> ## Documentation Index > Fetch the complete documentation index at: https://docs.didit.me/llms.txt > Use this file to discover all available pages before exploring further. # 交易监控规则回测 API｜Didit 管理 API > 在启用前，用历史交易回测假设的 KYT 规则：查看匹配数、已评估数和受影响主体。只读且免费。Didit 提供。 回测规则 API 提示词 将提示词复制到剪贴板 \

\`Backtest a hypothetical rule configuration against my recent transactions.

Endpoint:
POST https://verification.didit.me/v3/transactions/rules/backtest/

Authentication:
Use the x-api-key header with my Didit API key.

Request body (application/json):
\{
"conditions": [{"field": "currency", "operator": "eq", "value": "EUR"},
\{"field": "amount", "operator": "lt", "value": 10000}],
"aggregation": [{"metric": "count", "operator": "gte", "value": 20, "window": "30d",
               "filters": {"direction": "INBOUND", "transaction_type": "finance", "currency": "EUR", "subject_vendor_data": "__current__"}},
              \{"metric": "max", "field": "amount", "operator": "lt", "value": 10000, "window": "30d",
               "filters": {"direction": "INBOUND", "transaction_type": "finance", "currency": "EUR", "subject_vendor_data": "__current__"}}],
"evaluation_mode": "ALL",
"scope": {"transaction_types": ["finance"], "directions": ["INBOUND"]},
"period_days": 90          // 1-365, default 90
}

Response:
\{ "evaluated": 4820, "matched": 12, "affected_entities": 4, "period_days": 90 }

Behavior:
\- Read-only and free: no rule is created, no transaction is modified, no rule runs are recorded.
\- Evaluates the most recent transactions in the period, up to the backtest cap.
\- affected_entities counts distinct subjects (by vendor_data) among the matches.
\- Use it before switching a rule to ACTIVE; a surprising match count means the thresholds need tuning.
\- Copy the candidate rule EXACTLY: same conditions, aggregation, evaluation_mode and scope. Omitted conditions, aggregation and scope add no constraints of their own; dropping scope can include directions or transaction types the saved rule skips. Omitted evaluation_mode defaults to ALL (which can reduce matches for an ANY rule), and omitted period_days defaults to 90 days, not unlimited history.

Sandbox fixtures for this example: at least 20 inbound EUR finance transactions for the same subject within 30 days, each with raw amount below 10000. No normalized amount is required. Sandbox ingestion does not evaluate rules; call backtest explicitly.

Failure modes:
\- 400 - same condition/aggregation/scope validation as rule create.`

