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Lending Journey
- Anand Nerurkar
- Sep 13
- 17 min read
A digital lending platform can support multiple types of loans depending on the target customer segments (Retail, SME, Corporate) and business strategy. Typically, such platforms are designed to be modular and configurable to cater to secured, unsecured, short-term, and long-term loans. Here’s a breakdown:
1. Retail / Consumer Loans
Personal Loan (Unsecured)
Salary-based, self-employed, pre-approved offers
Instant disbursement using e-KYC and alternate credit scoring
Auto Loan / Two-Wheeler Loan
Secured against vehicle
Integration with RTO, dealer systems, and insurance APIs
Home Loan
Secured, long-tenure (10–30 years)
Requires property verification, legal opinion, and valuation integration
Consumer Durable Loan / BNPL (Buy Now Pay Later)
Instant credit for electronics, appliances, e-commerce transactions
Often zero-cost EMI
2. SME / MSME Loans
Working Capital Loan / Cash Credit
Collateral or unsecured
Based on GST filings, bank statements, cash flow analytics
Term Loan
Fixed tenure, secured against business assets
Invoice Discounting / Bill Discounting
Advance against unpaid invoices
Merchant Cash Advance
Linked to POS transactions or UPI inflows
3. Agri and Rural Loans
Crop Loan / Kisan Credit Card (KCC)
Seasonal repayment linked to harvest cycle
Equipment Financing
Tractors, irrigation pumps, solar solutions
4. Corporate / Institutional Loans
Project Finance
Large-scale infrastructure or manufacturing projects
Syndicated Loans
Multiple lenders participate
Trade Finance / Letter of Credit
Cross-border trade facilitation
5. Specialized / Emerging Loan Products
Education Loans
For higher studies in India or abroad
Green Loans
For renewable energy projects (solar rooftop, EV financing)
Microfinance / Nano Loans
Small ticket loans via mobile apps or UPI
P2P Lending
Platform enables matching borrowers with individual lenders
Architecture Implications
Configurable Product EngineSupports defining loan type, tenure, interest rate, collateral requirement.
Eligibility & Scoring ModuleUses alternate data (Aadhaar, PAN, GST, CIBIL, bank statements, social scoring).
Integration LayerAPIs with credit bureaus, eKYC, UPI, RTO, legal property databases, GSTN.
Regulatory ComplianceRBI/SEBI guidelines, AML/KYC, fair lending practices, audit trails.
Multi-channelMobile app, web, branch, partner (dealer, merchant) onboarding.
Here’s a detailed mapping of loan types → microservices → Azure architecture components for your Digital Lending Platform (Spring Boot microservices + Azure Cloud):
1. Loan Types Supported (MVP vs. Future Roadmap)
MVP (Launch Phase – 3 to 6 months)
Focus on high-demand, fast-turnaround loans:
Personal Loan (Unsecured)
Consumer Durable Loan / BNPL
Auto Loan / Two-Wheeler Loan
SME Working Capital Loan (Unsecured)
Invoice Discounting
Future Roadmap (Post-MVP – 6 to 18 months)
Expand into higher complexity products:
Home Loan / Mortgage
Education Loan
Green Loans / EV Financing
Corporate Term Loans / Project Finance
Microfinance / Nano Loans (Rural outreach)
2. Microservices Breakdown (Loan Type Coverage)
Microservice | Loan Types Supported | Key Functions |
Customer Onboarding Service | All | eKYC, Aadhaar, PAN, GST validation, CKYC |
Loan Application Service | All | Application intake, workflow orchestration |
KYC & Compliance Service | All | AML checks, PEP screening, regulatory reporting |
Credit Score Service | Personal, Auto, SME | CIBIL, Experian, internal credit scoring |
Loan Eligibility Service | Personal, Auto, SME | DTI ratio, alternate data scoring (bank/GST) |
Collateral Management Service | Auto, Home, Corporate | Asset valuation, lien marking, RTO/property APIs |
Loan Agreement Service | All | E-signature, agreement generation, e-stamping |
Loan Evaluation & Approval Service | All | Risk engine, rules-based + ML-based decisions |
