免费
免费
每月 $0。无需信用卡。
- 免费 KYC 套件（身份验证 + 被动活体检测 + 人脸匹配 + 设备与 IP 分析）, 每月 500 次，永久有效
- 黑名单用户
- 重复检测
- 每次会话 200+ 欺诈信号
- Didit 网络中可重复使用的 KYC
- 案件管理平台
- 工作流构建器
- 公开文档、沙盒、SDK、MCP（模型上下文协议）服务器
- 社区支持
全球2,000多家组织信赖。
不该支付的，却支付了
幽灵索赔人。模板化报告。深度伪造视频证据。
据反保险欺诈联盟估计，美国保险公司每年损失约3080亿美元。其中大部分是由于理赔时未对索赔人进行身份核查，也未对证据进行鉴定。Didit通过一个工作流程弥补了这两个漏洞, 每笔理赔0.53美元，每月免费500笔。
工作原理
从注册到验证用户，仅需四步。
- 步骤 01
创建工作流程
选择您需要的检查项, 身份、活体、人脸匹配、制裁、地址、年龄、电话、电子邮件、自定义问题。在仪表盘中将它们拖入流程，或通过我们的API发布相同的流程。根据条件进行分支，运行A/B测试，无需代码。
- 步骤 02
集成
通过我们的Web、iOS、Android、React Native或Flutter SDK进行原生嵌入。重定向到托管页面。或者直接通过电子邮件、短信、WhatsApp等任何方式向您的用户发送链接。选择适合您技术栈的方式。
- 步骤 03
用户完成流程
Didit负责托管摄像头、灯光提示、移动设备切换和无障碍功能。当用户在流程中时，我们实时评估200多个欺诈信号，并根据权威数据源验证每个字段。两秒内即可出结果。
- 步骤 04
接收结果
实时签名webhook确保用户获批、拒绝或送审时，您的数据库即时同步。按需轮询API。或者打开控制台检查每个会话、每个信号，并按您的方式管理案例。
01 · 理赔类型
欺诈团队每天都会遇到的模式。
机动车虚假损失理赔，损失发生在保单生效前。幽灵理赔，索赔人并非保单持有人。深度伪造视频证据。重复使用模板的警方报告，字段经过编辑。虚报业务中断（BI）发票。有组织的伤害团伙在不同保险公司提交相同损失。相同的工作流程构建器可识别所有变体。
工作流程编排模块Didit · Claim shapes
The patterns a fraud team sees daily.
- Motor · staged lossDamage predates the policy
- Ghost claimClaimant ≠ policyholder
- Deepfake video evidenceGenerated injury / location
- Template police reportSame PDF, edited fields
- BI inflationEdited invoices
- Organised injury ringSame human, many claims
Surface every pattern at first notice of loss.
02 · 索赔人KYC
索赔人即保单持有人。
一次`/v3/session/`调用即可完成身份验证（0.15美元）、被动活体检测（0.10美元）以及与保单持有人存档照片进行1:1人脸匹配（0.05美元）。捆绑价格为0.33美元。通过iBeta Level 1 PAD认证，入门级安卓设备上两秒内出结果。可捕获所有索赔人非保单持有人的幽灵理赔尝试。
用户验证模块Didit · Claimant verification
The claimant is the policyholder.
Claim · 4 / 5
Match against policy
- ID Verification$0.15
- Passive Liveness$0.10
- Face Match 1:1 vs policy$0.05
- AML Screening$0.20
- Document OCR—
iBeta Level 1 PAD · sub-2-second$0.33 bundle
03 · 文件鉴定
篡改、模板、元数据。全部检查。
文档光学字符识别（OCR）从支持证据中提取所有字段, 警方报告、维修报价、医疗发票、损失照片。像素级篡改检测标记编辑区域，模板匹配捕获重复使用的PDF骨架，EXIF元数据检查捕获与损失事件不符的日期。高篡改分数=自动转为“待审核”。
身份验证模块Didit · Document OCR + tamper
Tamper. Template. Metadata. All checked.