\
粘贴到 ## OpenAPI ````yaml zh/openapi-25.json POST /v3/transactions/rules/backtest/ openapi: 3.0.0 info: version: 3.0.0 title: Didit Verification API description: 身份证件验证 API。使用 x-api-key 请求头进行身份验证。 servers: - url: https://verification.didit.me security: [] tags: [] paths: /v3/transactions/rules/backtest/: post: tags: - Transactions summary: 回测规则配置 description: >- 在不创建规则或更改任何交易的情况下，对照您最近的交易（按最新优先排序，直至达到回测上限）评估假设的规则配置。在激活规则之前使用它，可查看该规则可能匹配的频率以及会影响多少主体。 operationId: backtestTransactionRules requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/TransactionRuleBacktestRequest' example: conditions: - field: currency operator: eq value: EUR - field: amount operator: lt value: 10000 aggregation: - metric: count operator: gte value: 20 window: 30d filters: direction: INBOUND transaction_type: finance subject_vendor_data: __current__ currency: EUR - metric: max field: amount operator: lt value: 10000 window: 30d filters: direction: INBOUND transaction_type: finance subject_vendor_data: __current__ currency: EUR evaluation_mode: ALL scope: transaction_types: - finance directions: - INBOUND period_days: 90 responses: '200': description: 回测统计数据。 content: application/json: schema: $ref: '#/components/schemas/TransactionRuleBacktestResult' example: evaluated: 4820 matched: 12 affected_entities: 4 period_days: 90 security: - ApiKeyAuth: [] x-codeSamples: - lang: curl label: curl source: >- curl -X POST 'https://verification.didit.me/v3/transactions/rules/backtest/' \ -H 'x-api-key: YOUR_API_KEY' \ -H 'Content-Type: application/json' \ -d '{"conditions": [{"field": "currency", "operator": "eq", "value": "EUR"}, {"field": "amount", "operator": "lt", "value": 10000}], "aggregation": [{"metric": "count", "operator": "gte", "value": 20, "window": "30d", "filters": {"direction": "INBOUND", "transaction_type": "finance", "subject_vendor_data": "__current__", "currency": "EUR"}}, {"metric": "max", "field": "amount", "operator": "lt", "value": 10000, "window": "30d", "filters": {"direction": "INBOUND", "transaction_type": "finance", "subject_vendor_data": "__current__", "currency": "EUR"}}], "evaluation_mode": "ALL", "scope": {"transaction_types": ["finance"], "directions": ["INBOUND"]}, "period_days": 90}' - lang: python label: Python source: |- from didit import Didit # Reads DIDIT_API_KEY. client = Didit() result = client.transactions.rules.backtest( conditions=[{ "field": "currency", "operator": "eq", "value": "EUR", }, { "field": "amount", "operator": "lt", "value": 10000, }], aggregation=[{ "metric": "count", "operator": "gte", "value": 20.0, "window": "30d", "filters": {"direction": "INBOUND", "transaction_type": "finance", "subject_vendor_data": "__current__", "currency": "EUR"}, }, { "metric": "max", "field": "amount", "operator": "lt", "value": 10000.0, "window": "30d", "filters": {"direction": "INBOUND", "transaction_type": "finance", "subject_vendor_data": "__current__", "currency": "EUR"}, }], evaluation_mode="ALL", scope={ "transaction_types": ["finance"], "directions": ["INBOUND"], }, period_days=90, ) print(result) - lang: javascript label: Node.js source: |- import Didit from "@didit-protocol/sdk-node"; // Reads DIDIT_API_KEY. const didit = new Didit(); const result = await didit.transactions.rules.backtest({ conditions: [{ field: "currency", operator: "eq", value: "EUR", }, { field: "amount", operator: "lt", value: 10000, }], aggregation: [{ metric: "count", operator: "gte", value: 20.0, window: "30d", filters: { direction: "INBOUND", transaction_type: "finance", subject_vendor_data: "__current__", currency: "EUR" }, }, { metric: "max", field: "amount", operator: "lt", value: 10000.0, window: "30d", filters: { direction: "INBOUND", transaction_type: "finance", subject_vendor_data: "__current__", currency: "EUR" }, }], evaluation_mode: "ALL", scope: { transaction_types: ["finance"], directions: ["INBOUND"], }, period_days: 90, }); console.log(result); - lang: go label: Go source: "ctx := context.Background()\n// Reads DIDIT_API_KEY.