Disbursement Service | All | UPI/NEFT/RTGS payouts, integration with CBS |
Repayment & Collection Service | All | EMI schedules, auto-debit, UPI mandates |
Fraud Detection Service (AI/ML) | All | Device fingerprinting, behavior analytics |
Notification Service | All | SMS, Email, WhatsApp updates |
Reporting & Analytics Service | All | MIS, regulatory, portfolio insights |
3. Azure Cloud Integration (Per Loan Type)
Core Azure Components
Azure AKS: Host all microservices (scalable containers)
Azure API Management (APIM): API gateway for internal/external partners
Azure Service Bus / Kafka (Event Hub): Event-driven orchestration (loan status updates, fraud triggers)
Azure SQL + Cosmos DB:
SQL for transactional data (loan contracts, repayments)
Cosmos DB for high-speed customer profiling, alternate credit scoring
Azure Cognitive Services: OCR for document extraction (PAN, Aadhaar, bank statements)
Azure AD B2C: Customer identity and access management
Azure Key Vault: Secure storage of credentials, keys, secrets
Azure Logic Apps / Durable Functions: Orchestration of workflows (KYC → Score → Approval → Disbursement)
Azure Monitor + Application Insights + Log Analytics: Observability, SLA monitoring
Azure DevOps: CI/CD for microservices deployment
Loan Type Specific Integrations
Personal Loan / Consumer Durable Loan
Instant approval → integrate CIBIL API, eKYC APIs, UPI disbursement
Store application in Azure SQL, cache customer profile in Redis
Auto Loan / Two-Wheeler Loan
Collateral → integrate RTO API, Insurance API
Use Cosmos DB for fast asset data retrieval
SME Working Capital / Invoice Discounting
Integrate GSTN APIs, Bank Statement Analyzers
Event-driven scoring with Kafka → ML Fraud Service
Home Loan / Corporate Loan
Property valuation → integrate Legal, Property APIs
Longer workflow → orchestrated via Logic Apps/Durable Functions
4. Mapping: Loan Types → Microservices → Azure Services
Loan Type | Key Microservices | Azure Services |
Personal Loan | Customer Onboarding, Loan Application, Credit Score, Loan Eligibility, Disbursement, Repayment | AKS, APIM, Service Bus, Azure SQL, Cosmos DB, Cognitive Services |
Auto Loan | Collateral Mgmt, KYC, Loan Evaluation, Agreement, Disbursement | AKS, APIM, Service Bus, Cosmos DB, RTO API via Logic Apps |
SME Loan | Loan Application, Credit Score, Eligibility, Invoice Discounting, Fraud Detection | AKS, Event Hub, Cosmos DB, Cognitive Services, Azure SQL |
Home Loan | Collateral Mgmt, Agreement, Evaluation, Disbursement, Repayment | AKS, Logic Apps, APIM, Azure SQL, Key Vault |
BNPL | Onboarding, Instant Approval, Disbursement, Collections | AKS, Redis, Cosmos DB, Service Bus |
5. Architecture Flow (Loan Lifecycle)
Step 1: Customer Onboarding
eKYC via Aadhaar/PAN → API call to KYC Service → Cosmos DB store → Azure Key Vault for sensitive data
Step 2: Loan Application
Loan Application Service receives request → Event pushed to Service Bus → triggers Credit Score + Eligibility services
Step 3: Credit Evaluation
Credit Score Service fetches from CIBIL → ML scoring (Fraud Detection Service) → results stored in Azure SQL
Step 4: Approval & Agreement
Loan Evaluation Service calculates risk score → Loan Agreement generated (e-sign via Cognitive Services)
Step 5: Disbursement
Disbursement Service triggers payment via UPI/RTGS → updates CBS → event logged in Service Bus
Step 6: Repayment & Monitoring
Repayment Service schedules EMIs → integrates with auto-debit mandates (UPI, NACH) → sends notifications
Step 7: Reporting & Compliance
Reporting Service aggregates data → Azure Synapse/Power BI for dashboards → regulatory reporting
Overview (one-line)
Modular Spring Boot microservices on AKS expose APIs to an Angular SPA via API Management; services communicate via Kafka (event-driven choreography + Sagas), persist transactional state in Azure SQL and fast lookups in Cosmos/Redis, and integrate with external systems (eKYC, bureaus, RTO, payment rails) via dedicated integration adapters.
