Document review is still manual, and it is where deals slow down. Credit and onboarding teams still read files by hand. Documents arrive by email, sit in spreadsheets and shared drives, and get checked against a policy that lives in someone's head. Analysts lose hours reconciling numbers across statements, accounts, and contracts, and teams tell us manual due diligence costs at least 12 hours a week. The result is a slow time-to-yes, checks applied unevenly from one file to the next, and an audit trail you have to rebuild after the fact.

Three steps. Days of review become minutes. Ingest. Upload the data room: financials, bank statements, IDs, tax filings, valuations, and contracts. Any format, and multiple languages. Risk Llama classifies every document automatically and pulls the figures out for you. Analyse. The engine reads across the whole file and runs the checks you have defined. Repayment capacity, name and identity consistency, security and valuation, tax and financials reconciliation, sanctions and ownership. Your policy, your thresholds. Decide. Open the assessment report. Each check comes back pass, flag, or fail, with the evidence and the reason. You get a readiness score, a full audit trail, and a clear recommendation. Risk Llama is a copilot: the final call stays with your team.

The checks that matter, applied the same way on every file.

Repayment capacity. Reads the bank statements and financials, calculates the debt service coverage ratio, and tests it against your policy minimum.

Identity consistency. Confirms the same legal name across IDs, incorporation records, and signed agreements, and flags spelling mismatches that change legal identity.

Security and collateral. Checks valuations and security documents against the facility.

Numbers that should agree. Reconciles figures across audited accounts, tax filings, and the financial model, and flags gaps.

Structure and approval. Confirms the financing is documented and approved under the right structure, including Islamic finance structures where relevant.

Screening. Sanctions, ownership, and reputation signals.

Beyond the checklist. Surfaces issues your checklist did not think to ask for. Everything here is configurable to your taxonomy, products, and reporting. You tune it, with no vendor wait.

What it catches, on a real-world file. An illustrative SME working-capital facility. This is an example scenario, not a customer. On a single document set, Risk Llama flagged debt service coverage at 1.15x against the bank's 1.25x policy minimum, caught the borrower's name spelled two different ways across the passport and the signed financing agreement, confirmed the financing structure and Shariah approval were in order, and surfaced company revenue in the audited accounts that did not reconcile with the declared sales-tax figures. Days of manual review, compressed to minutes.

Built for credit risk. Useful anywhere you decide from documents. Credit risk and loan origination, trade finance, vendor and third-party onboarding, investment and M&A due diligence, and KYB and KYC onboarding.

Teams already run this at scale. Trade finance: 50 percent reduction in analyst workload with 24/7 monitoring. Multi-product fintech: 70 percent reduction in manual case reviews, and a shorter time-to-yes on high-value customers.

A single, auditable environment. Your data stays yours. One secure, auditable workspace with clear ownership and version history. Single-tenant deployment and data-residency options with Llama Vault. Your documents never train the model. Human-in-the-loop by design: Risk Llama recommends, your team decides.

See it read one of your files. Book a live demo and watch Risk Llama classify, check, and score it in minutes.