How we validate
Structured intelligence across every financial data type.
Prajna AI ingests structured data, unstructured documents, images, and transaction XML — applying DocuLens, VizAIo, GrasPh, and AINalyzer according to each data type and business workflow. Every output is confidence-scored, field-traceable, and designed to survive compliance review.
Regulatory & compliance
Standards your banking teams will recognize
These are not marketing claims. Each reflects real datasets, enterprise integrations, and compliance frameworks used in production banking environments.
Validated use cases
Transform banking workflows with AI-driven intelligence across onboarding, risk, lending, compliance, and analytics. Prajna AI enables faster decisions, reduced operational effort, and improved accuracy by connecting data, documents, and transactions into a single intelligent layer.
AI Powered End-to-End Risk Intelligence
Establish a unified, AI-driven framework for customer onboarding, identity verification, and real-time fraud detection across the financial lifecycle.
Leverage document intelligence to automate KYC onboarding and ensure regulatory compliance, while simultaneously applying graph-powered analytics to detect fraud, uncover hidden relationships, and monitor transaction behavior in real time.
Move beyond siloed onboarding and fraud systems to a continuous intelligence model—where identity, behavior, and risk signals are interconnected—enabling faster decisions, stronger compliance, and proactive risk mitigation.
- Disconnected KYC and fraud detection systems
- Manual onboarding and fragmented verification workflows
- Rule-based fraud detection with limited context
- High false positives and delayed investigations
- Limited visibility into entity relationships and risk patterns
- End-to-end intelligent onboarding and fraud monitoring
- Automated document extraction, validation, and compliance scoring
- Graph-based entity resolution and relationship intelligence
- Real-time fraud detection with contextual risk signals
- Explainable, audit-ready decisions across the lifecycle
Deal & Due Diligence Intelligence
Accelerate investment and corporate banking due diligence with AI-powered document intelligence and connected financial insights. DocuLens extracts critical information from contracts, agreements, financial statements, and regulatory documents, while GrasPh connects entities, transactions, and obligations across multiple documents to uncover hidden relationships and potential risks. AINalyzer transforms complex financial data into conversational insights, enabling analysts to evaluate deals faster, strengthen compliance, and make confident investment decisions.
- Manual contract and report analysis
- Slow deal cycles
- Risk of missed insights
- Automated due diligence workflows
- Cross-document intelligence
- Risk and compliance insights in real time
Global Liquidity Positioning to Interest Optimization
Transform fragmented multi-entity account balances into unified treasury intelligence. GrasPh connects accounts, entities, currencies, and transactions into a unified financial knowledge graph, while AINalyzer delivers real-time treasury analytics, liquidity forecasting, and interest optimization. Together, they enable banks to optimize notional pooling, reduce borrowing costs, and maximize returns across regions, currencies, and business units.
- Fragmented visibility across accounts, entities, and regions
- Idle liquidity in some entities while others incur overdraft costs
- Manual reconciliation and delayed treasury decision-making
- Lack of real-time insight into interest cost vs yield impact
- Multi-entity liquidity consolidation across accounts and currencies
- Surplus vs deficit identification across entities and regions
- Interest optimization modeling (cost vs yield simulation)
- Real-time liquidity distribution and imbalance detection
- Predictive liquidity positioning using historical and live data
AI-Powered Financial Insight at Scale
Transform financial documents into actionable business intelligence with AI-powered document understanding, connected knowledge, and conversational analytics. DocuLens extracts and structures information from financial statements, annual reports, regulatory filings, and audit documents. GrasPh connects entities, financial metrics, and relationships across multiple documents, while AINalyzer enables natural language exploration, executive summaries, and decision-ready insights—eliminating manual analysis and accelerating financial decision-making.
- Manual review of lengthy documents
- Time-intensive financial analysis
- Disconnected insights across reports
- Instant document summarization
- Natural language querying across documents
- Cross-document contextual understanding
Transaction Intelligence & ISO Data Mapping
Modernize payment operations with AI-powered transaction intelligence across ISO 20022, SWIFT, CAMT, MT940, BAI2, and other financial messaging standards. DocuLens extracts and normalizes payment and transaction data from structured and semi-structured sources, GrasPh connects accounts, counterparties, transactions, and payment flows into a unified knowledge graph, and AINalyzer delivers real-time reconciliation insights, conversational analytics, and operational reporting to improve payment visibility and efficiency./b>
- Manual reconciliation processes
- Inconsistent data formats
- Limited visibility into transactions
- Automated transaction mapping
- Unified transaction intelligence
- Real-time reconciliation insights
AI-Assisted Credit & Lending Decisions
Accelerate credit underwriting and lending decisions with AI-powered document intelligence, connected risk analysis, and predictive analytics. DocuLens extracts and validates borrower information from financial statements, loan applications, income proofs, tax documents, and credit records. GrasPh uncovers relationships between borrowers, guarantors, accounts, transactions, and organizations to identify hidden risks, while AINalyzer generates predictive credit insights, risk scores, and lending recommendations that enable faster, more informed decisions.
- Static credit scoring models
- Limited data utilization
- Manual risk assessment
- AI-driven credit profiling
- Multi-source data integration
- Predictive risk scoring and insights
AI Powered End-to-End Risk Intelligence
Establish a unified, AI-driven framework for customer onboarding, identity verification, and real-time fraud detection across the financial lifecycle.
Leverage document intelligence to automate KYC onboarding and ensure regulatory compliance, while simultaneously applying graph-powered analytics to detect fraud, uncover hidden relationships, and monitor transaction behavior in real time.