\nclient := didit.NewClient()\n\nresult, err := client.Transactions.Rules.Backtest(ctx, didit.TransactionRuleBacktestRequest{\n\tConditions: didit.Some([]didit.TransactionRuleConditionParam{{\n\t\tField: \"currency\",\n\t\tOperator: \"eq\",\n\t\tValue: didit.Some[any](\"EUR\"),\n\t}, {\n\t\tField: \"amount\",\n\t\tOperator: \"lt\",\n\t\tValue: didit.Some[any](10000),\n\t}}),\n\tAggregation: didit.Some([]didit.TransactionRuleAggregationParam{{\n\t\tMetric: didit.Some(didit.TransactionRuleAggregationMetric(\"count\")),\n\t\tOperator: didit.Some(didit.TransactionRuleAggregationOperator(\"gte\")),\n\t\tValue: 20.0,\n\t\tWindow: didit.String(\"30d\"),\n\t\tFilters: didit.Some(map[string]any{\"direction\": \"INBOUND\", \"transaction_type\": \"finance\", \"subject_vendor_data\": \"__current__\", \"currency\": \"EUR\"}),\n\t}, {\n\t\tMetric: didit.Some(didit.TransactionRuleAggregationMetric(\"max\")),\n\t\tField: didit.String(\"amount\"),\n\t\tOperator: didit.Some(didit.TransactionRuleAggregationOperator(\"lt\")),\n\t\tValue: 10000.0,\n\t\tWindow: didit.String(\"30d\"),\n\t\tFilters: didit.Some(map[string]any{\"direction\": \"INBOUND\", \"transaction_type\": \"finance\", \"subject_vendor_data\": \"__current__\", \"currency\": \"EUR\"}),\n\t}}),\n\tEvaluationMode: didit.Some(didit.TransactionRuleBacktestRequestEvaluationMode(\"ALL\")),\n\tScope: didit.Some(didit.TransactionRuleScopeParam{\n\t\tTransactionTypes: didit.Some([]string{\"finance\"}),\n\t\tDirections: didit.Some([]didit.TransactionRuleScopeDirections{\"INBOUND\"}),\n\t}),\n\tPeriodDays: didit.Int(90),\n})\nif err != nil {\n\tlog.Fatal(err)\n}\nfmt.Printf(\"%+v\\n\", result)" - lang: java label: Java source: >- import java.util.List; import java.util.Map; import me.didit.Didit; import me.didit.types.TransactionRuleAggregation; import me.didit.types.TransactionRuleBacktestRequest; import me.didit.types.TransactionRuleCondition; import me.didit.types.TransactionRuleScope; // Reads DIDIT_API_KEY. Didit client = new Didit(); var result = client.transactions().rules().backtest(TransactionRuleBacktestRequest.builder() .conditions(List.of( TransactionRuleCondition.builder() .field("currency") .operator(TransactionRuleCondition.Operator.of("eq")) .value("EUR") .build(), TransactionRuleCondition.builder() .field("amount") .operator(TransactionRuleCondition.Operator.of("lt")) .value(10000) .build())) .aggregation(List.of( TransactionRuleAggregation.builder() .metric(TransactionRuleAggregation.Metric.of("count")) .operator(TransactionRuleAggregation.Operator.of("gte")) .value(20.0) .window("30d") .filters(Map.of("direction", "INBOUND", "transaction_type", "finance", "subject_vendor_data", "__current__", "currency", "EUR")) .build(), TransactionRuleAggregation.builder() .metric(TransactionRuleAggregation.Metric.of("max")) .field("amount") .operator(TransactionRuleAggregation.Operator.of("lt")) .value(10000.0) .window("30d") .filters(Map.of("direction", "INBOUND", "transaction_type", "finance", "subject_vendor_data", "__current__", "currency", "EUR")) .build())) .evaluationMode(TransactionRuleBacktestRequest.EvaluationMode.of("ALL")) .scope(TransactionRuleScope.builder() .transactionTypes(List.of("finance")) .directions(List.of(TransactionRuleScope.Directions.of("INBOUND"))) .build()) .periodDays(90L) .build()); System.out.println(result); - lang: php label: PHP source: |- transactions->rules->backtest([ 'conditions' => [[ 'field' => 'currency', 'operator' => 'eq', 'value' => 'EUR', ], [ 'field' => 'amount', 'operator' => 'lt', 'value' => 10000, ]], 'aggregation' => [[ 'metric' => 'count', 'operator' => 'gte', 'value' => 20.0, 'window' => '30d', 'filters' => ['direction' => 'INBOUND', 'transaction_type' => 'finance', 'subject_vendor_data' => '__current__', 'currency' => 'EUR'], ], [ 'metric' => 'max', 'field' => 'amount', 'operator' => 'lt', 'value' => 10000.0, 'window' => '30d', 'filters' => ['direction' => 'INBOUND', 'transaction_type' => 'finance', 'subject_vendor_data' => '__current__', 'currency' => 'EUR'], ]], 'evaluation_mode' => 'ALL', 'scope' => [ 