disparate systems.
Smooth transition and communication with other software is another challenge that requires extensive customization.
The next in line is employee training and adaptation. Employees who are used to the old system must be retrained. This requires time and resources, which affects productivity levels. It can also lead to potential errors during adaptation to the new system’s functionalities.
Finally, the cost of replacing a LOS can be huge as it includes:
Purchase and implementation of the new loan origination software
Potential downtime
Employee training
Hiring of AI consultants
These issues are keeping many mortgage companies from implementing AI. To minimize them, we’ve decided to take a different route from most AI vendors. It’s what we call an API-first approach.
Our Solution is API-First Approach
API, or Application Programming Interface, is a set of rules and protocols that allows different software applications to communicate with each other. In the context of loan origination systems and AI, it basically helps connect the two.
This is exactly why we use “an API-first approach”—i.e., prioritize designing and developing our solutions with robust APIs from the outset. By doing so, we ensure seamless integration of our AI capabilities into existing loan origination systems.
That way, we don’t force mortgage companies to replace their systems with new ones, nor force them to retrain their employees and change the way they work.
We give them the freedom to choose between the two:
Completely replacing their old systems with a new, more robust one, or
Integrating new solutions with existing software, i.e., upgrading current systems.
APIs also offer a lot more flexibility, allowing companies to use our AI across different platforms and interfaces. For example, they can integrate it with web applications used for online mortgage applications, mobile apps for on-the-go access to loan status updates, and backend systems for managing customer data and analytics.
Comparing it to alternative integration methods will quickly show us its main advantages:
SDKs (Software Development Kits): SDKs provide tools for direct integration, but may limit flexibility since they often come with predefined functionalities. They may also not easily adapt to unique system requirements without extensive customization.
Embedded AI Modules: Pre-built AI modules offer convenience, but may lack the versatility needed to seamlessly integrate with diverse software environments. Their functionality may be constrained to specific use cases and may not support comprehensive customization.
Custom Integrations: While offering tailored solutions, custom integrations require significant development effort and ongoing maintenance. They can be costly and time-consuming, especially when adapting to evolving AI technologies and changing business needs.
This shows what makes an API-first approach so advantageous—it streamlines integration, supports flexibility across platforms, and minimizes disruption to existing systems and workflows.
Let’s look at other benefits in more depth.
Benefits of Our Approach vs. Replacing Your Existing Software Stack
1. Your Process Stays the Same
Keeping your existing loan origination system minimizes disruption and allows employees to continue using a familiar workflow.
This eliminates the learning curve and maintains productivity. Upgrading LOS usually doesn’t require downtime. And since the upgrade doesn’t alter the core functionalities, employees can quickly familiarize themselves with the upgraded system features and improve performance.
A stable and smooth transition that doesn’t require a complete overhaul is another benefit, which avoids extensive retraining. Also, a company can keep its existing system, which is most likely already customized for its specific needs.
2. Reduced Implementation Time
Implementing upgrades is always faster than a full system replacement. Using the same foundational structure, upgrades integrate quickly, which minimizes downtime.
Continuous operations reduce expenses, maintain business continuity, and minimal disruption to daily operations. The quicker implementation also leads to other advantages like the quicker realization of the benefits and the ability to respond to market demands.
3. Minimized Risk
Upgrading LOS poses fewer risks compared to a full replacement. With the core system intact, there’s a reduced chance of data migration issues, integration failures, and operational disruptions.
The upgrade leverages the existing LOS’s stability and reliability, which minimizes error and potential downtime. Upgrading always ensures a smoother transition, which preserves the integrity of data and workflows.
4. Cost Efficiency
Upgrading an existing LOS is almost always more cost-effective than replacing it entirely. It leads to a lot of cost reduction by eliminating the need to purchase new software, migrate data, develop extensive training, and hire AI consultants.
With lower up-front costs and the requirement of fewer resources, companies benefit from substantial cost savings.
5. Improved Performance
Improved LOS enhances performance, resulting in faster processing times and smoother operations.
Companies get a chance to process loan applications more efficiently, reduce wait times, and improve customer satisfaction. Security is also improved as the integration can include security upgrades to protect customer data and foster compliance with regulatory requirements.
Staff can also serve customers better, improve productivity, and deliver exceptional service.
Upgrade Your LOS
Would you like to keep your loan origination system but improve it with the help of artificial intelligence?
If you’re looking to implement AI in your existing LOS, please schedule a 30-minute call with our experts. We can discuss your needs and the best ways to integrate AI into your company. You’ll also get a chance to see how our AI Agents work live.