SignalSampleVerdict
- Edited region · pixel-levelAmount fieldBlock
- Reused template skeleton3 prior claimsBlock
- EXIF date mismatchPhoto · 2024-09Review
- Font swap detectedTimes / ArialReview
- Clean original—Pass
Field-level OCR plus pixel-level tamper score.
04 · 深度伪造防御
深度伪造无法通过被动活体检测。
通过iBeta Level 1演示攻击检测（PAD）认证，符合ISO/IEC 30107-3完整目录。可阻止AI生成的保单持有人深度伪造、硅胶或乳胶面具、先前自拍的屏幕回放以及打印照片。随着新攻击向量的出现，该模型每年都会在iBeta进行重新测试。
活体检测模块Didit · Passive Liveness · iBeta L1 PAD
Deepfakes don't pass Passive Liveness.
Attack vectorScoreVerdict
- AI deepfake of policyholder95Block
- Silicone mask of policyholder91Block
- Screen replay of prior selfie88Block
- Printed photo · driving licence86Block
- Real claimant · present6Pass
Re-tested at iBeta every year as new attacks appear.
05 · 制裁 + 交叉理赔搜索
制裁命中 + 有组织团伙检测。
AML筛查（每次检查0.20美元）针对14种语言的1300多个制裁、政治公众人物（PEP）和负面媒体名单对每个索赔人进行检查，每日更新。人脸搜索1:N（每次搜索免费）将索赔人的自拍与您之前的索赔人图库进行比较, 有组织的伤害团伙会以高相似度匹配集群的形式在整个投资组合中浮现。
AML筛查模块Didit · AML + Face Search
Sanctions check + prior-claim face search.
AML screening
- OFAC SDN listNo hit
- EU consolidatedNo hit
- PEP databaseReview
- Adverse mediaPass
Face Search · prior claimants
- claim-7710 · motor0.94
- claim-6128 · health0.92
- claim-5404 · travel0.88
- Cluster of 3
AML $0.20 · Face Search free per searchCross-portfolio
06 · Webhook决策 + 审计包
签名判决。模块化信号。审计包。
一个签名的webhook会返回“已批准”、“待审核”或“已拒绝”状态，以及每个模块的信号, 人脸相似度、AML命中列表、人脸搜索匹配列表。使用基于哈希的消息认证码（HMAC）SHA-256验证X-Signature-V2。决策有效载荷即为审计包, 随时通过GET /v3/session/[id]/decision/获取完整版本。
Webhook 参考Didit · Webhook · X-Signature-V2
Verdict + per-module signals + audit pack.
POST /webhooks/didit
{
"session_id": "claim-8821",
"vendor_data": "claim-8821",
"status": "In Review",
"face": { "similarity_score": 0.42 },
"aml": { "status": "In Review",
"hits": [{ "list": "PEP" }] },
"face_search": { "matches": [
{ "session_id": "claim-7710",
"similarity": 0.94 }
] }
}- Approvedrelease the payout queue
- In reviewroute to Special Investigations Unit
- Declineddecline + open file · SIU alert
Verify the signature BEFORE reading the body.
集成
一次会话。一份签名裁决。五个欺诈信号。
针对捆绑工作流程开启理赔会话。读取签名裁决。每个模块的信号+匹配列表都在有效载荷中。
POST /v3/session/索赔
$ curl -X POST https://verification.didit.me/v3/session/ \
-H "x-api-key: $DIDIT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"workflow_id": "wf_claim_verify",
"vendor_data": "claim-8821",
"metadata": { "policy_id": "POL-44120" }
}'201已创建{ "session_url": "verify.didit.me/..." }
在 webhook 返回
status: Approved 之前，暂停支付。文档 →POST /webhooks/didit判决
// X-Signature-V2 verified upstream
if (payload.status === "Approved") {
releasePayout(payload.vendor_data);
} else if (payload.status === "In Review") {
routeToSiu(payload.face_search.matches);
}200OK状态：已批准 · 已拒绝 · 审核中 · 未完成
读取 payload 前，验证
X-Signature-V2。文档 →代理就绪集成
一键部署索赔欺诈防御。
粘贴到 Claude Code、Cursor、Codex、Devin、Aider 或 Replit Agent 中。填写您的技术栈。Agent 将连接工作流，启动会话，读取每个模块的信号，并将“审核中”的索赔路由到您的特别调查部门。
didit-integration-prompt.md
You are integrating Didit into an insurance carrier's claim workflow at first notice of loss (motor, health, property, travel, business interruption). Goal: catch ghost claims, deepfake video evidence, forged supporting documents, sanctions hits on the claimant, and organised-injury rings before the payout enters the queue. One API call. One signed webhook. Five fraud signals.
