LendFast

AI guidance and routing for faster loan journeys.

LendFast is an AI-native lending platform for mortgage, personal loan, and SME customers, with separate agents for guidance, product recommendation, and lead allocation. It helps borrowers complete applications faster, helps internal teams route and process qualified leads accurately, and gives banks a controlled, auditable way to use AI without fabricating outcomes.

Business Goals

  • Increase completed digital loan applications by 20 percent within 6 months of launch.
  • Increase qualified lead-to-submission conversion by 15 percent within 2 quarters.
  • Reduce manual operations effort in application support and routing by 35 percent within 9 months.
  • Improve product recommendation acceptance rate to 60 percent or higher within 3 months of Advisor launch.
  • Reduce lead assignment SLA breaches by 40 percent within 6 months.

User Goals

  • Help customers understand every field and required document in plain language.
  • Recommend only eligible, approved loan products based on real data.
  • Guide users to the next best action without forcing them to call support.
  • Route qualified leads to the correct banker, broker, or relationship manager quickly.
  • Provide customers and staff with clear status, errors, and next steps in English and Vietnamese.

Non-Goals

  • Not a loan decisioning engine that approves or declines credit applications.
  • Not a system for inventing products, rates, or policy exceptions.
  • Not a full CRM replacement for bank sales teams.
  • Not a customer-facing wealth management or deposit account platform.

Mortgage Borrower Linh, 34 - Linh is buying her first apartment and wants to understand whether she qualifies, what documents are needed, and how long the process will take. She prefers Vietnamese but can read English when needed.

Mortgage Borrower Linh, 34

  • As a mortgage borrower, I want field-by-field explanations in Vietnamese, so that I can complete the application without asking a bank branch.
  • As a borrower, I want the system to detect missing income or property documents, so that I can fix issues before submission.
  • As a borrower, I want product recommendations that only show products I can actually apply for, so that I do not waste time on ineligible options.

SME Owner David, 41 - David runs a small manufacturing business and needs a working capital loan quickly. He has limited time and wants a short, guided journey that helps him qualify and get routed to the right team.

SME Owner David, 41

  • As an SME borrower, I want the assistant to explain financial terminology in plain language, so that I can provide accurate business information.
  • As an SME borrower, I want to compare eligible products by installment, tenor, and capacity, so that I can choose the best option for my cash flow.
  • As an SME borrower, I want fast routing to the right banker or partner, so that my request is handled without delays.

Bank Sales Advisor Mei, 29 - Mei handles incoming leads across mortgage and personal loans and needs a reliable workflow that respects bank rules, SLA priorities, and relationship ownership. She needs visibility into why a lead was assigned to her.

Bank Sales Advisor Mei, 29

  • As a sales advisor, I want allocation decisions to include the rule outcome and timestamps, so that I can understand and trust the routing.
  • As a sales advisor, I want only qualified and complete leads assigned to me, so that I spend time closing rather than chasing missing data.
  • As a sales advisor, I want to reassign or escalate leads through approved workflows, so that exceptions do not get stuck.

Agent Assistance and Guided Application · High priority

  • Provide a bilingual conversational assistant that guides applicants through the lending journey, explains each step, validates inputs, and recommends the next action.
  • Support English and Vietnamese with language auto-detection and manual switching.
  • Explain every form field, required document, and business term in simple language with examples.
  • Validate format and completeness in real time for names, income, address, employment, and document uploads.
  • Detect contradictions such as income mismatches or missing co-borrower details and prompt the user to correct them.
  • Offer next-step recommendations such as upload document, review, save draft, or contact support.

Agent Advisor and Product Recommendation · High priority

  • Use internal product catalog, eligibility rules, pricing engine, and loan capacity calculator to recommend only approved products that fit the customer profile and intent.
  • Read only from approved product catalog and pricing/rate sources stored in internal systems.
  • Calculate eligibility using internal rules for product type, geography, income, debt, collateral, and policy constraints.
  • Rank eligible products by fit score, affordability, estimated monthly payment, and time to decision.
  • Continue refining recommendations based on customer preferences such as term, payment, purpose, and speed.
  • Never fabricate approval, rate, fee, eligibility, or capacity results; when unavailable, state that the data is unavailable and ask for the next permitted step.

Agent Allocator and Lead Routing · High priority

  • Route qualified leads to the correct receiver based on bank, product, geography, workload, SLA, partner rules, relationship manager ownership, and broker assignment.
  • Apply deterministic routing rules before any AI suggestion is shown to users or staff.
  • Record every routing decision with input factors, rule version, and final assignee.
  • Support assignment to internal bankers, relationship managers, branch teams, brokers, and partner queues.
  • Re-route only through approved escalation or reassignment logic with full audit trail.
  • Allow operations users to simulate routing outcomes before publishing rule changes.

