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Use Cases for Applying AI in Credit Underwriting for banks, lenders, and credit unions.
1. Build High Conversion Borrower Applications
Use automation to strengthen digital loan origination by improving borrower experience at first application.
A high conversion application should make a credit application:
Simple for the borrower to provide all their information.
Seamless for bankers to analyze for a decision
2. Automate Financial Statements for Borrowers
Gathering, verifying, and spreading borrower financials in a credit workbook is a complex process and is the root of most friction within a credit application.
SOLO's front facing borrower onboarding portal was developed to eliminate friction for borrowers and the bankers underwriting their loans.
01 PULL autofills an application and automates financials statements according to the lender's accounting methods from a borrower's raw data, including:
Balance sheets.
Income statements (profit and loss statements).
Cash flow statements.
On demand, from just their connected accounts and uploaded documents. Learn how we're powering the shift from self reported financial statements to autonomously generated financials.
3. Verify Borrower Income Across Documents, Including Tax Returns
Underwriters typically cross reference pay stubs, tax returns, and W-2 forms to verify the borrower's income.
SOLO's Document Uploader tool reads unstructured data from any group of documents, and extracts every data point needed for a verification. So underwriters and borrowers can upload anything, and pull borrower information directly into the file format needed for credit teams.
4. Pull Borrower Details From Unstructured Data
Use AI to read unstructured data in the form of PDFs, Rich-Text Files, .PNG or .JPEGs, etc submitted as credit application documents for ingesting into underwriting workflows.
SOLO's Document Uploader tool reads unstructured data from any group of documents, and extracts every data point needed for a verification. So underwriters and borrowers can upload anything, and pull borrower information directly into the file format needed for credit teams.
5. Apply Custom Credit Scoring Frameworks per Product
A major opportunity unlocked by ai for credit underwriting is the new ability to create systems that make context aware credit decisions viable at scale.
A context aware credit decision processes significantly more data points, run through tailored scoring frameworks that consider more nuances of creditworthiness in addition to a standard credit score. Automation can give lenders the power they need to fully consider borrower creditworthiness in every context, for every product, with a unique scoring framework for each instance.
6. Proactively Underwrite by Automating Calculations for Real Time Data
Once automation is properly applied at the beginnings of the underwriting process for credit document collection, standardization, and activation data can be leveraged to unlock opportunities over and over again.
7. Generate Custom Roadmaps for Customers to Track Their Progress
Once automation is properly applied at the beginnings of the underwriting process for credit document collection, standardization, and activation data can be leveraged to unlock opportunities over and over again.
SOLO 01 for Credit Underwriting
Automate Your Credit Underwriting Workbook
Automation in underwriting processes isn't just for speeding up decisions. AI appropriately applied to the beginning of the underwriting process, at first point of data collection and activation, can reduce friction and risk simultaneously in digital lending. The result speeds up decisions while enhancing the integrity of a decisioning algorithm.