1 — Retail Loan types covered
Personal Loan (unsecured)
Consumer Durable / BNPL (short-term, merchant-linked)
Auto / Two-wheeler Loan (secured — vehicle collateral)
Home Loan / Mortgage (secured — property; long-running)
Small-ticket micro-loans / EMI financing
2 — High-level loan lifecycle (applies to all retail loans)
Customer onboarding & authentication (Angular SPA)
Application submission (form + docs)
Document ingestion & OCR (ID, income docs)
KYC & AML checks (eKYC, PEP, sanctions)
Credit scoring & alternative scoring (bureau + transaction/GST/bank-parse)
Eligibility & pricing (interest, tenor, fees)
Underwriting (rules engine + ML + human/manual review)
Agreement generation & e-sign (digital signature)
Disbursement (UPI/NEFT/CBS integration)
Repayment scheduling & collections (auto-debit/UPI/NACH)
Servicing (top-ups, prepayment, closure)
Collections & recovery (delinquency workflows)
3 — Microservice decomposition (core services)
Each service is a Spring Boot app, containerized, 12-factor, deployed to AKS.
API Gateway / APIM (not a microservice): external entry point, auth, rate limiting JWT verification.
Frontend App: Angular SPA (customer + agent portals) served via CDN/Front Door.
Customer Service: profile, KYC status, consents.
Auth Service: Azure AD B2C integration, JWT token issuance, session mgmt.
Loan Application Service: receives applications, validates payload, persists application record.
Document Service: upload, virus-scan, store in Blob Storage, call OCR.
KYC & Compliance Service: eKYC, AML/PEP check, CKYC, regulatory reporting events.
Credit Score Service: fetch bureau scores, run internal models, alternative data aggregator.
Eligibility & Pricing Service: product engine, rule engine for rates & tenors.
Underwriting Service: ML model scoring + rules; issues ACCEPT/REFER/REJECT; sends events.
Collateral Service: asset valuation, register liens (auto/home).
Agreement Service: templating, e-sign integration, e-stamping hooks.
Disbursement Service: payment orchestration, CBS reconciliation.
Repayment & Collections Service: schedule EMIs, process receipts, late fee calc.
Fraud Detection Service: real-time scoring, device fingerprinting, velocity rules.
Notification Service: SMS/Email/WhatsApp via providers (SendGrid/Twilio/WhatsApp API).
Reporting & Analytics: event stream into Data Lake/Synapse, dashboards (Power BI).
Integration/Connector Service: adapters for external APIs (CIBIL, Aadhaar, RTO, Payment Gateways).
Audit & Audit Log Service (or centralized DB): immutable event audit.
Orchestration/Workflow: optional (we recommend Saga via Kafka choreography — see Saga section).
4 — Event topics & example events (Kafka)
Use semantic topic naming, partition by tenant/customer/region where needed.
loan.application.created
loan.application.submitted
document.uploaded
kyc.completed
credit.score.available
eligibility.decided
underwriting.decision
agreement.signed
disbursement.requested
disbursement.completed
repayment.scheduled
repayment.received
loan.status.updated
fraud.alert
Use Cloud-native Kafka (self-managed on AKS, Confluent Cloud, or Azure Event Hubs with Kafka protocol).
5 — Saga pattern & choreography (how transactions span services)
Use choreography: services react to events and publish new events. Example flow:
loan.application.created → Credit Score Service consumes → publishes credit.score.available.
Eligibility Service consumes credit.score.available → publishes eligibility.decided.
Underwriting consumes eligibility.decided → publishes underwriting.decision.
Agreement Service consumes decision → generates agreement → publishes agreement.signed.
Disbursement Service consumes agreement.signed → processes disbursement → publishes disbursement.completed.
Compensations: each service must implement a compensating action event (e.g., disbursement.rollback.requested) for failure cases.
Use outbox pattern for reliable event publishing (transactional DB write + event write).
6 — Sequence example (Personal Loan — simplified)
Angular -> POST /api/loan-applications (Loan Application Service)
Loan Application Service persists application; writes outbox; publishes loan.application.created.
Document Service is triggered for uploads → OCR → document.uploaded.
KYC Service picks up document.uploaded → verifies eKYC → publishes kyc.completed.
Credit Score Service consumes loan.application.created → calls bureau → publishes credit.score.available.
Eligibility Service consumes kyc.completed + credit.score.available → publishes eligibility.decided.
Underwriting consumes eligibility.decided → ML + rules => underwriting.decision. If REFER -> create manual review task in Workbench UI.
Agreement Service issues doc + eSign -> agreement.signed.
Disbursement Service processes -> disbursement.completed.
Repayment Service creates schedule and integrates with auto-debit; notifications sent.