Case Management and Human Handoff · Medium priority

  • Provide controlled escalation from AI to human staff when confidence is low, rules conflict, or customers request help from a person.
  • Escalate when document quality, identity, or eligibility confidence falls below configured thresholds.
  • Preserve conversation context, extracted data, and system explanations for the human agent.
  • Show a clear reason for handoff such as policy uncertainty, missing data, or customer request.
  • Allow staff to continue the case without forcing the customer to repeat information.
  • Track handoff completion and resolution time as operational metrics.

Admin, Policy, and Audit Controls · Medium priority

  • Give bank administrators tools to manage product content, routing rules, guardrails, and traceability without code changes for every policy update.
  • Version product catalog entries, eligibility rules, prompt templates, and routing rules.
  • Restrict publishing to authorized admins with approval workflow for sensitive changes.
  • Expose searchable audit logs for recommendations, routing decisions, and manual overrides.
  • Support configuration by market, bank, partner, and product line.
  • Provide rollback for policy or prompt updates that introduce errors.

Guided Entry and Qualification

  • Customer lands on LendFast from bank website, partner portal, or advisor link.
  • System detects language preference and shows a concise welcome with loan purpose options.
  • Customer selects mortgage, personal loan, or SME loan and enters basic profile details.
  • Agent Assistance explains required fields inline and confirms document checklist.
  • Within 2 to 4 minutes, the customer receives a preliminary eligible-product shortlist or a clear request for missing items.
  • If qualified, the lead is prepared for routing or advisor review without re-entering data.

1. Capture Intent and Context

  • The customer states what they need and why, then selects a loan type and country or bank context.
  • Support free-text intent plus structured selection to reduce friction.
  • If intent is unclear, ask one clarifying question at a time.
  • Persist draft state so the user can resume later without losing progress.

2. Guide and Validate Input

  • Agent Assistance walks the user through the required fields, explaining each item and validating entries in real time.
  • Show contextual help for every field and document upload.
  • Reject invalid formats with a specific fix, not a generic error.
  • Support bilingual prompts and responses during the same session.

3. Evaluate Eligibility and Recommend

  • Agent Advisor evaluates the profile against approved products and generates a ranked list of eligible options.
  • Use internal catalog, pricing, capacity calculator, and policy rules only.
  • If data is incomplete, show what is needed to continue and avoid speculative results.
  • Display why a product is recommended, including key fit factors and tradeoffs.

4. Confirm Choice and Prepare Handoff

  • The customer selects a product or requests more refinement, and the system prepares the qualified lead for routing.
  • Capture selection, consent, and final submission state.
  • If the customer changes requirements, rerun recommendation using updated preferences.
  • If no product is suitable, explain why and present permitted next steps.

5. Route and Track

  • Agent Allocator sends the lead to the correct recipient and provides status visibility to the customer and staff.
  • Apply routing rules based on geography, workload, SLA, partner, and ownership.
  • Show assignment status and expected follow-up timing.
  • Retain a full audit trail of every routing action and exception.

Advanced Capabilities

  • Scenario comparison across multiple eligible products with payment and term side-by-side.
  • Supervisor override for edge-case routing with reason capture and approval.
  • Conversation resume across web, mobile, and advisor-assisted sessions.
  • Document quality checks for blur, missing pages, mismatch detection, and expired statements.
  • Simulation mode for operations teams to test routing rules before deployment.

Interface Principles

  • Bilingual conversation UI with clear language toggle and saved preference.
  • Progressive disclosure to show only the next required field or action.
  • Persistent eligibility and routing status panels so users know what the system is doing.
  • Accessible design with WCAG 2.2 AA contrast, keyboard support, and screen-reader labels.
  • Fast response experience with typing indicators, inline validation, and sub-2 second UI interactions for most actions.

Linh visits her bank’s loan page to apply for a mortgage but quickly gets stuck on document requirements and financial terminology. LendFast’s Agent Assistance switches to Vietnamese, explains each field in plain language, and flags a missing income statement before she submits incomplete information.

Once Linh finishes the basics, Agent Advisor checks only approved mortgage products from the bank’s internal catalog and shows her a short list of eligible options with estimated payments and reasons for fit. She chooses one, and Agent Allocator routes the qualified lead to the correct relationship manager based on branch ownership and SLA, with every decision logged.

Instead of abandoning the process or calling support, Linh completes the journey in one session. The bank gains a qualified, correctly routed lead, fewer manual follow-ups, and a transparent audit trail that supports both compliance and sales efficiency.

