Scienaptic Systems Inc.

50 West, 47th Street, 16th Floor, Ste 1614, New York, NY 10036

Ph: +1 212 244 4030

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Sharper credit decisioning process to accelerate profitable portfolio growth

Case Study

Our client, a leading financial institution was experiencing increased delinquencies, resulting in credit losses and high operational costs on collections.

Detect Account Takeover Fraud Using AI

Case Study

One of our major banking clients in the US was seeing significant uptick in ATO (Account Take Over) fraud losses. There was a need for a platform which could help them detect fraud early and accurately...

The role of AI in Credit Line Assignment


Key driver of approve or reject decision is the credit worthiness of the applicant as
measured by risk score(s).

Forecast better, faster, at scale with advanced ML techniques

Case Study

A leading US bank was unable to accurately forecast aging losses due to underestimation of realizations, observing over 16% variance to actuals. 

Sharper AI tools for improved loss savings and approvals

Case Study

A case study on how Ether platform creates significant “Lift”

A practitioner’s
note on forecasting Retail Credit Losses


Accurate and reliable forecasting of the Credit Losses has always been a subject of critical focus in Retail portfolio Risk management- in literature and bank’s practices alike. 

How we are driving a robust credit program for a leading e-retailer

Case Study

The overall opportunity of this engagement lay in our ability to rebuild and enable the client to drive credit adoption and a sound decisioning process...

Using AI & ML to detect first party fraud


First party fraud occurs when customers apply for credit with an explicit intention
to not pay back. Such customers often use fabricated information (including
contact details) at the time of application.

ML in Credit Risk 

Best Practices

This explores the best practices which are followed while we build and deliver some of the world’s leading underwriting models on our platform Ether.