WHY THIS SHAPE
- The Coalition Against Insurance Fraud estimates fraud costs the US industry around $308 billion / year (2022 figures). Most of that walks in through claims with no identity check on the claimant and no document forensics on the evidence.
- Five signals settle the question on most claims: (1) the claimant is the policyholder, (2) the claimant is alive and present (not a deepfake), (3) the supporting documents are not tampered or templated, (4) the claimant is not on a sanctions list, (5) the claimant has not already filed N near-identical claims across your portfolio.
- One Didit /v3/session/ call bundles all five. $0.33 KYC + $0.20 AML = $0.53 per claim. Face Search 1:N is free per search. 500 verifications free every month.
PRE-REQUISITES
- Production API key from https://business.didit.me (sandbox key in 60 seconds, no credit card).
- A webhook endpoint with HMAC SHA-256 verification of the X-Signature-V2 header using your webhook secret.
- A Workflow Builder workflow bundling ID Verification + Passive Liveness + Face Match 1:1 (with the policyholder portrait as comparison target) + AML Screening + Face Search 1:N (gallery scoped to prior claimants on your account).
- Reference to the policy ID and policyholder portrait on file from your Policy Administration System (PAS) — passed as metadata on the session.
STEP 1 — Open the claim-verification session
POST https://verification.didit.me/v3/session/
Headers:
x-api-key: <your api key>
Content-Type: application/json
Body:
{
"workflow_id": "<wf id bundling ID + Liveness + Face Match + AML + Face Search 1:N>",
"vendor_data": "<your claim id, max 256 chars>",
"callback": "https://<your-app>/claims/verify/callback",
"metadata": {
"policy_id": "<your policy id>",
"line_of_business": "motor",
"loss_date": "2026-04-12"
}
}
Response: 201 Created with a hosted session URL. Send it to the claimant by email / Short Message Service (SMS) / inside the claims app. The claim stays in HOLD on your side until the signed webhook lands.
STEP 2 — Read the signed webhook
Didit POSTs the verdict. Verify X-Signature-V2 (HMAC SHA-256 of the raw body) BEFORE reading the JSON.
Payload (excerpted):
{
"session_id": "<uuid>",
"vendor_data": "<your claim id>",
"status": "In Review",
"id_verification": { "status": "Approved" },
"liveness": { "status": "Approved" },
"face": { "status": "Approved", "similarity_score": 0.92 },
"aml": { "status": "In Review", "hits": [{ "list": "PEP" }] },
"face_search": {
"matches": [
{ "session_id": "claim-7710", "similarity": 0.94, "vendor_data": "claim-7710" }
]
}
}
Session status enum (exact case, Title Case With Spaces): Approved | Declined | In Review | Resubmitted | Expired | Not Finished | Kyc Expired | Abandoned.
STEP 3 — Branch on the verdict
Approved → release the claim into the standard payout queue.
In Review → route to the Special Investigations Unit (SIU) with the per-module signals + face-search match list as the case file.
Declined → decline + open file. Block the payout. The decision payload is the audit pack.
Not Finished → resend the session link.