User-Centric Metrics

  • Application completion rate increases to 65 percent or higher for started journeys within 6 months.
  • Average time from start to qualified lead submission drops below 12 minutes for simple personal loans and 20 minutes for mortgage journeys.
  • First-pass data validity reaches 90 percent or higher for required fields and document checks.
  • Customer satisfaction score for guided lending reaches 4.5 out of 5 or higher.
  • Bilingual session completion rate for Vietnamese users is within 5 percent of English sessions.

Business Metrics

  • Lead conversion increases by 15 percent within 2 quarters.
  • Manual application support workload decreases by 35 percent within 9 months.
  • Routing SLA compliance improves to 95 percent or higher within 6 months.
  • Recommendation acceptance rate reaches 60 percent or higher for shown eligible products.
  • Abandoned-start recovery increases by 20 percent through draft resume and follow-up flows.

Technical Metrics

  • Platform uptime at 99.9 percent monthly.
  • Median recommendation response time under 2 seconds and p95 under 5 seconds.
  • Routing decision latency under 1 second for rule-based assignments.
  • Zero critical incidents involving fabricated product, rate, or approval output.

Tracking Plan

  • Track journey_started with loan type, language, and entry channel.
  • Track field_help_opened with field name, locale, and context.
  • Track validation_error_shown with error type, field, and recovery outcome.
  • Track eligibility_checked with ruleset version, products considered, and confidence.
  • Track recommendation_presented with product IDs, ranking order, and selected outcome.
  • Track lead_allocated with assignee type, routing rule version, SLA bucket, and override flag.
  • Track human_handoff_triggered with reason, confidence score, and resolution time.

Technical Needs

  • Frontend built with Next.js and TypeScript for web-based lending journeys.
  • Backend services in Node.js or Java with a rules engine for eligibility and routing.
  • LLM orchestration layer with tool calling, policy checks, and response filtering.
  • Event-driven architecture using Kafka or AWS SNS/SQS for audit, workflow, and handoff events.
  • Relational database such as PostgreSQL for applications, products, rules, and audit metadata.
  • Object storage such as Amazon S3 for documents with signed upload and retrieval links.
  • Centralized observability using OpenTelemetry, Datadog, or Grafana for traces, metrics, and logs.

Integration Points

  • Internal product catalog service.
  • Eligibility and pricing engine.
  • Loan capacity calculator.
  • CRM or sales platform such as Salesforce, Dynamics 365, or a bank internal CRM.
  • Identity verification and document services such as Onfido, Jumio, or equivalent bank-approved tools.

Data Storage & Privacy

  • Store sensitive personal and financial data encrypted at rest and in transit using managed KMS keys.
  • Separate customer PII from conversational logs, with tokenized or masked references in analytics.
  • Apply consent capture and data retention policies aligned to GDPR, CCPA, and local banking regulations.
  • Use role-based access control and least privilege for staff, operations, and support users.
  • Log only necessary data in audit trails and redact document contents where full fidelity is not required.

Scalability & Performance

  • Design recommendation and routing services to handle peak campaign bursts without degrading response time.
  • Cache approved catalog and policy snapshots with versioning to reduce repeated reads.
  • Use asynchronous processing for document extraction, lead handoff, and non-blocking background tasks.
  • Set SLO alerts for latency spikes, queue buildup, and tool failure rates.

Potential Challenges

  • Risk: hallucinated or outdated product information. Mitigation: force all product outputs to come from versioned internal data sources and block unsupported claims.
  • Risk: routing disputes caused by policy changes. Mitigation: store rule version, input snapshot, and decision explanation for every assignment.
  • Risk: poor Vietnamese-language quality. Mitigation: use bilingual test sets, human review, and locale-specific prompt templates.
  • Risk: sensitive data exposure in prompts or logs. Mitigation: redact PII before logging, use secure vaults, and enforce audit controls.
  • Risk: over-escalation to humans reduces automation value. Mitigation: tune confidence thresholds by journey type and monitor handoff reasons weekly.

Team & resourcing - Small cross-functional team: 3 backend engineers, 2 frontend engineers, 1 ML engineer, 1 product designer, part-time PM, part-time QA/compliance support.

Phase 1: MVP Guided Lending · Weeks 1-6

  • Bilingual Agent Assistance for a single loan journey.
  • Basic application capture, validation, draft save, and document checklist.
  • Initial audit logging and customer session tracking.
  • Manual handoff to human advisor through CRM link.

