Fortune 500 bank automates financial document operations, cutting costs 90%

Manual, Error-Prone Processing

Financial statement validation is one of banking’s most operationally dense workflows. 

Every incoming statement must be classified by type, parsed for key financial data, cross-checked against regulatory thresholds, and entered into downstream systems. 

For this institution, a single case required an average of 28+ hours to resolve. The dedicated team working this process full-time represented a significant and growing line item on the operational budget, and was an expert resource that could be deployed elsewhere.

The problem was structural: 

• Cycle times were too long to meet tightening internal SLAs. 
• Error rates introduced material operational and compliance risk: a misclassified statement or a missed data point could cascade into regulatory exposure. 
• The talent pipeline was thinning. Experienced validators with the domain knowledge to handle complex, multi-entity statements were increasingly difficult to recruit and retain.

The bank had explored conventional automation approaches, including rule-based extraction tools and workflow automation, but none could handle the variability inherent in financial statements: different formats, different issuers, different regulatory regimes. 

Partial automation created new bottlenecks rather than eliminating old ones: documents still required manual review at nearly every stage, and exceptions consumed more time than the original process.

The cost of inaction was quantifiable: rising per-case costs, headcount pressure that scaled linearly with volume, and a compliance surface area that grew with every manual touchpoint.

Autonomous AI Agents for Financial Operations

The bank aligned on a single operational objective: shift financial statement processing from a headcount-dependent manual operation to autonomous execution, where AI agents handle cases from intake to resolution and human specialists intervene only on exceptions.

Systems and data sources

Otera connected to the bank’s document intake channels, financial data repositories, and core banking validation systems. 

The integration operated alongside existing infrastructure with no changes required to core banking systems, a non-negotiable requirement given the institution’s regulatory and change-management constraints.

The agent workflow

Otera deployed a coordinated set of autonomous agents, each responsible for a distinct stage of the financial statement lifecycle:

• Intake Agent: Receives incoming financial statements from all intake channels, identifies the document type (annual report, balance sheet, income statement, regulatory filing), and routes it into the processing pipeline.
• Data Capture Agent: Parses each statement regardless of format, issuer, or structure. Then, it extracts key financial fields (revenue, liabilities, equity positions, ratios, and regulatory identifiers), and handles the format variability that defeated prior rule-based tools.
• Validation and Cross-Check Agent: Applies multi-layered validation: internal consistency checks across extracted fields, cross-referencing against regulatory thresholds and historical data, and flagging anomalies for escalation. This agent replaces the most time-intensive manual step in the legacy process.
• Exception Routing Agent: Cases that fall below confidence thresholds or trigger anomaly flags are routed to the human review team with the agent’s preliminary analysis, extracted data, and specific reason for escalation attached. Reviewers resolve the exception while the system learns from each resolution.

Governed autonomy

Every agent decision is logged with a full audit trail: what data was extracted, what validation rules were applied, what confidence score was assigned, and whether the case was resolved autonomously or escalated. 

Operators maintain complete visibility into agent behavior and can override any decision, which means this is autonomous execution under institutional governance, built to satisfy the scrutiny of European banking regulators. 

90% cost reduction and 2x faster end-to-end processing

Within weeks of go-live, autonomous execution became the default operating mode. 

The majority of financial statements now process from intake to validated output without human intervention:

• Annual process costs dropped 90%. The dedicated team that previously worked this process full-time was reduced by 85%, with remaining specialists focused exclusively on exception resolution and quality oversight. The freed capacity was redirected to higher-value analytical and client-facing functions. 
• Resolution time fell from 28+ hours to under 15 hours per case. The bottleneck that previously defined the operation (manual validation queues measured in days) was eliminated. Throughput is no longer constrained by available headcount, meaning the bank can absorb volume growth without proportional cost increases.
• Full audit traceability is built into every transaction. Every agent decision, extraction, and validation is logged and retrievable. Fewer manual touchpoints means fewer points of human error, and every automated decision carries a verifiable audit record.