7 — Data model (core tables) — simplified SQL schema
customer (customer_id PK, name, dob, pan, mobile, email, primary_address_id, created_at)loan_application (app_id PK, customer_id FK, product_code, amount_requested, tenure_months, status, created_at, updated_at, correlation_id, idempotency_key)loan_account (loan_id PK, app_id FK, principal, outstanding_amount, interest_rate, start_date, maturity_date, status)collateral (collateral_id, loan_id FK, type, value, registration_details)repayment_schedule (schedule_id, loan_id, due_date, principal_due, interest_due, status)transaction (txn_id, loan_id, amount, txn_type, posted_at, external_ref)audit_log (log_id, entity, entity_id, operation, payload, actor, timestamp)consent (consent_id, customer_id, scope, granted_at, expires_at)outbox_event (event_id, aggregate_id, event_type, payload, published_flag, created_at)
Include correlation_id in all messages and DB records; include idempotency_key for endpoints that might retry.
8 — Azure Infrastructure mapping
AKS — host all Spring Boot microservices (use node pools, spot & standard).
Azure API Management (APIM) — public API gateway, rate-limiting, policy enforcement.
Azure Front Door / CDN — serve Angular SPA (global edge).
Azure Blob Storage — document store (encrypted).
Azure SQL — primary transactional DB (loan_account, repayment_schedule). Use Hyperscale if needed.
Cosmos DB — fast lookup & customer profile caching (optional).
Redis Cache (Azure Cache for Redis) — short-lived session/cache.
Kafka — either Confluent Cloud or self-managed Kafka on AKS (statefulset) or use Azure Event Hubs with Kafka compatibility.
Azure Key Vault — secrets/certs/keys.
Application Insights + Log Analytics — tracing, metrics, logs.
Prometheus + Grafana — cluster and service metrics (if preferred).
Azure Container Registry (ACR) — store Docker images.
Azure DevOps / GitHub Actions — CI/CD pipelines building, scanning, deploying images to AKS.
Azure AD B2C — customer identity; Azure AD for staff/admin logins.
Azure Functions (only for small connectors if needed) — but not used for core orchestration.
Azure Policy / RBAC / Azure Security Center — security posture.
Power BI / Synapse — analytics, ETL from event stream to data warehouse.
9 — Security & Compliance
Auth: OAuth2/OIDC via Azure AD B2C for customers; Azure AD for internal users. JWT tokens issued by Auth Service.
Encryption: TLS everywhere, at-rest encryption for Blob/SQL/Cosmos; keys in Key Vault.
Network: AKS in private subnets; restrict egress; use Private Link for Azure SQL, Storage. WAF on Front Door.
Secrets: No secrets in code; injected from Key Vault via managed identity.
Data minimization & consent: Consent service logs customer consents; store minimal PII; retention policies.
Audit trail: immutable audit logs (append-only).
Compliance: Logging for regulatory audits (RBI guidelines in India), AML reporting hooks.
Pen test & SCA: include SAST/DAST + SCA in pipeline.
10 — Observability & Ops
Distributed Tracing: W3C traceparent; use OpenTelemetry; collect traces into Application Insights.
Logs: structured logs -> Log Analytics / ELK.
Metrics: Prometheus metrics exported by services; Grafana dashboards.
Alerts: SLA breaches, error rates, consumer lag on Kafka, infra resource exhaustion.
Chaos & load testing: run chaos experiments and performance tests (k6, Gatling).
11 — CI/CD & Dev Practices
Mono-repo or multi-repo pattern; each microservice has pipeline:
Build, unit tests, SCA, SAST
Build image -> push to ACR
Canary/Blue-Green deploy to AKS using Helm + ArgoCD or Azure DevOps Releases
DB migrations via Flyway or Liquibase.
Feature flags for gradual rollout (LaunchDarkly or homegrown).
Automated E2E tests for critical flows.
12 — Non-functional & capacity planning
Design for horizontal scaling: stateless services; scale consumers by consumer group.
Kafka partitions sized by throughput; retention for audit/analytics.
Use Redis/Cosmos for read-heavy endpoints.
SLA targets: e.g., personal loan pre-approved journey < 5s (excluding external API waits), full loan approval end-to-end depends on manual steps.
13 — Risk & mitigations (top 8)
External API latency/failures — Circuit breakers, retries + fallback rules, async compensation.
Data inconsistency across services — Outbox pattern + idempotent consumers + sagas.
Security breach of PII — Key Vault, encryption, least privilege, regular audits.
