Lending & AI Glossary
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Lending Architecture
- LOS vs LMS
- Payment Allocation
- Interest Engine
- Core Banking Integration
Accounting & Control
- Ledger vs GL
- Accounting Events
- Reconciliation
- Auditability
AI for Financial Services
- Document AI
- AI Evaluation
- RAG
- AI Gateway
Private AI
- Private vs Public AI
- Governance
- Model Runtime
- Managed Operations
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What is the difference between LOS and LMS?
A practical explanation of how a Loan Origination System (LOS) differs from a Loan Management System (LMS) and where they connect.
Read article →What is a Loan Management System (LMS)?
Understand how an LMS manages loan accounts, schedules, interest, fees, payments and lifecycle events after approval.
Read article →What should an end-to-end lending platform include?
A practical capability map from product design, LOS and LMS to collateral, collections, litigation, integration and reporting.
Read article →What should a collection management system do?
From delinquency events to strategy, work queues, customer contact, payment, restructuring and legal escalation.
Read article →What is Private AI and why does it matter?
Private AI explained for enterprise use: customer-controlled environment, shared AI services, private model runtime, governance and operations.
Read article →Where should AI governance start for Private AI?
A progressive governance approach starting with use case ownership, risk, data boundary, identity, registry, evaluation, approval and audit.
Read article →What is an AI Fintech Factory?
A delivery model for turning financial-services problems into AI use cases from discovery and prototype to evaluation, integration and production.
Read article →How should Document AI go beyond OCR in financial services?
Document AI should go beyond text recognition to classification, extraction, cross-document checks, confidence handling and human review.
Read article →What is payment allocation in lending?
Payment allocation defines how an incoming payment is applied to fees, interest, principal or other components. The order must reflect product rules, institutional policy and accounting treatment.
Read article →How should an interest engine be designed?
An interest engine should separate formula, day-count, rate source, rounding, calendars and calculation-triggering events from workflow so calculations remain auditable and reusable across products.
Read article →How should a lending platform integrate with core banking?
Lending-to-core integration should begin by defining system-of-record and ownership for customer, account, transaction, balance and accounting events before choosing APIs, events, batch or files.
Read article →What is the difference between a ledger and a General Ledger?
In lending, an operational ledger records account-level events and balances, while the General Ledger is the enterprise accounting book receiving postings under the chart of accounts and accounting rules.
Read article →How should financial institutions approach RAG?
RAG should start with governed source content, access rights, metadata and target questions before choosing a vector database or embedding model. Citation, access filtering and evaluation are essential.
Read article →What is an AI Gateway in enterprise AI?
An AI Gateway sits between applications and model services to manage authentication, policy, routing, logging, quotas and model changes without binding applications to a single endpoint.
Read article →What should AI evaluation measure before production?
AI evaluation should reflect the real task and risk, measuring answer quality, coverage, error types, latency, review effort and failure scenarios rather than relying on one benchmark for every use case.
Read article →How is Private AI different from Public AI?
The key difference is not only where the model runs, but also data boundaries, identity and policy controls, model approval, audit, operating ownership and integration with enterprise systems.
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