Lenders must ingest and analyze large volumes of unstructured documents across loan origination, underwriting, servicing, and risk management. BizAI enables the automated ingestion, analysis, and validation of loan documentation. By automating these traditionally manual processes, BizAI reduces risk by improving accuracy, reduces operational burden, and delivers a meaningful competitive advantage by reducing loan origination costs.

Lenders must ingest and analyze large volumes of unstructured documents across loan origination, underwriting, servicing, and risk management. In many cases, they are also required to process documents in multiple languages.

BizAI provides native support for more than 50 languages and over 150 file types, enabling the automated ingestion, analysis, and validation of loan documentation. By automating these traditionally manual processes, BizAI improves accuracy, reduces operational burden, and delivers a meaningful competitive advantage.

Fisent BizAI can be used to enable the automation of wealth account transfers. In this demo, we showcase the power of BizAI to analyze, validate, and extract unstructured data elements from wealth account statements. Automating aspects of a wealth account transfer can significantly reduce manual time and effort, reduce the risk of costly errors, and improve both customer and employee experience.

Mortgage lenders must process hundreds of Purchase Advice (PA) documents each week from multiple investors, each with its own format, structure, and naming conventions. These PAs confirm secondary market transactions, outlining the terms, wire details, and purchase adjustments.

Historically, post-closing teams manually keyed critical fields—such as Investor Loan Number, Purchase Date, and First Payment Due Date—into loan systems, creating bottlenecks, error risks, and reconciliation delays between the lender’s core system(s) and investor reporting.

Key challenges included:

• High document variability across investors and loan types
• Time-consuming manual review of PDF and Excel-based PAs
• Inconsistent field naming conventions (e.g., 30+ aliases for “Investor Loan Number”)
• Limited integration between extracted data and accounting systems
• Increased operational cost and turnaround pressure during investor delivery windows

Connection’s accounting and credit teams manually validated 60,000+ incoming sales orders against existing customer POs. This included verifying specifications, pricing, buyer approvals, and service-level commitments.

Traditional automation tools struggled with variability — dozens of document formats, inconsistent layouts, and small discrepancies (e.g., address, Part ID, or SKU mismatches) — resulting in high manual review volumes, long cycle times, delayed order fulfillment, and revenue recognition.

The company needed a secure and scalable automation solution that could manage these high-volume transactions with human-level accuracy and handle exceptions intelligently rather than relying on template-based rules.