问题我们不知道哪些产品在赚钱 › 金融科技

我们不知道哪些产品在赚钱
in 金融科技

每家金融科技公司都有一个大家默认赚钱的产品,而这个产品往往在占用仓储额度。 金融科技公司面对的问题不是通用版本。借贷业务把利润表固定下来,把原本乘以 7 倍的收入变成了乘以 2 倍的收入——因此忽略混合费率的答案必然出错。分析必须从坏账率和贡献毛利开始,而不是从收入开始。

简短回答

每家金融科技公司都有一个大家默认赚钱的产品,而这个产品往往在占用仓储额度。 金融科技公司面对的问题不是通用版本。借贷业务把利润表固定下来,把原本乘以 7 倍的收入变成了乘以 2 倍的收入——因此忽略混合费率的答案必然出错。分析必须从坏账率和贡献毛利开始,而不是从收入开始。

产品级利润确实难算,因为风险、合规等大部分成本是共享的,而按 TPV 分摊的常规做法会直接把答案定死。按支付规模分摊共享成本,会让高 TPV 产品显得昂贵、低 TPV 产品显得高效——这恰恰反了,因为低 TPV 产品往往消耗了不成比例的获客和坏账资源。

可行的做法是只分摊真正可追溯的成本,比如直接坏账和商户上线成本,其余保持未分摊。这样得到的是各产品的贡献毛利,以及一个诚实的共享成本池(含仓储额度),远比没人相信的完全分摊数字更有用。

结果通常不舒服。大多数组合里,少数商户段在承担全部成本,至少有一条存在多年的产品其实一直在亏钱,而所有人之前都以为它在盈利。

如何判断这确实是你的问题

这三者同时出现才是标志。单独一个通常指向其他问题。

✓ 只用全量 TPV 的混合费率讨论盈利能力
✓ 尽管做过多次贡献毛利复盘,却从未停掉任何商户群或产品
✓ CFO 和产品负责人对同一条借贷产品是否覆盖仓储额度给出不同答案

通常会让情况更糟的做法。 用任意的 TPV 分摊规则把仓储额度和总部成本完全摊到每个产品上,得出一个建立在未经验证规则上的精确数字,还因为看起来严谨而被维护。

Who this is for — and who it is not

It is for you if you run or finance a fintech and product profitability is quoted as a company-wide gross margin. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.

It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

实际运行分析时的样子

Below is an excerpt from a real run of this analysis on 一家金融科技公司. It is a sample profile rather than a customer, and it is engine output translated from English — this is the format you get, on your own numbers.

The subject is Verrano Pay, a sample company profile used for testing rather than a customer — $84M net revenue, 28,000 merchants, $9.4B of payment volume.

Excerpt from a real Percision run · Quick Market Scan · sample company profile

The move. Scale lending book from $110M to $260M advances using existing distribution and data assets while maintaining charge-off rate below 9.0% covenant.

The leak it closes. Reduces 26% partner rev-share leakage by increasing merchant stickiness through lending relationship

The assumption it rests on. Platform partners maintain 180-day termination clauses without exercising exit — the engine put the probability at 0.7.

What the run committed to
Investment required$0 incremental equity
Expected return4.5x
Revenue, year 1$24.1M lending revenue (30% growth)
Revenue, year 2$31.3M lending revenue (30% growth)
Revenue, year 3$40.7M lending revenue (30% growth)
Exit criteriaTerminate if charge-off rate exceeds 8.7% for two consecutive quarters OR if any platform partner terminates contract

This is one move out of a full analysis. Read a complete report — every page, no email required.

引擎如何处理这个问题

This question routes to Matrix Strategy, one of 29 engagements the platform runs. For 金融科技公司 it works through blended take rate, charge-off rate, contribution margin and CAC by channel, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.

You watch the analysis get built before paying anything. 在此阅读完整报告 if you would rather see the depth first.

人们关于此问题的常见提问

需要做作业成本法吗?

几乎不需要。可追溯成本加上未分摊的成本池就能排出优先级,而优先级才是你要采取行动的依据。完整的作业成本法往往会拖过当初触发它的决策期限。

支持其他产品的产品怎么办?

明确写出来并定价。一条真正拉动盈利收入的亏损产品,就是一笔有名字的营销费用——只要有人真正做过这个决定,这就没问题。

多久需要重做一次?

每年一次,或者在产品结构发生重大变化后重做。排序比具体数字更稳定,所以每次做都会更快。

Is this different in fintech than in other industries?

Materially, yes. Lending fixed the P&L and converts revenue worth a 7x multiple into revenue worth a 2x multiple — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are blended take rate, charge-off rate, contribution margin, and an answer built on industry-general benchmarks will usually point at the wrong one first.

What data do I need before this analysis is worth running for a fintech?

Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on blended take rate and charge-off rate. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.

When is Percision the wrong tool?

Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Does Percision replace a lawyer, tax advisor, auditor, or AI implementation team?

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

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