Identity fraud remains a significant challenge in digital onboarding. With cybercrime rising worldwide, financial institutions must both reduce fraud at the point of entry and deal with the financial impact when some cases still make it through.
Identity checks, MFA, AI decisioning, and behavioral analytics all help lower risk — but none of these tools can address the financial losses that occur when identity fraud slips through.
This is where Instnt changes what’s possible.
Why Strong Identity Checks Matter
Identity verification sits at the core of secure onboarding. ID scans, biometric checks, and database validation help stop false, stolen, and synthetic identities, but some fraud still gets through.
At the same time, onboarding must remain simple. As friction increases, completion rates tend to fall. The challenge is balancing security with experience. Without sacrificing growth.
Instnt supports both goals: stronger identity assurance and insured outcomes for the customers Instnt approves.
AI That Strengthens Identity Risk Decisions
AI brings identity and behavioral signals into a single view, which helps teams recognize synthetic identities, conflicting data, and activity that does not reflect normal customer behavior. Decisioning becomes more consistent, fewer legitimate customers are slowed down, and controls can be adjusted as fraud techniques change.
But here’s the reality:
While AI can reduce fraud. It does not remove fraud losses.
That’s why Instnt built a different model.
Instnt uses explainable AI to make identity decisions, and when Instnt approves a customer, identity fraud losses tied to that onboarding decision are insured. This gives institutions something AI alone cannot: predictable financial outcomes.
Behavioral Analytics and Onboarding Safety
Behavioral signals — how users type, move, or complete a form — help distinguish real people from bots and fraud actors. These techniques reduce onboarding risk and make automated decisions smoother. They also help institutions keep real customers in the flow instead of getting stuck in manual review queues.
Instnt works alongside these tools, adding the missing layer institutions have never had: if identity fraud gets through, the financial loss is not yours.
Why Traditional Fraud Programs Are Not Enough
Even with strong identity checks, MFA, analytics, and device intelligence, institutions still face fraud losses. Identity fraud continues to rise; fraudsters continue to adapt.
Traditional programs can:
- Reduce identity fraud
- Detect some risky behavior
- Add friction for suspicious users
- Lower, but not eliminate, fraud exposure
What they can’t do is remove the financial burden from the institution.
Instnt is the first to make that possible.
Adding Identity Fraud Loss Insurance: The Instnt Model
Even with the best detection tools, some fraud gets through. Instnt fills that final gap by transferring the financial impact of identity fraud to A-rated insurers.
When identity fraud occurs on a customer approved by Instnt, the loss is reimbursed quickly through a simple one-click claim. This removes volatility, stabilizes financial performance, and frees capital that would otherwise be held in reserve.
Key benefits:
- Turn unpredictable identity fraud losses into a predictable insured cost
- Protect capital ratios and reduce reserve requirements
- Safely increase approval rates without taking on additional fraud exposure
- Improve customer experience by reducing friction and unnecessary declines
Instnt offers up to $100 million in annual coverage, giving institutions the confidence to scale without absorbing identity-based fraud losses.
Performance-Based Premiums
Instnt’s pricing reflects real identity risk. Institutions with stronger onboarding performance and lower fraud rates benefit from lower premiums. As identity risk changes, pricing adjusts — ensuring firms always pay a fair rate tied to actual exposure.
Compliance and Trust in Digital Onboarding
Instnt supports compliance by ensuring institutions have clear, audit-ready identity decisions tied to approved users. With explainable AI and documented onboarding outcomes, institutions gain:
- Clear evidence of identity checks
- Transparent decision logic
- A defensible risk framework
- A consistent and documented approval process
This approach supports compliance across onboarding and identity verification while avoiding added strain on operational teams.
Balancing Security and User Experience
Digital onboarding requires managing fraud risk without disrupting legitimate customers. At the same time, sign-up experiences are expected to be fast while still protecting identities and accounts.
Heavy security slows customers down.
Weak security increases fraud losses.
Instnt solves both problems:
- AI-driven identity decisions keep onboarding fast
- Insured identity fraud losses protect financial performance
- Better approvals and fewer false declines improve customer trust
Institutions using layered security plus Instnt can grow safely and deliver an experience that meets customer expectations.
FAQs
How does AI help prevent fraud during digital onboarding?
AI supports fraud prevention during digital onboarding by monitoring activity in real time and identifying behavior that does not align with typical customer patterns. Its ability to process large amounts of data makes it easier to detect risks such as fabricated accounts or early indicators of account takeover.
As fraud tactics change, the models adjust accordingly. This allows organizations to address new risks while limiting friction for legitimate users, strengthening security without slowing the onboarding experience.
What makes Instnt different from traditional fraud detection tools?
Traditional fraud tools are designed to catch bad activity, but they stop short once fraud slips through. When that happens, institutions are still left to absorb the loss. Instnt takes a different approach by pairing identity risk decisioning with insurance-backed reimbursement, giving institutions a way to shift approved-customer identity fraud losses off their balance sheets.
How does Instnt fit into my existing onboarding process?
Instnt plugs directly into your current onboarding flow. Our AI evaluates identity risk in real time, and when we approve a customer, identity fraud losses tied to that approval are insured. You don’t need to replace your existing tools — Instnt becomes an insured decision layer on top of what you already have.
