Manual capture of loan agreement data slows down closing work

Starting point

The bank mainly grants corporate loans with individual contract terms. Around 600 new loan agreements are created every month, and they must be captured completely and correctly in the core banking system and financial accounting for closing, reporting and regulatory filings. Until now, clerks did this manually: they opened the digital contract documents, looked for relevant fields such as term, interest rate, repayment terms, collateral and covenants, and transferred the information into several input screens. This took 20 to 30 minutes per agreement on average, and considerably longer for complex cases. At peak times, up to eight employees worked almost exclusively on this data capture, while other accounting tasks were left undone.

The challenge

Capturing loan agreement data manually was not only time-consuming but also error-prone. Different contract layouts, appendices and amendments made it hard to find one's way around. Important fields were overlooked or misinterpreted, for example interest rate adjustment clauses or special repayment rights. Corrections were often made only during closing preparations, when discrepancies between the loan portfolio and the general ledger came to light. This led to queries to sales and delays in monthly and quarterly closings. At the same time, pressure grew from regulatory requirements demanding a timely and consistent data basis. The department was looking for a way to speed up data capture without creating additional positions or compromising quality.

Why this remained unsolved

The bank had analyzed the process several times and concluded that full automation with conventional means would hardly be economical. The contract documents were heterogeneous and contained free-text clauses and handwritten additions. A rigid form-based system would have required extensive adjustments for every new contract layout. At the same time, the process was considered too small-scale for a large IT project, yet too critical to ignore. The department feared that automation could crowd out the necessary expert review and create regulatory risks. So it remained a matter of minor optimizations such as checklists and templates, without solving the core of the problem.

The bank introduced a solution for automated data extraction from loan agreements that takes targeted pressure off specialists without replacing their role. Contract documents are imported centrally, analyzed in a structured way, and relevant fields such as loan amount, term, interest mechanics, repayment schedule, collateral and covenants are extracted. The extracted data is brought together in a review interface where accounting checks the suggestions, flags uncertainties and makes corrections where needed. Only after approval is the data written to the core banking system and downstream finance modules via defined interfaces. The solution recognizes different layouts, works with multilingual documents and flags uncertain extractions, so specialists can focus on the demanding cases.