Demystifying automation-ready data for the mortgage industry

As discussed in our last post, our new eBook, Achieving Automation with AI & RPA, details the steps lenders can take to fully understand the intelligent automation landscape, and select the right mortgage automation technology solution. In this post, we further explore this eBook and pull back the covers on automation-ready data.  

Mortgage process automation drives a significant reduction in time and costs, while improving quality and reducing risk. The output of automated document recognition (ADR) and automated data extraction (ADE) processes within the ICE Mortgage Technology Platform™ is automation-ready data. This type of data must be aggregated, cleansed, refined, and processed in order to be made available for downstream robotic process automation (RPA). This critical step unlocks the full potential of automation. 

So, what constitutes automation-ready data? It can be defined as: 

  • Verifiably correct data 
  • Data that is sourced from the correct document or data field
  • Data that has been verified for accuracy and always maintains a link to its source
  • Data that has the flexibility to be updated if a new version is ingested
  • Data that is mapped so it can be accessed and used at any time

Scalability and Ellie Mae AIQ

Variations in document types often exist. For example, bank statement format is dependent upon individual financial institutions. In cases of similar layouts, formatting differences can still exist based on fonts, image qualities, text treatments, etc. For the mortgage industry, AIQ’s document recognition and data extraction capabilities have taken all of these considerations into account.

Once documents are ingested, AIQ’s capture capabilities offer a configurable way to process documents or data, and automatically brokers the next step in the process. AIQ can scale to receive content via multiple channels, such as a collaborative portal, APIs, or manual upload from email. The controller then determines how the content is subsequently processed. Also within AIQ is an ensemble of supervised machine learning algorithms, coupled with mortgage industry-specific heuristics, that are optimized for high-productivity validation and correction. AIQ can scale up or down based on demand, and leverages best-in-class serverless components in order to fetch, load, and prepare the data to be routed to the AI engine. With a less scalable system, the feedback loop from ingestion to results could take weeks, whereas AIQ’s scalable model performs this function in minutes, profoundly impacting time to value.

Achieve faster results with RPA

Robotic process automation (RPA) is the automation of high-volume, repeatable tasks that a human would otherwise perform. This includes tasks that could be performed within a specific workflow or across multiple applications. Effective use of RPA within the mortgage industry removes bottlenecks and delays, while enabling enormous capacity improvements. It also frees up mortgage team professionals to apply their knowledge and attention to higher priority cases, rather than repetitive tasks. 

AIQ takes advantage of that perfected data that was ingested earlier in the process to automate key tasks in underwriting; such as evaluating income that has traditionally been a manual effort. For the transactions that can't be automated, it can be presented in an exception queue for an underwriter to evaluate with their expertise and experience.

Download the full eBook now, to learn even more about the advanced AI capabilities of AIQ and how to experience true mortgage process automation.  

Keep your AI momentum going...

Listen to our “Get peace of mind in the unknown with RPA and AI” podcast to hear Eric Kujala, Product Marketing Director at ICE Mortgage Technology, and Nolan Johnson, Sales Engineer, HPA at A Cognizant Company, discuss the key things to consider when evaluating RPA for your business. 

Plus, remember to register for Experience 2021 to access exclusive content to help you accelerate AI adoption, ask questions at live Q&A sessions with subject matter experts and connect with peers facing similar challenges on their AI journey.

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