Identity Verification in E-Signing: Email OTP, KBA, IDV, eKYC, and Risk-Based Authentication

Identity verification is the foundation of trustworthy e-signatures. It is not enough that someone clicks “Sign” – you need to be able to show who signed, under which identity, and with what level of assurance. Modern e-sign and CLM platforms, especially AI-native ones like Legitt AI (www.legittai.com), combine multiple verification methods – Email OTP, KBA, IDV, eKYC, and risk-based authentication – to match the assurance level to the risk of each transaction.

This article explains each of these methods, when to use them, how they work together, and how enterprises and SMBs can design a sensible, scalable identity strategy for e-signing.

1. Why Identity Verification Matters in E-Signing

Legally, an electronic signature is mostly about intent and association—did the signer intend to sign, and is the signature clearly attached to the document? In practice, especially at scale, you also need strong evidence that the right person signed and the document was not tampered with.

Identity verification underpins:

• Legal defensibility – can you prove who signed if the contract is later disputed?
• Fraud prevention – are you protecting against impersonation or unauthorized signing?
• Regulatory compliance – are you meeting sector-specific requirements (finance, healthcare, public sector, etc.)?
• Internal governance – can you show that approvals and signatures followed policy?

Different contracts need different levels of assurance. A low-value NDA does not require the same rigor as a regulated financial agreement or a high-value M&A contract. A mature e-sign strategy therefore uses a toolbox of identity methods and a policy to decide which combination to apply in each scenario.

2. The Building Blocks of Identity Assurance

Before diving into specific methods, it helps to frame identity verification around three classic factors and two contextual dimensions.

2.1 Identity factors

1. Something the user knows
   • Passwords, security questions, Knowledge-Based Authentication (KBA).
2. Something the user has
   • Email inbox, phone/SIM, hardware token, authenticator app, smartcard.
3. Something the user is
   • Biometric traits (face, fingerprint), often used in IDV flows.

2.2 Contextual signals

4. Device and network context
   • IP address, device fingerprint, geolocation, network anomalies.
5. Behavioral patterns
   • Typical login times, mouse and typing patterns, transaction history.

Email OTP, KBA, IDV, and eKYC all plug into this model in different ways. Risk-based authentication then uses these signals to decide how much friction to apply for each signing event.

3. Email Verification and Email OTP

Email-based verification is the most common starting point for e-sign workflows. It provides basic assurance with low friction, suitable for many business documents.

3.1 How Email OTP works

Typical flow:

1. The sender defines the signer’s email address.
2. The e-sign platform sends a unique, time-bound link or One-Time Password (OTP) to that address.
3. The signer clicks the link or enters the OTP, proving they can access that inbox.
4. Only then are they allowed to view and sign the document.

The system logs:

• The email address used.
• That a one-time token was sent and validated.
• The IP, timestamp, and device used for access.

3.2 Strengths and limitations

Strengths:

• Very low friction—no special setup required.
• Works across geographies and user types.
• Adequate for low to moderate-risk documents where the email address itself is a meaningful identifier.

Limitations:

• Assumes the email account is controlled by the intended person (not always true).
• Offers limited assurance in high-risk or regulated contexts.
• Does not bind to a government-issued identity or verified customer profile.

In an AI-native platform like Legitt AI (www.legittai.com), Email OTP is often the “baseline” method, which can be combined with stronger controls when risk or policy demands it.

4. Knowledge-Based Authentication (KBA)

KBA attempts to verify identity using answers to questions only the genuine user should know. It is widely used in legacy systems, especially in consumer financial services, but its role is evolving as security standards rise.

4.1 Types of KBA

1. Static KBA
   • Fixed questions (mother’s maiden name, first school, etc.).
   • Often weak because answers can be guessed or discovered from social media.
2. Dynamic KBA
   • Real-time questions derived from public records or credit data (“Which of these addresses have you lived at?”).
   • Harder to guess but raises privacy and UX concerns.

4.2 Pros and cons

Pros:

• Does not require special devices or apps.
• Can add an extra layer on top of email/OTP in some flows.

Cons:

• Knowledge can be stolen or socially engineered.
• Static questions are increasingly seen as weak.
• Dynamic KBA depends on data sources that may not be available globally and can feel intrusive.

Today, many organizations are moving away from KBA as a primary control and instead combining possession-based methods (OTP, IDV) and risk-based checks for stronger assurance with better user experience.

5. Document-Based ID Verification (IDV)

IDV involves verifying a person’s identity using official identity documents and, often, biometric checks. It is much stronger than simple email OTP or KBA and is appropriate where the risk or regulatory requirements are higher.

5.1 How document-based IDV works

A typical IDV flow embedded in an e-sign journey:

1. The signer is asked to scan or upload an ID document (passport, national ID, driver’s license).
2. The system extracts data using OCR and checks security features, document format, and tamper signals.
3. The signer is prompted to take a selfie or short video for liveness and face match.
4. The platform compares the selfie with the document photo to verify that the document belongs to the person present.
5. The result (pass/fail, confidence score, extracted identity data) is returned and linked to the signing session.

5.2 When to use IDV

IDV makes sense when:

• You need to anchor the signature to an official, government-recognized identity.
• Regulations expect stronger “Know Your Customer” procedures.
• The transaction value or risk is high (e.g., financial, real estate, regulated services).

