Author:
Nexval Infotech
In a 2018 survey, Equifax found automation to be the top near-term priority for mortgage lenders. Fast forward to 2022, and mortgage process automation has come a long way. Cognitive technologies like artificial intelligence, machine learning, optical character recognition, and neural networks are supercharging automation – taking it beyond the ambit of the usual repetitive processes. That is why intelligence process automation (IPA) is so important for mortgage businesses today.
IPA combines robotic process automation (RPA) with AI and ML so that the mortgage process automation bots are flexible and self-learning. Instead of being purely rules-based, they can handle more complex tasks, address exceptions, bring humans into the loop if needed, and learn from mistakes. In a recent IPA study, 89% of surveyed companies found that automation-enabled digital transformation provided them with a competitive advantage. This also applies to the mortgage sector.
Read more: What Is the Difference Between Automation and Hyperautomation and Why Does it Matter for Lenders?
What Does Intelligent Process Automation (IPA) in Mortgage Look Like?
Financial services, and mortgage, in particular, are known to be highly reliant on repetitive manual tasks. Automation resolves this by replacing human workers with bots that can perform a massive volume of tasks in a fraction of the time, without errors. Some of the common candidates for mortgage process automation include data transfer between systems, checking documents, data redaction for compliance, etc.
Intelligent process automation takes this to a whole new level by endowing the bots with cognitive intelligence, almost like human beings. In addition to transferring data, it can now use AI to differentiate between structured and unstructured information, make sense of the latter, perform complex data transformations, and much more. In mortgage servicing, for instance, IPA can automatically notify borrowers of key events, and handle routine conversations without a servicing executive ever intervening.
Indeed, mortgage service automation is one of the key applications of IPA in financial services. Key servicing assets such as payment transactions, monthly statements, escrow records, etc., can easily be processed by IPA to minimize errors.
Read more: 5 Reasons Why the Mortgage Industry Needs Smart Data Fabrics
3 Ways Intelligent Process Automation Empowers Mortgage Operations
IPA is useful for mortgage businesses in any operational area that involves data, such as mortgage services. Some of the key examples include:
1. Automated borrower assessment for faster underwriting
Borrower assessment and data verification is a central part of the underwriting stage on the mortgage value chain, and any delay can irreparably damage the customer experience. Errors in borrower assessment lead to effort duplication for both the borrower and lender, which extends the approval process and adds to your costs. IPA can look after a wide range of tasks when assessing loan applicants, such as employment history, income records, payroll data, etc.
The benefit of using IPA over traditional, RPA-based mortgage process automation is that it even works in unfavorable conditions. For instance, if the payroll data is incomplete, the bot does not only throw up an error and stop functioning. It can be programmed to self-learn and seek out different sources for filling in the information and also reach out to the right stakeholders.
2. Assisting mortgage servicing executives with intelligent recommendations
Live contact centers continue to be essential for mortgage businesses as they provide a necessary “human touch.” Borrowers get to interact with a knowledgeable support executive in a language that they understand without having to navigate complex reports, forms, or data. But one cannot deny that customer support is a cost and effort-intensive task that adds to your operational overheads.
Intelligent process automation (IPA) in mortgage can make small but significant improvements to this process. It can scan ongoing customer conversations to surface highly relevant data that the servicing executive may need at that moment. Instead of having to look through multiple databases and repositories, an IPA bot automatically recommends the information needed to resolve a query. Further, IPA can support mortgage service automation by automatically assembling reports.
3. Natural language processing to streamline document management
RPA has long been used in document management tasks, from document collection to indexing and storage. Now, with IPA, it is possible to go a step further and perform more complex operations related to mortgage documents. For example, natural language processing (NLP) is a cognitive technology that allows bots to actually “read” documents and flag specific keywords and phrases. Based on this, you can classify documents into highly personalized categories and sub-categories.
Optical character recognition is another IPA technology that lets bots convert information embedded in photographs, screenshots, PDFs, etc., into structured documents. This minimizes the risk of errors when processing a mortgage application, as one always has access to the most complete and comprehensive information set. Finally, NLP also plays a role in mortgage service automation by checking customer conversations for keywords, red flags, customer sentiment cues, and much more.
Read more: What Is Individual Artificial Intelligence and How Will It Impact the Mortgage Industry?
Discover the Power of IPA for Your Mortgage Operations
These three examples only scratch the surface of what one can achieve with IPA. From mortgage servicing to title automation, cognitive technologies can transform nearly every process that deals with data. Recent advancements in application programming interfaces (APIs) even allow IPA bots to work across multiple systems so that you can implement connected workflows with little to no human intervention.
At Nexval, we specialize in intersecting the latest digital innovations like IPA with our years of understanding of the mortgage sector in order to solve age-old business problems and anticipate new ones. In addition to mortgage servicing, title, and origination processes, our dedicated AI team employs DevOps techniques to help you build cutting-edge IPA apps and bots.
To discover the full potential of IPA for your mortgage operations, talk to our Tech Gurus today.
Frequently Asked Questions About Intelligent Process Automation
Q1. What is the difference between Intelligent Process Automation and Robotic Process Automation?
Although Robotic Process Automation (RPA) is often confused with Intelligent Process Automation (IPA), they are different in terms of capability. RPA technology is used to perform repetitive tasks to complete a process by mimicking human actions whereas IPA is used to perform more complex end-to-end tasks by combining various technology components like RPA, machine learning, natural language processing, and intelligent workflows. RPA can perform rule-based tasks, like sending an automatic reply to an email whereas IPA can perform tasks that require analysis and make decisions without human intervention.
Q2. How can intelligent process automation generate value for your mortgage business?
IPA can be beneficial for your mortgage business in many ways as it can help:
- Enhance efficiency by taking care of rule-based and repetitive tasks
- Minimize human errors while increasing speed and accuracy
- Ensure compliance
- Cut down on overhead experiences
- Reduce turnaround times
Q3. What is the difference between attended and unattended bots?
There are two modes of how RPA bots work – attended and unattended. Attended bots target the front-end activities and can come in handy when the end-to-end process cannot be automated. Virtual assistants are one of the most common examples of attended RPA bots that help employees in front-office tasks. On the other hand, unattended bots perform tasks and interact with various applications on their own, that is without human intervention. These bots can execute end-to-end processes independently. They are mostly used for back-office operations.