Phase 2: Advisor Recommendations · Weeks 7-12

  • Agent Advisor connected to approved product catalog, pricing engine, and eligibility rules.
  • Ranked eligible-product shortlist with explanation and refusal handling.
  • Recommendation analytics, feedback capture, and confidence thresholds.
  • Admin tools for catalog and rules versioning.

Phase 3: Automated Allocation · Weeks 13-16

  • Agent Allocator with deterministic routing rules and complete audit trail.
  • Workload, geography, SLA, partner, and ownership-based assignment.
  • Operations simulation mode and override workflow.
  • Queue integration with CRM and banker inbox notifications.

Phase 4: Hardening and Expansion · Weeks 17-24

  • Mortgage, personal loan, and SME journey variants.
  • Improved Vietnamese localization and document intelligence.
  • Compliance reporting, advanced observability, and rollback tooling.
  • Pilot rollout across one bank segment and one partner channel.

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Build an AI-native lending platform called LendFast using Next.js, TypeScript, PostgreSQL, and Node.js services.

Product summary:
LendFast helps mortgage, personal loan, and SME customers complete digital lending journeys with three AI agents: Agent Assistance for bilingual guidance and validation, Agent Advisor for approved product recommendations from internal bank systems only, and Agent Allocator for deterministic lead routing with full audit trail.

Core screens and flows:
1. Landing and loan purpose selection with language toggle for English and Vietnamese
2. Guided application form with inline explanations, document checklist, and real-time validation
3. Eligibility and recommendation results screen with only approved products, fit reasons, and next-step actions
4. Lead confirmation and submission screen
5. Routing status and audit history screen for sales advisors and relationship managers
6. Admin console for product catalog, eligibility rules, routing rules, prompt templates, and audit logs
7. Human handoff screen showing extracted customer data, confidence, and reasons for escalation

Data model:
Users, customer_profiles, applications, documents, conversation_sessions, messages, product_catalog, product_versions, eligibility_rules, pricing_snapshots, capacity_calculations, recommendations, routing_rules, routing_decisions, assignments, handoffs, audit_events, admin_users, consent_records

Key behaviors:
Support bilingual conversation, inline field help, missing/invalid data detection, product recommendation only from approved internal data, no fabricated rates or approvals, deterministic allocation based on bank/product/geography/workload/SLA/partner/owner rules, and immutable audit logs for every decision.

Integrations:
Mock or stub connectors for CRM, product catalog, eligibility engine, pricing engine, loan capacity calculator, document upload storage, identity verification, and notification service.

Non-functional requirements:
Secure authentication, role-based access control, encrypted storage, audit logging, p95 recommendation latency under 5 seconds, routing latency under 1 second, WCAG 2.2 AA accessibility, and modular architecture for adding more loan products later.

Build the app with polished UI, seed data, API routes, reusable components, state management for application drafts, and a rules-based service layer for eligibility and routing. Include realistic sample content, error states, loading states, and empty states.

Business Idea

Build a comprehensive Product Requirements Document (PRD) for an AI-native lending platform called LendFast. The product consists of three collaborative AI Agents: 1. Agent Assistance Purpose: - Guide customers through the entire digital lending journey. - Explain every field, document requirement, and business terminology. - Detect missing or invalid information. - Recommend the next step. - Support Vietnamese and English. 2. Agent Advisor Purpose: - Understand customer intent and financial profile. - Use internal product catalog, eligibility rules, pricing engine, loan capacity calculator, and bank policies. - Recommend only approved products from the internal system. - Continue refining recommendations until the customer is satisfied. - Never fabricate products, interest rates, or approval decisions. 3. Agent Allocator Purpose: - Allocate qualified leads selected by customers to the correct receiver. - Support allocation based on bank, product, geography, workload, SLA, partner rules, relationship manager, and broker assignment. - Record a complete audit trail for every routing decision. Target users: - Mortgage borrowers - Personal loan customers - SME borrowers - Sales advisors - Bank relationship managers Business objectives: - Increase journey completion - Increase lead conversion - Improve recommendation accuracy - Reduce manual operations - Improve lead routing efficiency The PRD must include: - Executive Summary - Business Problem - Product Vision - Personas - User Journeys - Functional Requirements - Non-functional Requirements - AI Agent Responsibilities - AI Workflow - Tool Integrations - API Requirements - Data Requirements - Prompt & Knowledge Requirements - Memory Requirements - Guardrails - Human-in-the-loop - Error Handling - Edge Cases - Security & Compliance - Logging & Audit - Acceptance Criteria - KPIs - Rollout Plan - Future Roadmap The document should be detailed enough that engineering teams can implement the solution without ambiguity.

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    PRD: Build a comprehensive Product Requirements Document (PRD)