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Finance

From credit risk diagnosis to performance analysis, with verifiable evidence

Unifies loan databases, policy documents, and market data through an ontology, delivering risk diagnosis and performance analysis with verifiable grounds.

Challenges

Finance: Today's Challenges

Scattered Credit Information

Borrower details, collateral, and covenant terms are spread across systems and documents, making holistic risk diagnosis difficult.

Regulatory Compliance Burden

When supervisory rules or internal regulations change, affected products and processes must be traced by hand.

Performance Mart Query Bottleneck

Competitiveness and performance queries pile up in the data department, delaying business decisions.

Use Cases

Use cases drawn from real demonstration scenarios

Q.Give me a comprehensive risk diagnosis of this loan

Combines borrower financials, covenant documents, and market data to lay out the risk factors with evidence.

Q.Show last month's top 10 branches by competitiveness metrics

The ontology interprets the performance mart's complex aggregation logic, returning accurate rankings with the SQL as evidence.

Q.Which products are affected by this regulatory amendment?

Semantically links regulation provisions to product terms, automatically deriving the scope of impact.

Impact

Impact

Credit risk diagnosis

BeforeManual compilation across systems
AfterComplete with a single unified query

Performance query turnaround

BeforeDays waiting on the data team
AfterMinutes, run directly by business staff

Answer verifiability

BeforeOpaque calculations
AfterSQL and source documents presented together

Reference — Intelligent workspace contract won with a major financial institution; NL2SQL PoC accuracy verified with a Korean securities firm

Finance — want to see it with your own data?

We'll arrange a demo tailored to your data environment and a 4–6 week PoC.