Credit Manager — Origination & Portfolio Growth at Pesapal

Position Purpose

• Pesapal is seeking a commercially driven Credit Manager to grow our merchant lending book. This is a growth and origination role, not a back-office control role: your job is to convert Pesapal's proprietary transaction data and credit scores into more merchants borrowing, borrowing more, and borrowing again — safely. We already sit on a rich data ecosystem of POS flows, e-commerce volumes, reservation data and digital spend, and a large number of merchants are creditworthy today and simply not borrowing. You will own that gap.
• Importantly, we lend in partnership. Pesapal originates, scores and services merchant credit alongside licensed Digital Credit Providers (DCPs) and banks, who bring the lending licence, the balance sheet, or both. We bring what partners cannot easily replicate: the merchant relationship, the daily transaction data, the credit score built on it, and the distribution. This makes the role dual-sided — you will grow the book on the merchant side and make the partnerships work on the lender side, keeping partner appetite, pricing and limits aligned with the volume of good merchants our data identifies.
• Critically, you will scale the book through the platform, not through headcount. Every lesson you learn in the market — which merchant profiles repay, which signals predict trouble, which limits and tenors get taken up — must end up codified in our digital origination platform as decision rules, eligibility criteria and limit logic. Your success is measured not by how many deals you personally wrote, but by how much of your credit judgement now runs automatically, at volume, without you in the loop. You will not manage Credit Operations, Data Science or Collections; you will work side by side with them and with our lending partners.

Key Responsibilities

Loan Book Growth & Origination

• Own the Growth Number: Carry the disbursement, active borrower and outstanding loan book (OLB) targets for your markets and segments, across all partner lending programmes.
• Build the Origination Engine: Design and run the end-to-end funnel — from identifying eligible merchants in the pre-scored base through offer, application, partner approval and disbursement — and lift conversion at every step.
• Activate the Dormant Base: Systematically work the population of merchants who already qualify but have never drawn down, and diagnose why they don't.
• Drive Repeat & Deepening: Grow repeat borrowing, top-ups, limit utilisation and graduated limit increases, and run pre-approved offers and seasonal working-capital campaigns with Marketing, Product and the relevant partner.
• Enable the Frontline: Equip Sales, Relationship and Merchant Success teams to position credit confidently — talk tracks, eligibility rules, objection handling and referral routes.

Lending Partnerships with DCPs & Banks

• Own the Commercial Relationship: Act as Pesapal's day-to-day counterpart to our lending partners, running the joint pipeline, performance reviews and the working relationship at credit and product level.
• Negotiate & Expand Appetite: Use portfolio evidence to secure larger allocations, higher limits, broader eligibility criteria, better pricing and faster decisioning.
• Keep the Joint Machinery Running: Work with Credit Operations, Finance and the partner on data exchange, decisioning integration, disbursement and repayment flows, reconciliation and revenue share, escalating blockages before they cost volume.
• Report with Credibility: Own the portfolio narrative our partners see — vintage performance, funnel metrics, NPL and recovery trends — so Pesapal is consistently the partner they want to allocate more capital to.

Codifying Credit Learning Into the Platform

• Turn Judgement Into Rules: Translate what you learn originating in the market — merchant behaviour, decline patterns, repayment signals, exception cases — into credit policy expressed as decision rules, eligibility criteria, and limit and pricing logic.
• Own the Credit Strategy in the Decision Engine: Define and continuously refine the cut-offs, scorecard bands, limit-assignment and step-up rules that govern automated decisions, working with Product, Engineering and Data Science to get them built and released.
• Raise Straight-Through Processing: Grow the share of merchants who receive an instant, fully automated decision, and treat every recurring manual exception as the specification for the next platform rule — so volume grows without growing the credit team.
• Commercialise the Score: Work with the Lead Data Scientist to turn model output into commercial decisions — who receives an offer, how large, at what price, over what tenor — and run champion/challenger tests that quantify volume gained against risk taken.
• Close the Feedback Loop: Feed origination intelligence — partner decline reasons, funnel drop-off points, thin-file and underserved segments — back into scoring and policy, and monitor the vintage performance of the cohorts you write.

Credit Assessment, Policy & Collaboration

• Assess & Recommend: Make sound credit decisions within delegated limits, and prepare well-argued cases for exposures above your threshold or requiring partner sign-off.
• Shape Policy With Evidence: Recommend changes to credit policy, limits and eligibility criteria — internally and with partners — supported by portfolio data, knowing when to loosen to capture safe share and when to tighten.
• Respect the Firewalls: Grow the book within the approved risk appetite of Pesapal and each partner, maintaining clear separation between origination, underwriting and collections.
• Work Across Functions: Partner with Credit Operations on clean handover and fast disbursement, Data Science on model design and rollout, Collections on early-warning feedback, and Finance and Compliance on pricing, revenue share, provisioning, Central Bank requirements, data protection and AML/KYC.

Candidate Profile & Experience

Required Qualifications

• Experience: 3–6 years in credit, SME or commercial lending, digital lending or credit analytics, with a clear record of growing a loan book rather than only managing or monitoring one — evidenced by volumes disbursed, borrowers acquired, book grown or conversion improved.
• Partnership Exposure: Experience working across institutional counterparties — banks, DCPs, microfinance institutions, fintech partners or funders — and comfort holding a commercial relationship with a lender rather than simply reporting to one.
• Credit & Systems Fundamentals: Ability to assess an MSME, size a limit sensibly and defend a decision to a partner credit committee, together with experience translating credit policy into the rules, criteria and limit logic that a decision engine or loan origination platform executes.
• Data Fluency: Comfort interrogating dashboards and working with scorecard output, preferably with the ability to write your own SQL queries or build your own analysis in Excel.
• Market Knowledge: Deep familiarity with the Kenyan MSME and merchant ecosystem and how DCPs and banks in this market think about credit. Experience in a digital lender, fintech or a bank's MSME / cash-flow lending unit, and exposure to alternative-data underwriting, is highly desirable.

Key Competencies & Traits

• Commercial Drive With Credit Discipline: You chase growth, but you understand that a book grown badly is worse than no growth at all — and that a partner's trust, once lost, is expensive to rebuild.
• Data-Driven Credit Mindset: You accept that a merchant's daily POS consistency can tell you more than a three-year audited financial statement, and you can prove it to a sceptical bank.
• Influence Without Authority: You get results through peers in Operations, Data Science, Collections and Sales, and through partner institutions, without managing any of them.
• Systems Thinker, Not a Deal Doer: When you solve a credit problem once, your instinct is to make sure the platform solves it every time after that.
• Bias to Experiment: You would rather run a controlled pilot on 200 merchants this month than write a strategy paper about it, and you understand what an MSME actually needs working capital for, and when.

Key Performance Indicators (KPIs)

• Loan Book Growth: Value disbursed and outstanding loan book against target, across all partner programmes.
• Take-Up & Conversion: Proportion of eligible merchants who accept and draw down, funnel conversion at each stage including partner approval, and growth in active borrowers, repeat borrowing and limit utilisation.
• Partnership Performance: Funding capacity secured and utilised, expansion of partner appetite and eligibility, and successful onboarding of new lending partners.
• Quality of Originated Business: First-payment default and vintage NPL on the cohorts you write, within budgeted and partner-agreed boundaries.
• Automation & Speed: Straight-through processing and automated approval rates, reduction in applications needing manual review, and time from eligibility to disbursement.