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Relieving the Data Supply Chain Bottleneck in Mortgage Loan Manufacturing
Data Supply Chain Bottleneck

Supply chain disruption hinders any manufacturing process, including loans. TRUE reliably automates the data supply chain, making loan manufacturing faster and more efficient. 

Mortgage lenders often refer to loan origination as “loan manufacturing.” It makes sense: like any assembly process, a loan requires materials and parts to be brought together to produce a final product. The quality of that product – its suitability, durability, and availability – depends not only on the design of the factory process but also access to a steady flow of quality materials and parts. 

Think of a carmaker building a car. Its inputs are metals and plastics, wiring looms and electronics, glass and rubber. For a lender to build a mortgage those inputs are documents: bank statements, paystubs, W2 earning and tax statements, identification documents, and property appraisals.  

Quality and speed in the data supply chain 

Managing the supply chain is critical to manufacturing success. With cars, the pandemic revealed why that’s so important. Disruption has famously led to factory slowdowns and stoppages. Car buyers face longer waiting lists and higher prices. Carmakers have lost revenue as buyers seek alternatives or abandon purchases altogether.  

Problems with the supply of documents hold a similar threat for mortgage lenders. Poor document quality, mistakes, and information gaps all hold up the loan manufacturing process. Origination takes longer or cannot be completed, causing wasted time and worthless expense. Borrowers may report a bad customer experience and leave negative reviews. 

Compared with carmakers, mortgage lenders don’t enjoy anything approaching the level of control over their supply chain. Instead, lenders must take whatever documents are provided and run checks for quality and completeness. They must extract the relevant data about the borrower, assess the veracity of the documents (both individually and collectively), and verify the accuracy of the data extraction process itself.  

The bottleneck of human capacity 

Mortgage operations professionals know that conversion of documents into data, and data verification, are laborious yet complex tasks. They also understand that they are mission critical.  

Skimping on data accuracy raises costs further along the production line: when accuracy is off by as little as 5 percent it decreases productivity by 30 percent or more. Inaccurate data also creates risk: the integrity of data extraction and verification processes determine whether a mortgage is properly risk-assessed, priced, and compliant.  

The data bottleneck has long frustrated operations leaders – and it is getting tighter. Expanding in-house teams was traditionally the best option for adding capacity without compromising quality, but this loads the business with highly salaried employees at a time of volatile demand.  

Outsourced teams are more flexible, but quality is harder to manage and costs are not significantly lower. Offshoring used to offer a lower cost option, but fees have risen as other economies have matured. Meanwhile, there is increased concern about the risks of transferring customer data into overseas jurisdictions.  

Specialized technology for skilled tasks 

Returning to our analogy, carmakers have used automation – robotics – to boost productivity when human skills are unavailable or too costly. Many lenders have also invested in automation platforms, but the docs-to-data and verification components of these systems have disappointed with poor accuracy. People are routinely needed to step in and figure things out.  

Constant human monitoring of technology undermines its value. Operations leaders are left to figure out some awkward combination of people and technology in the hopes of increasing productivity, or else give up on automation altogether.  

Some lenders have discovered a different option. TRUE provides task-focused artificial intelligence for docs-to-data conversion and verification. Like skilled human operatives, the TRUE platform is trained in the lifecycle and language of loans. It is uniquely able to review documents contextually, seeing the connections between the borrower and their data, and building a complete picture.  

This allows TRUE products – Trapeze for docs-to-data conversion, VerifAI for data verification – to slot neatly into data supply chain tasks and deliver fully automated performance – no humans in the loop. 

Task specialization means TRUE products consistently surpasses human performance. They work out of the box, but the underlying AI learns the specific needs of different loan manufacturing processes and continually improves. Soon enough, operations leaders see that they can trust the accuracy of automated data, allowing them to deploy skilled human resources where they can add more value. 

With TRUE, lenders can efficiently scale up in busy times without the burden of high fixed costs in fallow periods. The result is a mortgage-making factory in control of its data supply chain, ensuring consistent quality and readily adapting to demand.