STEP 4 — Document forensics on supporting evidence (separate sub-flow)
For each supporting PDF / image uploaded (police report, repair quote, medical invoice, photo of loss), run Didit Document Optical Character Recognition (OCR). The OCR response surfaces:
- Field-level extracted text (claim amount, names, dates)
- Tamper score per region (pixel-level edits)
- Template match against prior submissions (reused PDF skeleton)
- EXIF / metadata mismatch (date in photo vs date of loss)
A high tamper score or a template match against a prior claim flips the case status to In Review.
STEP 5 — Pull the full decision for the case file
GET https://verification.didit.me/v3/session/{session_id}/decision/
Headers:
x-api-key: <your api key>
Returns the full decision payload — per-module signals, raw face-similarity scores, AML hit list with source list per match, face-search candidate list with scores. Use this as the audit pack for any dispute.
WEBHOOK EVENT NAMES
- Sessions: standard session webhook. One endpoint, status field tells you the lifecycle.
- Verify X-Signature-V2 (HMAC SHA-256) on every payload.
CONSTRAINTS
- Session statuses use Title Case With Spaces. Never UPPER_SNAKE_CASE — that's the Transactions API.
- The Face Match comparison target is the policyholder portrait from your Policy Administration System (PAS). A deepfake of the policyholder cannot pass when Passive Liveness is also in the workflow.
- Face Search 1:N gallery is scoped to YOUR account — Didit does not search across carriers. To collaborate across an industry pool, use a shared workflow_id pointing at a multi-carrier gallery you own.
- 200+ fraud signals are surfaced on every session at no extra cost — read them off the decision payload, don't re-query.
- Default retention is the standard 5-year insurance horizon; adjust per workflow if your jurisdiction differs.
Read the docs:
- https://docs.didit.me/sessions-api/create-session
- https://docs.didit.me/core-technology/face-match/overview
- https://docs.didit.me/core-technology/aml-screening/overview
- https://docs.didit.me/core-technology/face-search/overview
- https://docs.didit.me/integration/webhooks
Start free at https://business.didit.me — sandbox key in 60 seconds, 500 verifications free every month, no credit card.需要更多上下文？请参阅完整的模块文档。docs.didit.me →
合规性设计
一键开启新国家/地区业务。 我们为您解决难题。
我们负责设立当地子公司、获取许可证、进行渗透测试、获得认证，并与所有新法规保持一致。要在新国家/地区发布验证服务，只需轻点开关。已覆盖220多个国家/地区，每个季度进行审计和渗透测试, 是唯一一个被欧盟成员国政府正式认定比线下验证更安全的身份提供商。
阅读安全与合规性档案欧盟金融沙盒
Tesoro · SEPBLAC · BdE
ISO/IEC 27001
信息安全 · 2026
SOC 2 · Type I
AICPA · 2026
iBeta Level 1 PAD
NIST / NIAP · 2026
GDPR
EU 2016/679
DORA
EU 2022/2554
MiCA
EU 2023/1114
AMLD6 · eIDAS 2.0
原生符合欧盟标准
数据证明
数据证明
- $0.00每份完整筛选的索赔, $0.33 KYC 套餐 + $0.20 AML。人脸搜索每次免费。
- 0+制裁名单、政治公众人物 (PEP) 和负面媒体名单，每日更新。
- iBeta L1被动活体检测，可防范深度伪造、面具和回放攻击。每年重新测试。
- 0每个账户每月免费验证。
三个层级，一份价目表
免费开始。按使用量付费。可扩展至企业级。
每月 500 次免费验证，永久有效。生产环境按量付费。企业版提供定制合约、数据驻留和 SLA (Service Level Agreements)。
最受欢迎
按用量付费
按用量计费
按实际用量付费。25+模块。公开的模块定价，无每月最低费用。
- 完整KYC $0.33（身份+生物识别+IP/设备）
- 10,000+ AML数据集, 制裁、PEP、负面媒体
- 1,000+ 政府数据源用于数据库验证
- 交易监控 $0.02/笔交易
- 实时KYB $2.00/家企业
- 钱包筛选 $0.15/次检查
- 白标验证流程, 您的品牌，我们的基础设施
企业版
企业版
定制MSA和SLA。适用于大批量和受监管项目。
- 年度合同
- 定制MSA、DPA和SLA
- 专属Slack和WhatsApp频道
- 按需人工审核员
- 经销商和白标条款
- 独家功能和合作伙伴集成
- 指定CSM、安全审查、合规支持
免费开始 → 仅在检查运行时付费 → 解锁企业版以获取定制合约、SLA 或数据驻留。
FAQ
常见问题
What is Didit?
