Request Multiple Quotes from Credit Agencies, Suppliers & Manufacturers

The challenge

The solution

The outcome

Requirements

• 1. Define business need, scope, and use cases; confirm countries, segments, volumes, and service levels required.
• 2. Set objectives and success criteria; cost, coverage, data quality, speed, compliance, and customer experience.
• 3. Identify regulatory, legal, privacy, and data-residency requirements; confirm local licensing and permissible use.
• 4. Build supplier shortlist; include national and international agencies, niche specialists, and alternative data providers.
• 5. Assess data coverage and quality; depth, freshness, match rates, bureau score performance, and adverse action support.
• 6. Evaluate product fit; reports, scores, monitoring, decisioning, fraud, collections, KYC/AML, and APIs.
• 7. Review technology and integration; API reliability, batch options, security, sandbox, documentation, and support.
• 8. Compare commercial model; pricing, minimums, fees, rebates, commitments, and total cost of ownership.
• 9. Check operational capability; onboarding time, service desk, SLAs, issue resolution, and business continuity.
• 10. Perform risk and due diligence; financial stability, information security, SOC/ISO, audit rights, and subcontractors.
• 11. Confirm governance and controls; ownership, approval process, usage policies, access management, and reporting.
• 12. Run pilots and proofs of concept; validate data accuracy, decision impact, and operational performance.
• 13. Negotiate contract terms; scope, SLAs, liability, termination, data rights, compliance, and change control.
• 14. Plan implementation and onboarding; integration, testing, training, user access, and cutover timeline.
• 15. Establish monitoring and review; KPI tracking, periodic scorecards, compliance checks, and annual renegotiation.
• 16. Define exit and contingency plan; data portability, transition support, dual sourcing, and fallback provider.

Best practices

• 1. Define clear business use cases before buying any credit data or services.
• 2. Verify the agency’s data sources, refresh frequency, and coverage.
• 3. Check legal, regulatory, and privacy compliance for all intended uses.
• 4. Assess data accuracy, completeness, and dispute resolution processes.
• 5. Match the product to your credit policy, risk model, and customer segments.
• 6. Require transparent scoring, rating, and decisioning methodologies.
• 7. Test integration with your CRM, ERP, underwriting, and workflow systems.
• 8. Establish data governance, access controls, and audit trails.
• 9. Review SLA commitments for uptime, delivery speed, and support response.
• 10. Compare total cost of ownership, including licensing, usage, and implementation.
• 11. Validate vendor security controls, certifications, and incident response plans.
• 12. Pilot the service with a limited portfolio before full deployment.
• 13. Monitor performance regularly with KPIs such as approval rate, delinquency, and default.
• 14. Maintain documented procedures for data updates, exceptions, and model overrides.
• 15. Reassess the agency relationship periodically to ensure continued business value.