Financial Services
Expense Management
IDP

Commercial Bank Speeds Processing, Gains Muscles to Manage Demand Peaks

Ideal for financial analysts and report managers, this case study demonstrates how AI-enabled data extraction revolutionizes annual report analysis
Intelligent ratio comparison A
Accounting rule automation S
Seamless cross-referencing
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It takes a long time and multiple hands to translate as well as extract data with precision, especially with a volume like ours of 20,000,000/annum. Infrrd saved us time and cost involved in the process by about 63%

Commercial Bank Speeds Processing, Gains Muscles to Manage Demand Peaks

A large commercial bank creates a loan risk rating based, in part, on data from the client firm’s financial statements and annual reports. If the loan risk is high, then the bank takes action to address issues.

The bank uses data from annual reports, financial statements, tables, and unstructured documents to assess portfolio risks.

It needs to extract data, cross-reference, generate insights, and report, but the documents’ complexity means the bank needs to use skilled staff to accurately complete these tasks. It’s a slow and costly process.

Read the use case to learn how the bank:

  • Reduced time to assess financial risk.
  • Increased process scalability and ability to handle demand peaks.
  • Freed up business analyst time to work on higher-value tasks.

Infrrd. Redefine Possible.

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