Move beyond siloed onboarding and fraud systems to a continuous intelligence model—where identity, behavior, and risk signals are interconnected—enabling faster decisions, stronger compliance, and proactive risk mitigation.
- Disconnected KYC and fraud detection systems
- Manual onboarding and fragmented verification workflows
- Rule-based fraud detection with limited context
- High false positives and delayed investigations
- Limited visibility into entity relationships and risk patterns
- End-to-end intelligent onboarding and fraud monitoring
- Automated document extraction, validation, and compliance scoring
- Graph-based entity resolution and relationship intelligence
- Real-time fraud detection with contextual risk signals
- Explainable, audit-ready decisions across the lifecycle
Deal & Due Diligence Intelligence
Accelerate investment and corporate banking due diligence with AI-powered document intelligence and connected financial insights. DocuLens extracts critical information from contracts, agreements, financial statements, and regulatory documents, while GrasPh connects entities, transactions, and obligations across multiple documents to uncover hidden relationships and potential risks. AINalyzer transforms complex financial data into conversational insights, enabling analysts to evaluate deals faster, strengthen compliance, and make confident investment decisions.
- Manual contract and report analysis
- Slow deal cycles
- Risk of missed insights
- Automated document extraction and due diligence workflows
- GrasPh powered Cross-document intelligence
- Risk and compliance insights in real time
Global Liquidity Positioning to Interest Optimization
Transforms fragmented multi-entity account balances into unified treasury intelligence — enabling banks to optimize notional pooling, minimize borrowing costs, and maximize yield across regions, currencies, and business units using real-time liquidity insights.
- Fragmented visibility across accounts, entities, and regions
- Idle liquidity in some entities while others incur overdraft costs
- Manual reconciliation and delayed treasury decision-making
- Lack of real-time insight into interest cost vs yield impact
- Multi-entity liquidity consolidation across accounts and currencies
- Surplus vs deficit identification across entities and regions
- Interest optimization modeling (cost vs yield simulation)
- Real-time liquidity distribution and imbalance detection
- Predictive liquidity positioning using historical and live data
AI-Powered Financial Insight at Scale
Analyze financial documents using AI-powered document intelligence for banking to extract insights instantly. Process financial statements, reports, and regulatory filings without manual review. Enable natural language search and document Q&A for faster access to critical data. Perform cross-document analysis to uncover relationships and trends. Improve decision-making with automated financial document summarization and insight generation.
- Manual review of lengthy documents
- Time-intensive financial analysis
- Disconnected insights across reports
- Instant document summarization
- Natural language querying across documents
- Cross-document contextual understanding
Transaction Intelligence & ISO Data Mapping
Enable ISO 20022 and payment data processing using AI in banking systems for accurate transaction analysis. Interpret complex formats such as SWIFT, CAMT, MT940, and BAI2. Automate reconciliation and normalization of transaction data. Provide real-time transaction monitoring and reporting insights. Improve operational efficiency with structured and unified transaction intelligence.
- Manual reconciliation processes
- Inconsistent data formats
- Limited visibility into transactions
- Automated transaction mapping
- Unified transaction intelligence
- Real-time reconciliation insights
AI-Assisted Credit & Lending Decisions
Enhance credit risk assessment and lending decisions using AI in banking with predictive analytics. Analyze borrower data from multiple sources including financial records and behavioral signals. Enable AI-driven credit scoring and loan decision automation for faster approvals. Identify hidden risks using graph-based relationship intelligence. Improve portfolio performance with data-driven lending strategies and risk insights.
- Static credit scoring models
- Limited data utilization
- Manual risk assessment
- AI-driven credit profiling
- Multi-source data integration
- Predictive risk scoring and insights
Before and after
What changes when you switch from reactive to predictive banking intelligence
| Dimension | Current Approach | With Prajna AI |
|---|---|---|
| KYC & Onboarding | Manual document review Compliance staff verify documents manually — slow, costly, and inconsistent across clients |
Automated verification pipeline DocuLens automates document intake, identity verification, data extraction, and onboarding workflows with complete audit trails. |
| Financial analysis | Spreadsheet-based KPIs Weekly manual consolidation from multiple systems with high error risk and stale data |
Real-time intelligence dashboards AINalyzer delivers conversational analytics, KPI dashboards, forecasting, and executive insights from structured banking data. |
| Compliance & risk | Reactive monitoring Breaches and suspicious activity identified after the fact — exposure to fines and reputational damage |
Proactive threat intelligence GrasPh, AINalyzer, and VizAIo deliver continuous monitoring, relationship intelligence, anomaly detection, and real-time operational visibility across digital and physical banking environments. |
| Payment operations | Manual reconciliation Cross-border payments involve multiple intermediaries, manual FX steps, and opaque tracking |
Automated payment intelligence AINalyzer and GrasPh automate reconciliation, connect payment entities, and provide real-time visibility into transaction flows and payment intelligence. |
| Document processing | Fragmented document handling Financial reports, invoices, and contracts processed across disconnected systems with heavy manual effort |
Unified document intelligence layer DocuLens extracts, validates, classifies, and structures banking documents into actionable intelligence for downstream workflows. |
| Decision-making | Delayed, reactive decisions Insights generated after data consolidation, limiting responsiveness to market changes |
Real-time, proactive insights AINalyzer, powered by GrasPh and DocuLens, delivers real-time insights that enable faster, explainable, and data-driven banking decisions. |
Agentic framework
Five layers. All traceable.
Each layer of the Prajna AI banking framework is independently auditable and aligned to enterprise-grade financial data, compliance, and operational intelligence standards.
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