Didit is infrastructure for identity and fraud, the platform we wished existed when we were building products ourselves: open, flexible, and developer-friendly, so it works as a real part of your stack instead of a black box you integrate around.
One API covers verifying people (KYC, know your customer), verifying businesses (KYB, know your business), screening crypto wallets (KYT, know your transaction), and monitoring transactions in real time, on a stack built to be:
- Fast, sub-2-second p99 on every session
- Reliable, in production with 1,500+ companies across 220+ countries
- Secure, SOC 2 Type 1, ISO 27001, GDPR-native, and formally attested by Spain's financial regulator as safer than verifying someone in person
The footprint underneath: 14,000+ document types in 48+ languages, 1,000+ data sources, and 200+ fraud signals on every session. The Didit infrastructure dynamically learns from every session and gets better every day.
How big is insurance claim fraud?
The Coalition Against Insurance Fraud estimated US insurers lose around \$308.6 billion a year to fraud across all lines (2022 study). The European insurance body Insurance Europe reports similar share-of-premium loss across the EU.
Most of it is opportunistic, small inflated amounts on otherwise legitimate claims. A smaller share is professional rings filing the same loss across carriers. Both shapes share one weakness: nobody checks who the claimant is at first notice of loss.
What is a ghost claim?
A ghost claim is when the person filing the claim is not the policyholder. Typical pattern: an attacker buys leaked customer data from a breach, calls the carrier impersonating the policyholder, files a small loss claim, and asks for the payout to a new bank account.
The attack succeeds when there is no biometric check tying the caller to the person on the policy. Face Match 1:1 against the policyholder portrait closes this gap in two seconds.
How fast is the verification for my end user?
The full flow normally takes under 30 seconds end-to-end, pick up the ID, snap the document, snap the selfie, done. That is the fastest in the market. Legacy KYC providers usually take more than 90 seconds for the same flow.
On the back end, Didit returns the result in under two seconds at p99, measured from the moment the user finishes the selfie to the moment your webhook fires. Mobile capture is tuned for slow phones and slow networks: progressive image compression, lazy software development kit load, and a one-tap hand-off from desktop to phone via QR code if the user starts on web.
What does document forensics actually check?
On every supporting document the claimant uploads, police report, repair quote, medical invoice, photo of the loss, Didit runs:
- Field-level Optical Character Recognition (OCR), extracts amounts, names, dates, reference numbers
- Pixel-level tamper detection, flags edited regions (covered scratches, swapped totals)
- Template matching, catches reused PDF skeletons across prior claims
- EXIF / metadata check, flags photos whose timestamp doesn't match the loss date
A high tamper score or a template match flips the claim from Approved to In Review automatically.
What happens if a user fails, abandons, or expires?
Every session lands on one of seven clear statuses, so your code always knows what to do:
Approved, every check passed. Move the user forward.Declined, one or more checks failed. You can allow the user to resubmit the specific failed step (for example, re-take the selfie) without re-running the whole flow.In Review, flagged for compliance review. Open the case in the console, see every signal, decide approve or decline.In Progress, user is mid-flow.Not Started, link sent, user has not opened it yet. Send a reminder if it sits too long.Abandoned, user opened the link but did not finish in time. Re-engage or expire.Expired, the session link aged out. Create a new session.
A signed webhook fires on every status change, so your database always stays in sync. Abandoned and declined sessions are free.
Where does my customer data live and how is it protected?