'transaction_types' => ['finance'], 'directions' => ['INBOUND'], ], 'period_days' => 90, ]); print_r($result->toArray()); - lang: ruby label: Ruby source: |- require "didit" # Reads DIDIT_API_KEY. didit = Didit::Client.new result = didit.transactions.rules.backtest( conditions: [{ field: "currency", operator: "eq", value: "EUR", }, { field: "amount", operator: "lt", value: 10000, }], aggregation: [{ metric: "count", operator: "gte", value: 20.0, window: "30d", filters: { direction: "INBOUND", transaction_type: "finance", subject_vendor_data: "__current__", currency: "EUR" }, }, { metric: "max", field: "amount", operator: "lt", value: 10000.0, window: "30d", filters: { direction: "INBOUND", transaction_type: "finance", subject_vendor_data: "__current__", currency: "EUR" }, }], evaluation_mode: "ALL", scope: { transaction_types: ["finance"], directions: ["INBOUND"], }, period_days: 90 ) puts result.to_h - lang: csharp label: .NET source: >- using System; using System.Collections.Generic; using System.Text.Json; using Didit; // Reads DIDIT_API_KEY. using var client = new DiditClient(); var result = await client.Transactions.Rules.BacktestAsync(new TransactionRuleBacktestRequest { Conditions = new TransactionRuleCondition[] { new() { Field = "currency", Operator = "eq", Value = "EUR", }, new() { Field = "amount", Operator = "lt", Value = 10000, }, }, Aggregation = new TransactionRuleAggregation[] { new() { Metric = new TransactionRuleAggregationMetric("count"), Operator = new TransactionRuleAggregationOperator("gte"), Value = 20.0, Window = "30d", Filters = new Dictionary { ["direction"] = "INBOUND", ["transaction_type"] = "finance", ["subject_vendor_data"] = "__current__", ["currency"] = "EUR" }, }, new() { Metric = new TransactionRuleAggregationMetric("max"), Field = "amount", Operator = new TransactionRuleAggregationOperator("lt"), Value = 10000.0, Window = "30d", Filters = new Dictionary { ["direction"] = "INBOUND", ["transaction_type"] = "finance", ["subject_vendor_data"] = "__current__", ["currency"] = "EUR" }, }, }, EvaluationMode = new TransactionRuleBacktestRequestEvaluationMode("ALL"), Scope = new TransactionRuleScope { TransactionTypes = new string[] { "finance" }, Directions = new TransactionRuleScopeDirections[] { "INBOUND" }, }, PeriodDays = 90, }); Console.WriteLine(JsonSerializer.Serialize(result)); components: schemas: TransactionRuleBacktestRequest: type: object properties: conditions: type: array items: $ref: '#/components/schemas/TransactionRuleCondition' default: [] aggregation: type: array items: $ref: '#/components/schemas/TransactionRuleAggregation' default: [] evaluation_mode: type: string enum: - ALL - ANY default: ALL scope: $ref: '#/components/schemas/TransactionRuleScope' period_days: type: integer minimum: 1 maximum: 365 default: 90 description: >- 用于对照近期交易进行评估的假设规则配置。只读且免费：不会创建或修改任何内容。请发送与您打算激活的规则相同的 conditions、aggregation、evaluation_mode 以及 scope。省略 conditions、aggregation 和 scope 不会添加其自身的限制约束；省略 scope 可能会包含已保存规则所跳过的流向或交易类型。省略 evaluation_mode 默认设为 ALL（对于 ANY 规则这可能会减少匹配项），省略 period_days 默认设为 90 天，而非无限制的历史记录。 TransactionRuleBacktestResult: type: object properties: evaluated: type: integer description: 已评估的交易（最近优先，有数量上限）。 matched: type: integer description: 该配置本应匹配的交易。 affected_entities: type: integer description: 匹配项中不同的主体（按 vendor_data 区分）。 period_days: type: integer TransactionRuleCondition: type: object required: - field - operator properties: field: type: string description: >- 要评估的交易字段路径。核心字段：amount、currency、direction、action_type、score、severity、transaction_type、payment_details、preferred_currency_amount（回退到 amount_in_default_currency）、default_currency_code、subject_country、counterparty_country、subject_vendor_data、counterparty_vendor_data、subject_device_fingerprint、counterparty_device_fingerprint、subject_browser_family、subject_browser_version、subject_platform、subject_accept_language、subject_session_age_ms、subject_ip_country、counterparty_ip_country、subject_ip_address、counterparty_ip_address、subject_payment_method_type、subject_payment_method_country、subject_payment_method_fingerprint、subject_payment_method_account_id（以及 counterparty_payment_method_* 等效字段）、travel_rule_status、travel_rule_required、travel_rule_obligations_count、counterparty_dd_status（您对 Travel Rule 交易对手的决策：APPROVED、RESTRICTED 或 BLOCKED，实体遵循其品牌决策）、counterparty_risk_level（LOW、MEDIUM 或 HIGH；在您自己的交易对手筛查被标记时为 HIGH）、counterparty_jurisdiction（交易对手 VASP 的国家/地区）、counterparty_responsiveness（RESPONSIVE、UNRESPONSIVE 或 UNKNOWN）、subject_days_since_previous_transaction、tags，以及在创建交易时通过 custom_properties 提交的任何键的 custom_values.。