Kafka consumer lag — autoscale consumers; monitoring and alerting.
Manual-review bottleneck — workbench with SLAs, auto-escalation, throttling.
Fraud attacks — multi-layer fraud scoring, behavioral ML, device fingerprinting.
Regulatory non-compliance — consent capture, configurable retention, audit logs.
Deployment failures — Canary deploys, rollbacks, automated tests.
14 — Sample API endpoints (customer-facing)
POST /api/v1/loan-applications — submit application (idempotency-key header)
GET /api/v1/loan-applications/{id} — status & events
POST /api/v1/documents — upload doc (returns docId)
POST /api/v1/customers — create profile (OAuth-protected)
POST /api/v1/payments/disburse — request disbursement (internal)
Include OpenAPI/Swagger for each microservice and publish aggregated API docs in APIM.
15 — Implementation suggestions & tech stack
Java 17+, Spring Boot 3.x (WebFlux for high concurrency optional)
Spring Cloud (Kafka), Spring Data JPA, Flyway
Angular 15+ for SPA
Kafka (Confluent / Event Hubs Kafka compatibility)
PostgreSQL/Azure SQL, Cosmos DB (if needed)
Docker, Helm charts, ArgoCD/Flux (GitOps) or Azure DevOps pipelines
OpenTelemetry for tracing
16 — MVP scope (3–6 months) — suggested priority
Supports: Personal Loan, BNPL, Small Auto Loan (basic)
Microservices: Customer, Loan Application, Credit Score (bureau aggregator), Eligibility, Underwriting (rules only), Disbursement, Repayment, Notification, Document (OCR), Integration connectors for eKYC & payment.
Event infra + outbox + basic dashboards.
17 — What I can deliver next (quick options)
Architecture diagram + sequence diagram + workflow diagram (PNG/SVG) for your deck.
Detailed DB schema with fields for each table (DDL).
Sample Spring Boot microservice template with outbox pattern, Kafka consumer/producer, tracing and CI pipeline.
Here’s how loan type → journey differences typically work:
1. Personal Loan (Unsecured)
Journey: Fastest & simplest
Steps:
Onboarding → eKYC → Bureau Score
Instant decision (pre-approved offers possible)
Agreement → e-sign → Instant disbursement
Key Characteristics:
No collateral validation
Risk model heavily credit-score-driven
End-to-end TAT: seconds to minutes
Often fully automated (no manual underwriting)
2. Consumer Durable / BNPL Loan
Journey: Embedded financing at point of sale
Steps:
Merchant integration triggers loan flow
Minimal KYC (Aadhaar OTP, PAN check)
Lightweight risk scoring (not full bureau pull sometimes)
Instant approval → generate EMI plan → disburse to merchant
Key Characteristics:
Low ticket, low risk, short tenor
UX must be frictionless
Strong integration with merchant/partner systems
High volume, low latency focus
3. Auto / Two-Wheeler Loan
Journey: Collateral-based, dealer-assisted
Steps:
KYC + Bureau Score
Vehicle details capture (chassis/engine no.)
Collateral valuation (price from OEM/RTO)
Agreement → Hypothecation filing → Disbursement to dealer
Key Characteristics:
Asset verification mandatory
Dealer/DMS integration
RTO lien marking (hypothecation) step required before disbursement
Moderate automation, but manual checks for certain regions
4. Home Loan / Mortgage
Journey: Longest, most complex
Steps:
KYC, income documents (bank statements, salary slips)
Detailed bureau & affordability check
Property documents upload → legal & technical verification
Collateral valuation & title search
Sanction letter → agreement → registration/stamping
Tranche disbursements (not always lump sum)
Key Characteristics:
Multiple manual touchpoints
Third-party verification (legal, technical)
Multiple approval layers (risk, compliance)
TAT: days to weeks
Often integrated with manual workflow systems
5. Micro Loans / Small Ticket Lending
Journey: Ultra-fast, mobile-first
Steps:
Mobile onboarding → OTP-based KYC
Alternative credit scoring (UPI, SMS data, wallet usage)
Instant decision → Instant disbursal
Key Characteristics:
Uses alternate data instead of full bureau pulls
Designed for underbanked customers
Must support very high volumes, low cost per acquisition
How It Differs in Architecture & Microservices
Component | Personal / BNPL | Auto Loan | Home Loan |
KYC Service | Basic eKYC, OTP flow | Full eKYC + additional address proof validation | Full eKYC + manual doc review |
Credit Score Service | Instant bureau + internal score | Bureau + LTV (Loan-to-Value) check | Bureau + DTI + complex affordability models |