Production data is processed and stored in the European Union by default, on Amazon Web Services. Enterprise contracts can request alternative regions for jurisdictions whose regulators require it.
Encryption everywhere. AES-256 at rest across every database, object store, and backup. Transport Layer Security 1.3 in transit on every API call, webhook, and Business Console session. Biometric data is encrypted under a separate Customer Master Key.
Retention is yours to control. Default retention is indefinite (unlimited) unless you configure shorter, between 30 days and 10 years per application, and you can delete any individual session at any time from the dashboard or the API.
Certifications: SOC 2 Type 1 (Type 2 audit in progress), ISO/IEC 27001:2022, iBeta Level 1 PAD, and a public attestation from Spain''s Tesoro / SEPBLAC / CNMV that Didit''s remote identity verification is safer than verifying someone in person. Full report at /security-compliance.
Is Didit compliant for my industry?
Didit ships compliant by default for the regulators that matter to identity infrastructure:
- GDPR + UK GDPR, controller / processor split, full Data Processing Agreement published, lead supervisory authority named (Spain''s AEPD).
- AMLD6 + EU AML Single Rulebook, 1,300+ sanctions, politically exposed person, and adverse-media lists screened in real time.
- eIDAS 2.0, EU Digital Identity Wallet aligned; reusable-identity ready.
- MiCA (Markets in Crypto-Assets), ready for crypto on-ramps, exchanges, and custodians.
- DORA, Digital Operational Resilience Act, EU financial-services operational resilience.
- BIPA, CUBI, Washington HB 1493, CCPA / CPRA, US biometric privacy (Illinois, Texas, Washington) and California consumer privacy.
- UK Online Safety Act, age-gating and child-safety obligations.
- FATF Travel Rule, originator and beneficiary data on crypto transfers, IVMS-101 interoperable.
Detailed memo, every certificate, every regulator letter: /security-compliance.
How fast can I integrate and start verifying users?
- 60 seconds to a sandbox account at business.didit.me, no credit card.
- 5 minutes to a working verification through Claude Code, Cursor, or any coding agent via our Model Context Protocol (MCP) server.
- A weekend to a production-ready integration with signed-webhook verification, retries, and a remediation flow when a user is declined.
Three integration paths, pick whichever fits your stack:
- Embed natively with our Web, iOS, Android, React Native, or Flutter SDK.
- Redirect the user to the hosted verification page, zero SDK.
- Send a link by email, SMS, WhatsApp, or any channel, zero front-end work.
Same dashboard, same billing, same pay-per-success price for all three. Step-by-step guide at docs.didit.me/integration/integration-prompt.
What does the recipe cost?
Per claim:
- User Verification bundle (ID + Liveness + Face Match): \$0.33
- AML Screening: \$0.20
- Face Search 1:N against prior claimants: \$0.00 (free per search)
- Document OCR on each supporting file: included in the User Verification price
Around \$0.53 per fully-screened claim. The first 500 verifications every month are free on every account, pilot the workflow inside the free tier.
No minimums, no annual commitment, no per-seat pricing.
How does it integrate with my Special Investigations Unit?
The signed webhook is the routing signal. On status: In Review, your back-end routes the case to the Special Investigations Unit (SIU) with the per-module signals + face-search match list as the opening case file.
Pull the full decision payload via GET /v3/session/[id]/decision/ for the analyst, face similarity scores, AML hit list with source list per match, face-search candidate list with scores, document forensics output. The decision payload is the audit trail for any dispute.
What about General Data Protection Regulation (GDPR) and Anti-Money-Laundering (AML) retention?
Biometric vectors are special-category data under the EU's General Data Protection Regulation (GDPR). The lawful basis is the standard claims-investigation legitimate interest plus the consent flow at session start.
Default retention is the standard 5-year insurance horizon, adjust per workflow if your jurisdiction or supervisor differs. The gallery for Face Search 1:N is scoped to your account by design, no cross-carrier search unless you join a consortium and run a shared workflow_id.