国家/地区代码字段接受 ISO-2 或 ISO-3；比对前双方均会归一化为 ISO-3。 operator: type: string enum: - eq - ne - gt - gte - lt - lte - in - not_in - contains - not_contains - contains_any - regex - fuzzy_match - exists - is_not_empty - is_not_null - not_exists - is_empty - is_null description: >- 比较运算符。in/not_in 测试成员资格（值可以是一个列表或单个标量）。contains/not_contains 是针对字符串值的大小写不敏感子字符串检查。contains_any 接受一个字符串列表，并在其中任意一项是字段值的大小写不敏感子字符串时匹配。regex 将值模式与字段进行正则匹配。fuzzy_match 使用所需的 `score` 阈值（0-100）与值字符串进行模糊比对。当任意一侧缺失时，gt/gte/lt/lte 绝不会匹配。exists/is_not_empty/is_not_null（别名）和 not_exists/is_empty/is_null（别名）是忽略 `value` 的存在性检查。 value: description: >- 比较值。其结构取决于运算符和 value_type；对于存在性检查运算符，请将其省略。其他所有运算符都需要一个既不是 `null` 也不是空列表的值，否则规则将被拒绝并返回 `400`。`contains_any` 需要一个字符串列表，而 `contains`、`not_contains` 和 `regex` 需要单个字符串。 value_type: type: string enum: - list - field - relative_date description: >- 可选的值解释方式。`list`：值为 List UUID，该列表中的条目将作为比对值。`field`：值为另一个字段路径，进行字段之间的比对。`relative_date`：值为相对日期对象，例如 {"direction": "past", "unit": "days", "amount": 30}。 score: type: number minimum: 0 maximum: 100 description: 当 operator 为 fuzzy_match 时必填：0-100 的相似度阈值。 group_index: type: integer description: >- 可选的分组逻辑。当任何条件带有 group_index 时，共享同一索引的条件将组成一个组，并由分组求值取代 evaluation_mode。 group_logic: type: string enum: - AND - OR default: AND description: 组内条件的组合方式。 groups_logic: type: string enum: - AND - OR default: OR description: 跨组的组结果组合方式。从第一个条件读取。 description: 条件仅读取正在被评估的交易，绝不筛选聚合窗口。 TransactionRuleAggregation: type: object required: - value properties: metric: type: string enum: - count - sum - max - min - avg - distinct_count default: count description: 匹配的历史交易的聚合方式。unique_count 可作为 distinct_count 的别名接受。 field: type: string default: amount description: 按 sum/max/min/avg/distinct_count 聚合的字段。对于 count 则忽略。 operator: type: string enum: - eq - ne - gt - gte - lt - lte default: eq description: 应用于计算指标的比对条件。 value: type: number description: 与计算出的指标进行比对的阈值。 window: type: string pattern: ^\d+(m|h|d)$ default: 1d description: >- 截至交易 txn_date 的回溯窗口：m（分钟，非月份）、h（小时）或 d（天），例如 30m、24h、7d、30d。 filters: type: object additionalProperties: true description: >- 限制聚合的历史交易范围。键是来自条件字段目录的字段路径；值为 "__current__" 表示解析为正在评估的交易上相同字段的值（例如 {"subject_vendor_data": "__current__"} 将时间窗口限定为同一主体），列表值表示成员关系。没有分组值的记录绝不会被分组在一起：当正在评估的交易没有 "__current__" 字段的值（无交易对手、无设备指纹）时，无论其运算符是什么，聚合都不会匹配。过滤器仅通过相等性或成员关系进行比较：没有 lt/gte 过滤器，因此无法在此处表达诸如“10,000 以下的历史交易”之类的范围。请改为在指标上设置范围（运算符为 lt 的 metric max 会将时间窗口内的每笔交易保持在阈值以下）。 description: >- 在时间窗口内对应用的历次交易执行频次检查。无论 evaluation_mode 为何，每个聚合条目都必须匹配，该规则才算匹配。聚合仅约束时间窗口；被评估的交易受范围和条件约束，因此当规则要求时，需在两部分上重复 direction、currency 或 transaction_type。 TransactionRuleScope: type: object properties: transaction_types: type: array items: type: string description: 限制交易类型，例如 finance、kyc、travel_rule、user_event。为空或缺失 = 无限制。 directions: type: array items: type: string enum: - INBOUND - OUTBOUND description: 限制交易方向（写入时不区分大小写）。 action_types: type: array items: type: string description: 限制为您定义的 action_type 值，例如 withdrawal、deposit。 description: 该规则适用于哪些交易。仅接受这三个键。 securitySchemes: ApiKeyAuth: type: apiKey in: header name: x-api-key description: >- 您的应用 API 密钥，可在 Business Console 的“开发者 -> API 密钥”中获取。主密钥拥有完整访问权限。指定名称的密钥可设置作用域：针对每个资源设为无权限、只读或读写，限定于特定工作流或已通过的会话、限定于 IP 地址列表，以及设置到期日期。401 表示密钥错误、已撤销或已过期；403 表示未发送密钥、密钥无权访问该资源或操作，或请求来自其 IP 列表之外的地址；在会话路由上返回 404 表示该会话不在该密钥允许的工作流或状态范围内。没有媒体访问权限的密钥获取到的图片、视频和 PDF URL 将为 null；没有会话写入权限的密钥获取到的会话链接和 token 将为 null。请参阅 https://docs.didit.me/console/api-keys。 ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.