Regional Collections Leader: Drive Performance & Growth

Home Credit; Canlandog; On-site; PHP 900,000 - 1,400,000; Full time

Benefits offered by this job

Up to 20% bonus

Health insurance starting Day 1

Mental health support

Wellness leaves

Career mobility

Learning opportunities

Job summary

Home Credit Philippines is seeking an Area Manager to drive collections across assigned clusters and regions. You will coordinate with Field Supervisors and Field Collectors to align performance with department targets.

The role requires visits to local offices, coaching of supervisors, and regular performance reviews. Motorbike driving is preferred, with the goal of optimizing field processes and outcomes.

Qualifications

• At least 3 years’ experience in field collection.
• Familiar with assigned region and a residence in the area preferred.
• Minimum 2 years’ experience as Area Manager or Senior Supervisor.
• Must know how to drive motorcycle with driver’s license.
• Advanced knowledge of MS Office.

Responsibilities

• Drives collections for specific clusters/areas and aligns performance to targets.
• Visits local offices to ensure process alignment and conducts team meetings.
• Provides regular feedback and coaching to assigned Field Supervisors.
• Conducts monthly performance reviews and sets action plans.
• Monitors KPIs and trends to drive attainment of monthly region targets.
• Collaborates with HR on recruitment and employee referrals.
• Works with Collections Management for task execution and program improvements.
• Ensures adherence to Code of Conduct and company policies.

Skills

Field collection

Motorcycle riding

MS Office

Leadership

Tools

MS Office

Job description

Home Credit Philippines is seeking an Area Manager to drive collections across assigned clusters and regions. You will coordinate with Field Supervisors and Field Collectors to align performance with department targets.

The role requires visits to local offices, coaching of supervisors, and regular performance reviews. Motorbike driving is preferred, with the goal of optimizing field processes and outcomes.