Electronics Financing — From Transactions to RelationshipsPembiayaan Elektronik — Dari Transaksi ke Relasi
Turning a per-purchase process into a credit limit, priced by riskMengubah proses per-pembelian menjadi sebuah credit limit, dihargai sesuai risiko
"Underwrite the customer once, not every purchase." — the reframe that started it.
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Snapshot
| Role | Product Manager |
| Company | PT KB Finansia Multi Finance (KreditPlus) |
| Timeline | 2023 – 2025 |
| Team | Cross-functional — Product, Risk, Engineering, Compliance |
| Domain | Risk-based product & monetization |
TL;DR
Electronics financing was purely transactional: every purchase meant re-submitting data, another CA analysis, and the same flat rate and DP for everyone — while fraud slipped through eyeball checks and low-risk customers were quietly overpriced.
I reframed it from a transaction into a relationship: a tiered Credit Limit (Blue / Gold / Platinum) plus Risk-Based Pricing, on a fraud-hardened acquisition journey. Application fraud dropped sharply and sales more than tripled (IDR 1.5B → 5B over three months).
This case study is about treating pricing and limits as product levers, not finance settings — and what that unlocked.
1. Context
Electronics is a high-frequency, competitive financing category — many competitors had already moved to low or zero down payment. KB Finansia, meanwhile, was underwriting each purchase from scratch and pricing everyone the same.
2. The Problem — "We re-met every customer as a stranger."
- Repetitive friction. Returning customers re-entered data and were re-analyzed on every single purchase.
- Fraud gaps. Without EKYC, central CAs still did manual eyeball checks — a soft spot fraudsters could exploit.
- Flat pricing ignored risk. Low-risk customers paid the same rate and DP as high-risk ones, so we lost the safest customers to cheaper competitors.
"I bought from you last month — why am I filling out the same forms all over again?" — a returning customer, relayed by a dealer
The real problem wasn't "approve more." It was: "stop re-underwriting loyal customers, and price by risk."
3. Discovery — Reading the repayment behavior
- Repeat behavior was a pre-approval signal. Customers with clean repayment histories were being made to re-prove themselves needlessly.
- Behavior data made fair tiering possible. Payment patterns let us tier and price customers by actual risk instead of a flat default.
- Down payment was a competitive battleground. Zero-DP for low risk wasn't a giveaway — it was the price of staying in the game.
4. The Strategic Bet — Build a credit limit, not a faster transaction
The conventional move was to speed up the per-transaction flow. I bet instead on changing the unit of the relationship: underwrite a customer once into a limit, then let them transact within it — converting a stop-start funnel into an ongoing relationship.
5. Prioritization & Trade-offs — Deciding what to build first
Decision 1 — Tiered Credit Limit (Blue / Gold / Platinum). Each class carries its own journey and transaction plafond, set by risk profile and repayment behavior — so repeat customers transact within their limit without re-submitting. Trade-off: this leans on scoring maturity, so tiers were defined conservatively at first.
Decision 2 — Risk-Based Pricing (RBP). Rate and DP scale with risk; low-risk customers get a lower rate and even 0 DP. Pricing became a growth lever aimed squarely at the customers we most wanted to keep.
Decision 3 — Close fraud before scaling. I re-engineered the acquisition journey to introduce EKYC and shut the eyeball-check gap first — because scaling sales on a leaky funnel would have multiplied the fraud, not the profit.
6. Execution — Shipping risk-based product under OJK rules
Built across Risk, Engineering, and Compliance, with fraud and credit-risk indicators monitored closely through rollout. Sequencing fraud-hardening ahead of the growth levers kept the expansion safe.
7. Impact
- Application fraud: sharply reduced
- Sales: more than tripled (IDR 1.5B → IDR 5B over three months)
8. Reflections — What I'd carry forward
- Change the unit, change the game. Moving from transaction to credit limit reframed the entire product.
- Pricing is a product lever. Used deliberately, RBP became a growth engine, not just a finance setting.
- Harden before you scale. Closing fraud first is what made that growth profitable growth.
Prepared by Hamdan Fauzi — Product Manager. Some figures generalized for company confidentiality. Happy to walk through the full version in conversation.
"Nilai konsumennya sekali, bukan tiap pembelian." — reframe yang memulai semuanya.
Snapshot
| Peran | Product Manager |
| Perusahaan | PT KB Finansia Multi Finance (KreditPlus) |
| Timeline | 2023 – 2025 |
| Tim | Lintas fungsi — Product, Risk, Engineering, Compliance |
| Domain | Produk berbasis risiko & monetisasi |
TL;DR
Pembiayaan elektronik sepenuhnya transaksional: setiap pembelian berarti input data ulang, analisa CA lagi, dan rate serta DP yang sama rata untuk semua — sementara fraud lolos lewat eyeball checking dan konsumen low risk diam-diam kemahalan.