Collateral Service | Not used | Vehicle valuation + RTO lien marking | Property valuation + legal title check |
Underwriting | Fully automated | Semi-automated (manual override possible) | Multi-level approval, manual review required |
Disbursement | Instant | Dealer disbursement (post lien) | Tranche-wise disbursement |
Agreement Service | Simple digital e-sign | e-sign + lien registration docs | Sanction letter + registered mortgage |
How You Should Design for It
Instead of creating completely separate journeys per loan type, design configurable workflows:
Workflow Engine / Rules Service (Camunda, Temporal, Zeebe or custom)
Define loan journey as steps (KYC → Score → Valuation → Approval → Disbursement)
Enable/disable steps based on product config
Product Configuration Table
Loan Type
Required steps (boolean flags: KYC, Collateral, Legal, Multi-Level Approval)
SLA per step
Auto/manual decision threshold
This way:
Personal Loan skips collateral/valuation
Auto Loan includes collateral validation
Home Loan includes property verification + manual approval steps
BNPL uses short KYC + instant disbursement
Key Design Principle
🔑 Build Once, Configure ManyRather than separate code paths, create configurable microservice orchestration so new loan products can be onboarded by changing configuration and business rules — not redeploying code.
Digital Lending Architecture & Journey — Retail Loans
Scope: Personal, Consumer Durable / BNPL, Auto / Two-wheeler, Home / Mortgage, Micro-loans (small-ticket). Spring Boot microservices (Java), Angular frontend, Kafka event-driven choreography, Saga pattern, deployed on Azure Cloud.
Executive summary
A single, configurable digital lending platform that supports multiple retail loan products by using a common microservice backbone and a workflow-driven product configuration. The platform uses event-driven choreography (Kafka) for internal orchestration and Saga/compensation for distributed transactions. Azure provides the infrastructure (AKS, APIM, Blob, SQL, Cosmos, Key Vault, Event Hubs/Kafka, ACR, AD B2C). The architecture follows “build once, configure many” to spin different loan journeys through product configuration rather than separate code paths.
High-level architecture (conceptual)
Angular SPA (Customer portal + Dealer/Agent portal) served via Front Door / CDN.
API Gateway (APIM) exposes secure REST endpoints; forwards to microservices on AKS.
Microservices (Spring Boot) on AKS: Customer, Auth, Loan Application, Document, KYC, Credit Score, Eligibility, Underwriting, Collateral, Agreement, Disbursement, Repayment, Fraud, Notification, Integration/Connector, Reporting, Audit.
Event Bus (Kafka / Event Hubs) for internal events; Outbox pattern for reliable event emission.
Data stores: Azure SQL (transactional), Cosmos DB (profile & high-read cache), Blob Storage (documents), Redis (cache), Data Lake / Synapse (analytics).
CI/CD: Azure DevOps / GitHub Actions -> ACR -> AKS (Helm/ArgoCD).
The detailed diagram is represented as sections below (sequence+workflow). If you want a PNG/SVG, tell me and I’ll produce visual exports.
Key design principles
Product-configurable workflows — each loan product is defined by a set of ordered steps and policy thresholds stored in a Product Configuration service.
Event-driven choreography — services react to events and publish subsequent events; keep services loosely coupled.
Outbox + Idempotent Consumers — ensure eventual consistency & exactly-once semantics for critical flows.
Compensating Sagas — each long-running distributed transaction has compensating actions.
Separation of concerns — integrate external partners via dedicated Integration/Connector services.
Security by design — data encryption, Key Vault, private networking, Azure AD B2C.
Product configuration model (example)
A product_config entity controls the journey:
product_code (PERSONAL/BNPL/AUTO/HOME/MICRO)
steps (ordered list) e.g. [KYC, BUREAU, ELIGIBILITY, VALUATION, UNDERWRITING, AGREEMENT, HYPOTHECATION, DISBURSEMENT]
auto_approval_thresholds (score >= X, LTV <= Y)
requires_collateral (bool)
collateral_type (vehicle/property)
manual_review_rules (business rules pointing to Workbench)
sla_per_step (seconds/minutes/hours/days)
When a loan application is created, the Loan Orchestrator (lightweight service) resolves the product config and publishes events to start the corresponding steps.
