Question 1

What asset classes does Vishwa AI support?

Accepted Answer

Vishwa AI supports private credit, commercial real estate (CRE), CLOs, fixed income/bonds, and mortgage lending. The platform adapts to each asset class's specific metrics, document types, and underwriting frameworks.

Question 2

How does Vishwa AI handle CRE-specific analysis like NOI, Cap Rate, and DSCR?

Accepted Answer

Vishwa AI extracts data from rent rolls, operating statements, and property financials. It computes NOI, Cap Rate, DSCR, Debt Yield, and occupancy metrics automatically with cross-document validation.

Question 3

Can Vishwa AI process different financial statement formats across geographies?

Accepted Answer

Yes. Vishwa AI handles US GAAP and IFRS. It supports scanned, handwritten, and digital documents including financial statements, bank statements, borrowing base certificates, and tax returns.

Question 4

How does the AI handle ambiguous or missing data?

Accepted Answer

The system flags missing or inconsistent data rather than making assumptions. Analysts see exactly what was extracted, what could not be found, and what needs manual review.

Question 5

Can I customize underwriting templates, ratios, and credit policies?

Accepted Answer

Fully configurable. You define the ratios, KPIs, risk thresholds, and report templates. Vishwa AI applies your framework consistently across every deal.

Question 6

How does portfolio monitoring work for CLO and bond portfolios?

Accepted Answer

Automated ingestion of monthly and quarterly reports. Vishwa AI tracks covenant compliance, key metric drift, and surfaces early warning signals across the portfolio with drill-down to individual credits.

Question 7

What integrations do you support?

Accepted Answer

Native integrated intelligence inside MS Word and Excel, email and cloud drive ingestion, API access, and configurable export to Word/PDF. Vishwa AI works within the tools your team already uses.

Question 8

How do you handle multi-entity and holding company structures?

Accepted Answer

Vishwa AI can consolidate financials across entities, map intercompany relationships, and produce analysis at both entity and consolidated levels.

Question 9

What security and compliance certifications do you hold?

Accepted Answer

SOC 2 Type II, ISO 27001, GDPR, and CCPA certified. Vishwa AI is architected to meet requirements from US banking regulators and the EU AI Act.

Question 10

How quickly can our team get started?

Accepted Answer

Most teams are live within weeks. Vishwa AI adapts to your existing underwriting framework, so there is no need to change your process.

Question 11

What is an underwriting OS?

Accepted Answer

An underwriting OS runs the whole credit workflow in one place: document intake, financial spreading, risk analytics, credit memo generation, and portfolio monitoring. Instead of moving a deal between a data room, three point tools, and a stack of spreadsheets, you run it in one system. Vishwa AI applies your underwriting framework and credit policies the same way on every deal, and every output ties back to the source document it came from.

Question 12

What does 'outcome-as-a-service' mean for lending?

Accepted Answer

It means we hand you the finished work product, not just a tool to produce it. You get spread financials, a drafted credit memo, and a monitored portfolio. The AI does the extraction and the analysis, our experts verify the result, and your team reviews and signs off. You are not configuring software and hoping it works on your documents.

Question 13

Is AI underwriting auditable and explainable?

Accepted Answer

Yes. Every figure links to the source document and the calculation behind it, so when an examiner, an auditor, or an LP asks how you got a number, you can show them in one click. Vishwa AI applies the same logic to every deal and keeps a complete audit trail, which is usually the part manual spreading cannot reproduce six months later.

Question 14

How do you handle model governance and risk controls?

Accepted Answer

We keep a human in the loop on every extraction and analysis, version the models and prompts behind each output, and give your model risk team full traceability. The platform is built to line up with US banking supervisory expectations and the EU AI Act, so your second line can document and defend how it is used.

Question 15

Where is our data hosted, and do you support private deployment?

Accepted Answer

We offer data residency in the US, EU, and India, and we support single-tenant and VPC or private deployments for regulated institutions. Enterprise customers pick their region and isolation model, and nothing is shared across tenants.

Question 16

Should we build underwriting automation in-house or buy it?

Accepted Answer

Building it yourself means standing up document AI, spreading logic, model governance, and integrations, then keeping accuracy up as borrower documents and your credit policy change. That is a multi-quarter program with ongoing maintenance. Vishwa AI ships as a configured underwriting OS that adapts to your framework, so most teams reach production in weeks.

Question 17

How accurate is the extraction, and is there human review?

Accepted Answer

AI extracts, our experts verify, and your analysts review the exceptions. In practice that turns a multi-day spreading exercise into a quick validation. Credit businesses run up to 86% straight through, with people focused on the cases that actually need judgment rather than re-keying a T-12 into Excel.

Question 18

Does vishwa.ai have customers?

Accepted Answer

Yes. Vishwa AI runs in production at large enterprise clients across banking and private credit. Most of them prefer that we do not name them publicly, so we keep those relationships confidential. The product is mature and proven in the US market, and we are glad to walk through relevant, anonymized references under NDA on a call.

Question 19

Who uses vishwa.ai?

Accepted Answer

Large banks and private credit firms use Vishwa AI for live underwriting and portfolio monitoring. We do not publish a client list because our customers prefer to keep their use of the platform confidential. It is an established, production grade system in regulated US lending, not a pilot.

Question 20

Can you share customer references or case studies?

Accepted Answer

Our enterprise clients in banking and private credit prefer to stay anonymous, so we do not post named case studies. We can take you through real, anonymized outcomes and arrange references under NDA during a demo. Vishwa AI is a proven product in the US market, with enterprise deployments already in production.

Question 21

Is vishwa.ai proven, or is it early-stage?

Accepted Answer

Vishwa AI is a mature, production grade platform used by large enterprises across US banking and private credit. It is not a pilot stage tool. We keep client names confidential at their request, but the product is proven at scale in regulated US lending.

The AI Underwriting Platform for Private Markets

Book your demo

Safe, Secure & Private

Frequently Asked Questions