In a CLM context, IDV can be required only for particular contract types or roles, rather than across every signature, to balance assurance and user experience.

6. eKYC: Digital Customer Onboarding and Reuse of Identity

eKYC (electronic Know Your Customer) goes beyond one-time IDV and establishes an ongoing, verified identity profile that can be reused across multiple transactions.

6.1 What eKYC does

An eKYC process typically:

• Performs IDV (document + face + liveness).
• Collects additional attributes (date of birth, address, tax ID, etc.).
• Runs screening or eligibility checks (for example, sanctions, credit checks, residency).
• Stores a verified identity record in a secure system.

Once established, this eKYC profile can be referenced by future e-sign workflows:

• “This signer is already eKYC-verified within our bank / fintech / platform.”
• “We trust this identity to a higher level; only a simple OTP is needed per transaction.”

6.2 eKYC and e-signatures

For organizations that already have KYC (banks, insurers, fintechs, large platforms):

• E-sign events can be tied to the existing verified customer identity instead of re-verifying ID from scratch.
• Risk-based rules can decide when fresh verification is required (for example, after a long period of inactivity or for high-risk transactions).

Legitt AI (www.legittai.com) can integrate with eKYC providers or internal KYC systems so that the same verified identity underpins both customer onboarding and contract execution.

7. Risk-Based Authentication: Matching Assurance to Risk

Risk-based authentication (RBA) is the glue that ties all these methods together. Instead of using the same level of friction for every document, RBA dynamically chooses controls based on risk.

7.1 Inputs to risk scoring

A risk engine can consider:

• Contract context
  • Type (NDA vs credit agreement vs DPA).
  • Value and financial exposure.
  • Jurisdiction and governing law.
• User context
  • Existing eKYC status or prior verification.
  • Role (internal employee vs external customer vs vendor).
• Behavior and environment
  • Device, IP, location anomalies.
  • Unusual signing times or patterns.

7.2 Outputs: stepped-up or stepped-down auth

Based on a risk score, the system can choose:

• Low risk – email OTP alone; minimal friction.
• Medium risk – email OTP + additional factor (SMS OTP, SSO, or simple KBA).
• High risk – full document-based IDV or requiring a pre-verified eKYC profile.

An AI-native platform like Legitt AI (www.legittai.com) uses contract metadata and identity signals to drive these decisions automatically, so users do not have to manually select the right verification level each time.

8. Designing an Identity Verification Policy for E-Signing

A robust identity strategy is policy-driven, not ad hoc. The goal is to codify which methods are required for which scenarios.

8.1 Segment contracts into risk tiers

A practical approach:

• Tier 1 – Low-risk
  • Routine NDAs, internal HR forms, small-value orders.
  • Controls: email OTP, audit trail, device logging.
• Tier 2 – Medium-risk
  • Standard commercial contracts, vendor agreements, SLAs.
  • Controls: email OTP + SSO or SMS OTP; optional KBA; tighter monitoring.
• Tier 3 – High-risk / regulated
  • Financial, regulated, public-sector, or very high-value agreements.
  • Controls: document-based IDV or eKYC; possibly digital signatures with qualified certificates.

8.2 Policy examples

• “All contracts above $X or in Region Y require IDV before signing.”
• “All customer-facing agreements in regulated markets must be tied to a verified eKYC profile.”
• “Internal approvals use SSO, external signatures use Email OTP, and high-risk roles use step-up IDV.”

Once defined, these policies should be implemented in the platform rules so they are enforced automatically and consistently.

9. Implementing Identity Controls in an AI-Native CLM Stack

Identity verification should not be an isolated step; it should be embedded in the full contract lifecycle.

9.1 Identity across the lifecycle

• Drafting – user identity determines which templates and clause libraries can be accessed.
• Approval – internal approvers authenticate via SSO/MFA; each decision is tied to their identity.
• Signing – external signers go through Email OTP, IDV, or eKYC-based flows according to policy.
• Storage and audit – all identity events are captured in the audit trail and evidence package.

9.2 Integrations and orchestration

With a platform like Legitt AI (www.legittai.com):

• Identity providers (SSO/IdP), OTP gateways, IDV/eKYC vendors, and risk engines are integrated behind one interface.
• Contract metadata (value, type, jurisdiction) and identity data are evaluated together.
• The system builds consistent, defensible evidence for each transaction without forcing users to manage identity steps manually.

This is what differentiates an AI-native CLM stack from a simple e-sign point solution.

10. Governance, Privacy, and User Experience

Stronger identity verification brings more data and more friction. Enterprises must balance security, privacy, and usability.

10.1 Governance and privacy

• Define who can configure identity policies and thresholds.
• Limit access to sensitive identity data (ID document images, biometrics) to necessary roles.
• Ensure compliance with data protection laws for storage and retention of identity data.
• Use clear consent flows so signers understand what is being collected and why.

10.2 User experience

• Avoid using high-friction methods (like full IDV) for low-risk documents.
• Keep flows as simple as possible – short steps, clear instructions, mobile-friendly.
• Reuse verified identities where allowable (eKYC profiles) instead of re-verifying every time.

A well-designed, risk-based approach lets most users experience a lightweight flow while still protecting the organization where it matters most.

Read our complete guide on Contract Lifecycle Management.