Microservices (brief responsibilities)
API Gateway / APIM — authentication, rate-limiting, request validation, routing, aggregated docs.
Auth Service — integrates Azure AD B2C for customers; issues JWT to front-end.
Customer Service — master customer profile, KYC status, consent records, correlation IDs.
Loan Application Service — persistent application aggregate, handles idempotency, writes outbox events.
Document Service — handles uploads to Blob, triggers OCR (Cognitive Services) and stores metadata.
KYC & Compliance Service — eKYC (Aadhaar), AML/PEP checks, CKYC integration.
Credit Score Service — bureau integrations + internal models (cache results in Cosmos).
Eligibility & Pricing Service — product rules engine, pricing calculator.
Underwriting Service — ML-based risk scoring + business rule engine; creates manual review tasks.
Collateral Service — valuation, lien registration helpers (RTO, property, eRegistries).
Agreement Service — templating, e-sign integration, e-stamping hooks.
Disbursement Service — orchestrates UPI/NEFT/RTGS/CBS payouts; handles tranche logic.
Repayment Service — schedules EMIs, NACH/UPI mandates, reconciliation.
Fraud Service — real-time flagging, device fingerprinting, velocity checks.
Integration/Connector Service — adapter layer for bureaus, payment gateways, RTO, GSTN.
Reporting Service — stream ETL to Synapse and Power BI; regulatory exports.
Audit Service — append-only audit entries for regulatory compliance.
Event design (topics & example payloads)
Use domain-driven, versioned events. Examples:
loan.application.created { appId, customerId, productCode, amount, correlationId }
document.uploaded { docId, appId, docType, storageUri }
kyc.completed { customerId, kycStatus, evidence }
credit.score.available { customerId, score, bureau, modelVersion }
eligibility.decided { appId, eligible, recommendedAmount, rate }
underwriting.decision { appId, decision, reasons, manualTaskId? }
agreement.signed { appId, agreementId, signedAt }
disbursement.completed { appId, loanId, amount, txnRef }
Partition keys: tenantId or customerId depending on scale and privacy.
Saga choreography & compensations
Approach: Choreography for happy path; compensating events for failures.
Example: Disbursement Saga (high level)
agreement.signed → Disbursement Service attempts fund transfer.
On success -> disbursement.completed (update loan_account state).
On failure -> emit disbursement.failed -> trigger compensations: agreement.revoke (if needed), reserve_release for collateral hold, notify customer and operations.
Every service must implement idempotent handlers and compensating events where a state change affects external systems.
Loan-specific journeys (condensed)
Personal Loan (fast path)
Steps: KYC → Bureau Score → Eligibility → Auto Underwriting → Agreement eSign → Disbursement
Key differences: no collateral, decision thresholds tuned for automation, limited manual review.
BNPL / Consumer Durable (merchant-embedded)
Steps: Merchant trigger → Lightweight KYC → Lightweight score (internal) → Instant Approval → Agreement (simplified) → Pay merchant
Key differences: merchant integration adapters; lower friction; tokenized payment rails; settlement with merchant payout schedules.
Auto Loan
Steps: KYC → Bureau → Eligibility + LTV calc → Dealer inputs vehicle details → Collateral Valuation → Hypothecation/RTO filing → Underwriting → Agreement + Lien docs → Disbursement to Dealer/CBS
Key differences: Collateral service interacts with RTO & Dealer systems; pre-disbursement check for lien registration.
Home Loan
Steps: KYC → Detailed affordability & bureau → Property docs upload → Technical valuation & Legal title search → Manual underwrite & multi-level approval → Sanction letter → Agreement signing & registration → Tranche-based disbursement
Key differences: lengthy 3rd-party processes (legal/valuation); human-in-loop workflows; tranche payments; document-heavy.
Micro-loans
Steps: Mobile onboarding → OTP KYC → Alternate-data scoring (UPI/telemetry) → Instant approval & disbursal
Key differences: alternative data connectors, extremely lightweight UX, high throughput.
Configurable workflow engine (implementation options)
You have 3 choices:
Use Temporal / Camunda / Zeebe (recommended if you prefer explicit workflow modeling & visibility). It maps product-config steps into orchestrated stateful workflows with retries, timers, human tasks.
Pure event-driven choreography (Kafka) with a lightweight Orchestrator service that resolves product config and emits initial events (recommended for high scalability and low centralization).
