Finance & Banking Application Catalogue¶

Enterprise AI applications for banking and financial services operations, powered by the Semantic Ontology Layer.

Data Plane Overview¶

The application catalogue draws from a unified data plane spanning core banking systems, CRM, lending platforms, and semi-structured financial data sources:

graph TD
    subgraph Data Plane
        CBS["Core Banking System<br/><i>Accounts, Transactions, Balances, Deposits</i>"]
        SFSC["Salesforce Financial Services Cloud<br/><i>Relationships, Advisory, Leads, Opportunities</i>"]
        LOS["Loan Origination System<br/><i>Applications, Underwriting, Collateral, Collections</i>"]
        MKT["Market Data & News<br/><i>Prices, Rates, Indices, Economic Indicators</i>"]
        DMS["Document Management<br/><i>KYC Docs, Loan Files, Contracts, Compliance</i>"]
        AML_SYS["Transaction Monitoring<br/><i>AML Alerts, SAR Filings, Watchlists</i>"]
    end

    subgraph Semantic Ontology Layer
        ONT["Unified Banking Ontology<br/><i>Entity Resolution · Relationship Mapping · Business Rules</i>"]
    end

    subgraph Application Catalogue
        C360["Customer 360"]
        CREDIT["Credit Risk"]
        FRAUD["Fraud & AML"]
        REG["Regulatory Compliance"]
        TREASURY["Treasury & Liquidity"]
        LOAN["Loan Lifecycle"]
        REVENUE["Revenue & Product Reco"]
        OPRISK["Operational Risk"]
    end

    CBS --> ONT
    SFSC --> ONT
    LOS --> ONT
    MKT --> ONT
    DMS --> ONT
    AML_SYS --> ONT

    ONT --> C360
    ONT --> CREDIT
    ONT --> FRAUD
    ONT --> REG
    ONT --> TREASURY
    ONT --> LOAN
    ONT --> REVENUE
    ONT --> OPRISK

Application Catalogue¶

P0 — Immediate ROI¶

Application	Primary Data Sources	ROI Signal	Time to Value
Customer 360 & Relationship Intelligence	CBS, Salesforce FSC, LOS, AML	Increase cross-sell 15-25%, reduce churn 20-30%	4-6 weeks
Credit Risk & Early Warning System	LOS, CBS, Market Data, Documents	Reduce NPAs 20-35%, improve ECL accuracy 40%	4-6 weeks

P1 — High Value¶

Application	Primary Data Sources	ROI Signal	Time to Value
Fraud Detection & AML Intelligence	CBS, AML System, Documents, Market Data	Reduce false positives 40-60%, cut investigation time 50%	6-8 weeks
Regulatory Compliance & Reporting Automation	CBS, LOS, Documents, Market Data	70% reduction in reporting effort, zero regulatory penalties	6-8 weeks

P2 — Strategic Value¶

Application	Primary Data Sources	ROI Signal	Time to Value
Treasury & Liquidity Optimization	CBS, Market Data, Salesforce FSC	Optimize liquidity buffer 10-15%, improve NIM 5-10 bps	8-10 weeks
Loan Lifecycle Intelligence	LOS, CBS, Documents, Market Data	Reduce origination TAT 40%, improve recovery rate 15-20%	8-10 weeks

P3 — Operational Excellence¶

Application	Primary Data Sources	ROI Signal	Time to Value
Revenue & Product Recommendation Engine	CBS, Salesforce FSC, Market Data	Increase fee income 8-12%, improve product penetration 20%	10-12 weeks
Operational Risk & Process Mining	All Systems, Documents, AML	Reduce operational losses 25-30%, improve audit readiness 60%	10-12 weeks

Ontology Entity Map¶

Key business entities resolved across systems by the Semantic Ontology Layer:

Business Entity	Core Banking System	Salesforce FSC	Loan Origination System
Customer	CIF / Customer Master	Account / Contact / Household	Borrower / Co-Borrower
Account	Deposit / Current / FD / Savings	Financial Account	Loan Account
Transaction	Ledger Entry / Statement Line	—	Repayment / Disbursement
Product	Product Catalog / Scheme	Opportunity Product	Loan Product / Scheme
Instrument	Security / Investment Holding	—	Collateral / Guarantee
Relationship	Joint Holder / Nominee / PoA	Relationship Group	Guarantor / Co-Applicant

Architecture Pattern¶

Every application in this catalogue follows a consistent execution pattern:

flowchart LR
    A["Ontology Layer<br/><i>Resolved Entities</i>"] --> B["AI Workflow Engine<br/><i>LLM + Business Rules</i>"]
    B --> C["Dashboard & Alerts<br/><i>Real-time Visualization</i>"]
    B --> D["Action Layer<br/><i>Recommendations · Automation</i>"]

Data Ingestion — Ontology layer resolves entities across Core Banking, Salesforce FSC, Loan Origination, and semi-structured sources
AI Workflow Execution — LLM-powered pipelines apply business logic, anomaly detection, risk models, and predictive analytics
Presentation — Dashboards surface KPIs; alerts trigger on threshold breaches and regulatory limits
Action — Recommendations feed back into source systems or trigger automated workflows (credit decisions, compliance filings, customer outreach)

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