Hi all,

We're Matthew and Luc, two Stanford grads building Incandor (YC P26).

https://youtu.be/dWrp82VkDbA

TL;DR: Banks verify identity at account creation, but have no continuous signal for who's actually operating an account afterward. Incandor builds that layer – a behavioral identity per session, persistent across the accounts, devices, and credentials a fraudster cycles through.

The Problem

Banks have built layers of defense – KYC pipelines, device fingerprinting, transaction monitoring, rules engines built over decades. Fraud and money laundering are still a multi-hundred-billion dollar problem.

Every defense was built around identity, but identity has become a commodity:

• Attackers buy verified IDs in bulk, pass document checks, rotate devices, and stay under transaction thresholds by design
• A mule operator running 40 accounts under 40 different identities can look like 40 unrelated people to every system you have
• Coordinated rings move money across your platform sharing no transactions, no devices, no names – invisible to rules engines until it's too late

Banks have strong verification at account creation and strong monitoring of transactions, but no continuous, identity-level signal in between. Incandor is that layer.

The Solution

Incandor analyzes how people physically interact with their devices (taps, clicks, scrolls, etc.) and turns every session into a behavioral point. Every human creates a unique cluster. We then place all these points in a map to provide a population view of all users.

Incandor allows banks to reconcile the operators of accounts through their behavior alone. From this, we can identify the most common patterns among fraud rings:

• We can detect when the person operating an account changes mid-life, a tell-tale sign of a mule handoff, resale of accounts, account takeover, or other bespoke coordinated activity.
• Detecting when account changes hands isn’t enough, though – we can identify the operator behind that behavior and inspect their activity across the platform.
• We can see when someone is operating multiple accounts – very typical for coordinated fraud or money laundering.
• After a confirmed fraud case, banks can flag the operator so that if they attempt to return to the platform, we can block banned operators during onboarding or if they later take over another account.

We’ve designed this system so that banks can integrate the navigation of Incandor’s behavioral map into their own workflows which may also contain transaction linking and other linking signals.

Integration is simply a matter of deploying our SDK which sends us these behavioral telemetry signals. Once signals are in, our API for interacting with the map becomes live.

We collect only behavioral signals – not what users type, read, or view. Behavior alone enables operator-level reconciliation, and keeps user data private by design.

The Ask

We're onboarding early customers and would love intros to any of the following at commercial and consumer banks, fintechs, neobanks, or digital banks:

• Chief Risk Officers / Chief Compliance Officers
• Heads of Fraud / Financial Crime / AML
• Fraud engineers or investigators
• CEOs / CTOs at Series A-E fintechs

Reach out directly at matthew@incandor.com or luc@incandor.com :)