Hybrid: choreography for internal microservice interactions + Temporal/Camunda for business-visible long-running human tasks (e.g., home loan manual review).
Data model (core aggregates)
Key aggregates/tables (with sample important fields):
customer(customer_id, name, dob, pan, mobile, email, primary_address_id)
loan_application(app_id, customer_id, product_code, requested_amount, tenure, status, correlation_id, idempotency_key, created_at)
loan_account(loan_id, app_id, principal, outstanding, interest_rate, start_date, status)
document(doc_id, app_id, type, storage_uri, ocr_text, verified)
collateral(collateral_id, loan_id, type, value, registration_status)
repayment_schedule(schedule_id, loan_id, due_date, principal, interest, status)
outbox_event(id, aggregate_id, event_type, payload, published_flag)
consent(consent_id, customer_id, scope, granted_at, expires_at)
Design notes: use transaction-per-aggregate and outbox for publishing events.
Azure services mapping (detailed)
AKS — host microservices; node pools split by workload type (system, burst, critical). Use pod-level identity.
APIM — public APIs, aggregation, developer portal.
Azure Front Door + CDN — host Angular SPA; WAF.
Azure Event Hubs (Kafka API) or Confluent Cloud — event backbone.
Azure SQL — primary transactional DB (use geo-replication for DR).
Cosmos DB — customer profile, session store, scoring cache.
Blob Storage — documents (tiering + immutable storage for audit).
Key Vault — secrets, certificates.
Azure AD B2C — customer auth & identity.
Cognitive Services / Form Recognizer — OCR for documents.
Power BI / Synapse — reporting & analytics.
Application Insights + Log Analytics — tracing & logs.
Azure Cache for Redis — caching.
Azure DevOps / GitHub Actions & ACR — CI/CD.
Security & privacy
TLS 1.2+, mTLS for service-to-service where required.
RBAC & least privilege via Azure AD & managed identities.
Encrypt at rest (SQL, Cosmos, Blob) with Customer-Managed Keys in Key Vault.
PII redaction on logs; store only necessary PII; consent capture & retention policy enforcement.
Network isolation: private AKS cluster, private endpoints for SQL & Storage.
Observability & SLOs
Tracing: OpenTelemetry across services, correlate via correlation_id.
Metrics: Prometheus + Grafana for infra; Application Insights for app metrics.
Logs: Structured logs → Log Analytics; high-volume events sent to ELK if needed.
SLO examples: 99.9% availability for APIs; consumer lag < 30s for critical topics.
CI/CD, testing & deployment
Multi-stage pipelines: build -> SCA/SAST -> unit tests -> containerize -> push to ACR -> helm chart -> deploy to staging -> integration tests -> canary -> production.
Use feature flags for gradual rollouts.
Automate DB migrations (Flyway). Run contract tests for each service's consumer-provider.
Scalability & capacity planning
Partition Kafka topics by tenant or customerId to parallelize.
Scale consumers by consumer groups; stateless microservices horizontally autoscale.
Cache hot lookups in Redis/Cosmos; use CQRS pattern for read-optimized endpoints.
Regulatory & operational governance
Compliance pipelines: scheduled exports for regulator formats; eKYC & AML audit trails.
Consent & data retention management service to comply with local laws.
Regular DR drills; backup policies for DB & Blob.
Example APIs (customer-facing)
POST /v1/loan-applications (idempotency-key required)
GET /v1/loan-applications/{appId}
POST /v1/documents (multipart upload)
GET /v1/loan-products (product config summary)
POST /v1/customers (customer onboarding)
Sample sequences (condensed)
Personal Loan (auto flow): Submit -> KYC -> Credit Score -> Eligibility -> Underwrite(auto) -> Agreement -> Disburse.
Home Loan (human-in-loop): Submit -> KYC -> Credit & Affordability -> Docs -> Valuation -> Legal -> Manual Underwrite -> Sanction -> Register -> Disburse (tranches).
Auto Loan (collateral): Submit -> KYC -> Credit -> Collateral Valuation -> Hypothecation -> Agreement -> Disburse to dealer.
Risks & mitigations (top items)
External API failures: design fallbacks, retries with exponential backoff, circuit breakers, async fallbacks.
Data inconsistency: outbox pattern + idempotency keys + strong audit trails.
Fraud: multi-layer checks, monitoring for anomalies, configurable rules.
Manual-review bottlenecks: SLA gates, auto-escalation, queue prioritization.
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