Saya mengubahnya dari transaksi menjadi relasi: Credit Limit berjenjang (Blue / Gold / Platinum) plus Risk-Based Pricing, di atas journey akuisisi yang tahan fraud. Fraud aplikasi turun tajam dan penjualan lebih dari tiga kali lipat (Rp 1,5 miliar → 5 miliar dalam tiga bulan).
Studi kasus ini tentang memperlakukan pricing dan limit sebagai tuas produk, bukan setelan keuangan — dan apa yang dibukanya.
1. Konteks
Elektronik adalah kategori pembiayaan berfrekuensi tinggi dan kompetitif — banyak kompetitor sudah pindah ke DP rendah atau nol. Sementara itu, KB Finansia masih meng-underwrite tiap pembelian dari nol dan menghargai semua orang sama.
2. Masalah — "Kami menyambut setiap konsumen seolah orang asing."
- Friksi berulang. Konsumen lama mengisi data ulang dan dianalisa ulang di setiap pembelian.
- Celah fraud. Tanpa EKYC, CA sentral masih melakukan eyeball checking manual — titik lemah yang bisa dimanfaatkan pelaku fraud.
- Pricing seragam mengabaikan risiko. Konsumen low risk membayar rate dan DP yang sama dengan high risk, jadi konsumen teraman lari ke kompetitor yang lebih murah.
"Saya beli bulan lalu — kenapa sekarang harus isi formulir yang sama lagi?" — konsumen lama, disampaikan lewat dealer
Masalah sebenarnya bukan "setujui lebih banyak." Melainkan: "berhenti meng-underwrite ulang konsumen setia, dan beri harga sesuai risiko."
3. Discovery — Membaca perilaku pembayaran
- Perilaku berulang adalah sinyal pre-approval. Konsumen dengan riwayat bayar bersih dipaksa membuktikan diri lagi tanpa perlu.
- Data perilaku memungkinkan penjenjangan yang adil. Pola pembayaran memungkinkan menjenjangkan dan menghargai konsumen sesuai risiko nyata, bukan default seragam.
- Down payment adalah medan tempur kompetitif. Nol-DP untuk low risk bukan bagi-bagi hadiah — itu harga untuk tetap di permainan.
4. Taruhan Strategis — Bangun credit limit, bukan transaksi yang lebih cepat
Langkah konvensionalnya: mempercepat alur per-transaksi. Saya justru bertaruh pada mengubah unit relasinya: underwrite konsumen sekali ke dalam sebuah limit, lalu biarkan mereka bertransaksi di dalamnya — mengubah funnel stop-start menjadi relasi berkelanjutan.
5. Prioritas & Trade-off — Menentukan apa yang dibangun lebih dulu
Keputusan 1 — Credit Limit berjenjang (Blue / Gold / Platinum). Tiap kelas punya journey dan plafon transaksi sendiri, ditetapkan oleh profil risiko dan perilaku bayar — sehingga konsumen lama bertransaksi dalam limitnya tanpa input ulang. Trade-off: ini bersandar pada kematangan scoring, jadi jenjang awalnya didefinisikan konservatif.
Keputusan 2 — Risk-Based Pricing (RBP). Rate dan DP menyesuaikan risiko; konsumen low risk dapat rate lebih rendah bahkan 0 DP. Pricing menjadi tuas pertumbuhan yang diarahkan tepat ke konsumen yang paling ingin kami pertahankan.
Keputusan 3 — Tutup fraud sebelum menskalakan. Saya mendesain ulang journey akuisisi untuk menghadirkan EKYC dan menutup celah eyeball-check lebih dulu — karena menskalakan penjualan di atas funnel bocor justru melipatgandakan fraud, bukan profit.
6. Eksekusi — Merilis produk berbasis risiko di bawah aturan OJK
Dibangun lintas Risk, Engineering, dan Compliance, dengan indikator fraud dan risiko kredit dipantau ketat sepanjang rollout. Mengurutkan fraud-hardening di depan tuas pertumbuhan menjaga ekspansi tetap aman.
7. Dampak
- Fraud aplikasi: turun tajam
- Penjualan: lebih dari tiga kali lipat (Rp 1,5 miliar → Rp 5 miliar dalam tiga bulan)
8. Refleksi — Yang akan saya bawa terus
- Ubah unitnya, ubah permainannya. Beralih dari transaksi ke credit limit me-reframe seluruh produk.
- Pricing adalah tuas produk. Dipakai dengan sengaja, RBP menjadi mesin pertumbuhan, bukan sekadar setelan keuangan.
- Perketat sebelum menskalakan. Menutup fraud lebih dulu yang membuat pertumbuhan itu menjadi pertumbuhan yang menguntungkan.
Disusun oleh Hamdan Fauzi — Product Manager. Sebagian angka digeneralisasi demi kerahasiaan perusahaan. Dengan senang hati menjelaskan versi lengkapnya secara langsung.