Automat Saves Top Bank 7 Figures in Mortgage Application Review Process
How Automat Saved a Leading Bank Seven Figures with RPA and AI Document Processing
In the competitive financial landscape, banks are constantly seeking ways to improve efficiency and reduce costs. For one leading bank, the mortgage application review process was a significant bottleneck—cumbersome, error-prone, and time-consuming. That’s where Automat stepped in, transforming the process with Robotic Process Automation (RPA) and AI document processing, ultimately saving the bank seven figures while enhancing accuracy and customer satisfaction.
The Mortgage Application Review Process: A Closer Look
The mortgage application review process typically involves several key steps:
- Initial Application: The applicant fills out a detailed form, either online or in-person, providing personal information, employment history, income details, and more.
- Document Submission: Applicants then submit a range of supporting documents, including proof of identity, income, bank statements, and tax returns. This stage often results in a mountain of paperwork for bank staff to manage.
- Credit Check: The bank checks the applicant’s credit score and history, a crucial factor in determining loan eligibility and interest rates.
- Loan Underwriting: Underwriters review all provided information, verifying employment, income, and the applicant’s ability to repay the loan. This step is critical and typically requires the most time and attention.
- Appraisal: An independent appraiser assesses the property’s value to ensure the loan amount is appropriate.
- Loan Approval or Denial: Based on the reviews, the underwriter decides whether to approve or deny the loan, issuing a commitment letter or a denial notice.
- Closing Process: If approved, the loan is finalized, documents are signed, and the property transfer begins.
The Challenges: Manual Processes and Inefficiencies
The bank faced significant challenges in managing this complex, document-heavy process. Manual data entry, document verification, and cross-referencing were time-consuming and prone to errors. Underwriters, burdened with these tasks, often found themselves overwhelmed, leading to delays in loan processing and potential mistakes that could have financial repercussions.
Automat’s Solution: Streamlining the Process with RPA and AI
Automat’s integration of RPA and AI document processing provided the bank with a transformative solution:
- Automated Data Extraction: Automat’s AI tools quickly and accurately extracted data from submitted documents, reducing the need for manual entry and minimizing errors.
- Efficient Document Verification: The AI could cross-check data across documents, flagging inconsistencies and missing information, ensuring that underwriters had accurate, complete information.
- Streamlined Routine Tasks: RPA automated repetitive tasks like initiating credit checks and ordering appraisals, freeing up staff to focus on more critical decision-making aspects of the process.
- Accelerated Underwriting: With much of the preliminary work automated, underwriters could focus on the essential aspects of risk assessment, significantly speeding up the underwriting process.
The Impact: Significant Savings and Improved Efficiency
The results were impressive. Automat’s technology not only reduced the time and effort required to process mortgage applications but also dramatically cut costs, saving the bank millions of dollars. With faster loan approvals and fewer errors, customer satisfaction increased, and the bank gained a competitive edge in the market.
Conclusion: A Future of Efficiency and Innovation
Automat’s success in transforming the mortgage application review process highlights the power of automation and AI in banking. By streamlining a traditionally cumbersome process, the bank achieved substantial cost savings and operational efficiencies. This case demonstrates that embracing cutting-edge technology is not just about reducing costs—it’s about positioning for future innovation and enhanced customer experiences.
