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Market Analysis9 min readPublished 8 April 2025Updated 18 April 2026

Q1 2025 Loan Approval Trends: Which Profiles Banks Approved

We analysed 1,248 applications processed by Malaysian banks in Q1 2025 to see which incomes, industries, and DSR levels succeeded.

Data Insights Lab

Quantitative analyst

Reviewed by: GURU Credits Senior ConsultantLast reviewed: 18 April 2026
Financial DisclaimerContent is for educational purposes only and does not constitute financial, legal, or tax advice. Loan approval depends on bank policy and your profile. Always verify rates and terms with the lender.
Q1 2025 Loan Approval Trends: Which Profiles Banks Approved

Q1 2025: Loan Approval Snapshot

Using anonymised pipelines from partner banks, we reviewed 1,248 applications (home, personal, business) submitted between January and March 2025.

Approval Rate by Product

| Product | Approval Rate | Notes | |---------|---------------|-------| | Home Loans | 63% | Higher approvals for joint borrowers with combined income > RM8k | | Personal Loans | 54% | Strong bias towards salaried applicants with 6+ months tenure | | SME/Business Loans | 41% | Cashflow statements required in 78% of successful cases |

What Helped Applicants Win

  1. DSR sweet spot – approvals peaked at 45% – 55% DSR. Above 60% dropped approval odds by 28%.
  2. Industry resilience – healthcare, oil & gas, and digital services enjoyed 10% higher approvals.
  3. Documentation completeness – applicants who uploaded supporting docs within 48 hours saw 2x faster approvals.

Signals That Triggered Declines

  • Unresolved PTPTN obligations were cited in 18% of rejections.
  • Gig income without bank statements led to automatic declines in 70% of cases.
  • Multiple enquiries (4+ in 60 days) lowered scorecards significantly.

How to Use This Insight

  • Benchmark your own DSR using our eligibility test.
  • Prepare a clean documentation pack before submitting.
  • If self-employed, show 6 months of consistent revenue in one bank account.

About the Dataset

  • Period: 1 Jan – 31 Mar 2025
  • Region: Major urban centres in Peninsular Malaysia
  • Sample: Mix of Tier-1 and Tier-2 banks

Need personalised odds? Our analysts can simulate your approval probability using your CCRIS data.

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About the Author

Data Insights Lab

Quantitative analyst

The insights lab cross-references GURU Credits anonymised case data (1,000+ consultations) with public BNM and DOSM datasets to surface approval patterns and rejection drivers.

Expertise: Analyses approval patterns across anonymised client records and public datasets

Reviewed by: GURU Credits Senior ConsultantUpdated 18 April 2026
analysisloan approvalDSRdata

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