Design loan application system
Problem Statement
Design a scalable and compliant end-to-end loan origination platform for a small lending startup. The platform will facilitate unsecured term loans for both small businesses and consumers.
Context
The system must handle a peak traffic of 2,000 applications per day, with bursts up to 5 requests per second. Critical performance targets include decisioning within minutes and funding within hours. The architecture should prioritize horizontal scalability and allow for easy replacement of third-party vendors.
Core Requirements
1. User Experience and Product Selection
- Enable users to browse available loan products, displaying details such as amount, term, APR ranges, and eligibility hints.
- Support a pre-qualification process, involving a soft credit or cashflow pre-check, with explicit user consent.
- Provide a multi-device application experience, allowing users to save and resume their application at any point.
2. Application Intake
- Capture comprehensive applicant data, including identity, business information, income/cashflow details, loan purpose, and supporting documents.
- Implement Know Your Customer (KYC)/Customer Identification Program (CIP) and Anti-Money Laundering (AML)/Office of Foreign Assets Control (OFAC) screening.
- Manage user consents, including FCRA disclosures, credit pull authorizations, and bank data access permissions.
- Facilitate document uploads and bank account linking (e.g., via a financial data aggregator).
3. Underwriting Workflow (Internal)
- Orchestrate a series of automated and manual tasks, such as credit pulls, bank statement fetching, identity verification, and fraud screens.
- Integrate a rule engine and Machine Learning (ML) scoring models for automated decisioning.
- Provide a manual review queue and an analyst console for human intervention and oversight.
- Maintain a comprehensive audit trail and generate clear reason codes for all decisions.
4. External Integrations
- Connect with one or more credit bureaus for both soft and hard credit pulls.
- Integrate with bank statement and cashflow aggregation services for read-only access to financial data.
- Utilize payment rails (e.g., ACH/wire) for loan disbursements, incorporating webhook-based status updates.
5. Decisioning and Offer
- Apply risk scoring and credit policies to determine approval, denial, or conditional offers.
- Assign appropriate loan pricing and limits, and compute the full amortization schedule.
- Generate adverse action notices and ensure compliance with Equal Credit Opportunity Act (ECOA) reason codes.
6. Funding/Disbursement
- Support electronic signature (e-sign) and Knowledge-Based Authentication (KBA) for agreement finalization.
- Securely vault signed agreements.
- Execute idempotent payouts and maintain an internal ledger for all transactions.
- Implement reconciliation processes for disbursed funds.
- Provide status tracking and notifications to applicants regarding their funding.
Non-Functional Requirements & Compliance
- Security: Ensure PII security through encryption at rest and in transit, robust key management, and Role-Based Access Control (RBAC).
- Reliability: Implement idempotency, retries with backoff, and circuit breakers for all external vendor calls.
- Observability: Provide comprehensive observability, including audit logs and monitoring.
- Data Management: Define clear data retention policies and support GDPR/CCPA-compliant data deletion requests.
- Deployment: Support feature flags and phased rollout strategies for new functionalities.
Deliverables
Describe the high-level architecture, critical APIs, eventing/queues, workflow states, and data model. Explain your approach to failure handling and how the system would scale. Include key trade-offs and assumptions made during your design. Provide at least one small numeric example illustrating pricing or decisioning logic.
AI interview prep
Core dilemma
Balancing the need for rapid, automated loan decisioning and funding with the absolute necessity of stringent financial compliance, robust fraud prevention, and resilient error handling across numerous external, potentially unreliable systems. This is a classic 'speed vs. safety/compliance' challenge in a highly regulated domain.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Design loan application system
Problem Statement
Design a scalable and compliant end-to-end loan origination platform for a small lending startup. The platform will facilitate unsecured term loans for both small businesses and consumers.
Context
The system must handle a peak traffic of 2,000 applications per day, with bursts up to 5 requests per second. Critical performance targets include decisioning within minutes and funding within hours. The architecture should prioritize horizontal scalability and allow for easy replacement of third-party vendors.
Core Requirements
1. User Experience and Product Selection
- Enable users to browse available loan products, displaying details such as amount, term, APR ranges, and eligibility hints.
- Support a pre-qualification process, involving a soft credit or cashflow pre-check, with explicit user consent.
- Provide a multi-device application experience, allowing users to save and resume their application at any point.
2. Application Intake
- Capture comprehensive applicant data, including identity, business information, income/cashflow details, loan purpose, and supporting documents.
- Implement Know Your Customer (KYC)/Customer Identification Program (CIP) and Anti-Money Laundering (AML)/Office of Foreign Assets Control (OFAC) screening.
- Manage user consents, including FCRA disclosures, credit pull authorizations, and bank data access permissions.
- Facilitate document uploads and bank account linking (e.g., via a financial data aggregator).
3. Underwriting Workflow (Internal)
- Orchestrate a series of automated and manual tasks, such as credit pulls, bank statement fetching, identity verification, and fraud screens.
- Integrate a rule engine and Machine Learning (ML) scoring models for automated decisioning.
- Provide a manual review queue and an analyst console for human intervention and oversight.
- Maintain a comprehensive audit trail and generate clear reason codes for all decisions.
4. External Integrations
- Connect with one or more credit bureaus for both soft and hard credit pulls.
- Integrate with bank statement and cashflow aggregation services for read-only access to financial data.
- Utilize payment rails (e.g., ACH/wire) for loan disbursements, incorporating webhook-based status updates.
5. Decisioning and Offer
- Apply risk scoring and credit policies to determine approval, denial, or conditional offers.
- Assign appropriate loan pricing and limits, and compute the full amortization schedule.
- Generate adverse action notices and ensure compliance with Equal Credit Opportunity Act (ECOA) reason codes.
6. Funding/Disbursement
- Support electronic signature (e-sign) and Knowledge-Based Authentication (KBA) for agreement finalization.
- Securely vault signed agreements.
- Execute idempotent payouts and maintain an internal ledger for all transactions.
- Implement reconciliation processes for disbursed funds.
- Provide status tracking and notifications to applicants regarding their funding.
Non-Functional Requirements & Compliance
- Security: Ensure PII security through encryption at rest and in transit, robust key management, and Role-Based Access Control (RBAC).
- Reliability: Implement idempotency, retries with backoff, and circuit breakers for all external vendor calls.
- Observability: Provide comprehensive observability, including audit logs and monitoring.
- Data Management: Define clear data retention policies and support GDPR/CCPA-compliant data deletion requests.
- Deployment: Support feature flags and phased rollout strategies for new functionalities.
Deliverables
Describe the high-level architecture, critical APIs, eventing/queues, workflow states, and data model. Explain your approach to failure handling and how the system would scale. Include key trade-offs and assumptions made during your design. Provide at least one small numeric example illustrating pricing or decisioning logic.