Document-heavy work can be difficult to plan for. Loan volume changes. A large transaction can suddenly increase the number of files that need to be reviewed. Audits, investor requests, and servicing activity can create additional work with little warning.
That creates a challenge when choosing document technology. How much capacity should you pay for? Which processes should you automate first? What happens if your volume drops?
For teams considering document AI, the answer does not have to be a large commitment from the start. Focus on a problem you already have, understand what you are paying for, and expand when there is a reason to.
Start With the Document Work Taking Up Time
Look at the work your team is doing manually today.
Employees may be sorting and organizing loan files, searching documents for specific information, rebuilding packages to meet investor stacking requirements, or reviewing mortgage payment histories across multiple servicers. These are defined processes where the time and effort involved can be identified.
organizing files
information
packages
histories
AiCR can classify and index documents, extract data, organize loan packages, review mortgage payment histories, and deliver structured information for audits, transactions, and reporting.
Avoid Paying for Capacity You Are Not Using
Document volume does not stay the same from month to month. Paying for unused capacity during slower periods can make it harder to justify the investment.
AiCR uses usage-based pricing with no monthly minimums and no long-term commitments. Clients pay for the documents they actually process.
When volume increases, usage can increase with it. When volume slows, costs can come back down. Teams do not have to predict how much capacity they may need months from now and commit to paying for it upfront.
Expand When It Makes Sense
Starting with one workflow does not mean that is the only way the technology can be used.
A lender may begin with investor stacking orders and later identify data that could be extracted from the same loan files. A due diligence team may start with mortgage payment history review and later find another document process worth automating.
The next use can come from an actual need rather than a decision made before the technology was implemented.
AiCR was developed from within MIAC Analytics, where teams have spent more than 35 years working across mortgage valuation, due diligence, loan trading, risk management, and other document-intensive financial processes. That experience helped shape a platform built around the way this work actually arrives: volumes change, requirements change, and the next need is not always known in advance.
Start With the Work You Have Now
Getting started with document AI does not require knowing every way you may eventually use it. Identify one process taking up your team’s time, understand what it costs today, and determine whether automation can improve it.
Tell us where document work is taking up your team’s time. We’ll show you how AiCR could support the workflow and what usage-based pricing could look like for your organization.