Decline too many applicants and you're leaving profitable loans on the table. Accept the wrong ones and bad debt erodes your margins.
The harder truth is that line isn't fixed. Your risk appetite shifts. Your applicants' circumstances change.
What looks like the wrong risk today may be exactly the right one tomorrow, and your underwriting needs to keep up.
The harder truth is that line isn't fixed. Your risk appetite shifts. Your applicants' circumstances change.
What looks like the wrong risk today may be exactly the right one tomorrow, and your underwriting needs to keep up.
Go Beyond the Score.
See Their Cashflow Fingerprint™
A credit score is a number. A Cashflow Fingerprint™ is an identity.
Every borrower has a unique financial behavior - the rhythm of their income, the weight of their obligations, the patterns in how they spend and save. No two are the same.
Our AI-powered platform reads a borrower's complete bank statement history and maps that behaviour into a picture that tells you exactly who you're lending to.
Every borrower has a unique financial behavior - the rhythm of their income, the weight of their obligations, the patterns in how they spend and save. No two are the same.
Our AI-powered platform reads a borrower's complete bank statement history and maps that behaviour into a picture that tells you exactly who you're lending to.
01 / Fetch
02 / Classify
03 / Score
04 / Recommend
Have unique needs? Contact us for a custom Enterprise solution
Oren Abiri
CEO
Alex Vysotzky
COO
Sean S. Gonen
CBDO
Brian Y Gonen
Head of Sales
Igor Baklytskyi
CPO
Mykhailo Stadnyk
CTO
Different lenders use CreditSense for different reasons.
Performance Optimization
16%
A small lender (~$1.5M portfolio) started with a 29% first payment default rate. Within 90 days it dropped to 19%. After six months it stabilized at 16%.
$1.32
A medium lender (~$6M portfolio) used the LTV model instead. Conversion increased by 5 percentage points. ROI per dollar lent moved from $1.16 to $1.32.
Manual Work Reduction
A large lender with 150 call center agents was reviewing bank statements manually. Average processing time per client: 15.8 minutes.
Operational Standardization
A storefront lender with 20+ locations across 3 states could not get consistent performance across shops. The top 3 stores outperformed the average by nearly 70%. After 90 days on CreditSense, that gap shrank to 37.1%. The lender could finally identify what worked, replicate it, and track improvement across the entire network.
gap shrank to 0,1 %
Automation
A medium lender processing ~15,000 applications per month was handling everything manually.
Within 60 days, 18.3% of traffic was automated — the clear approvals and clear declines that did not require human review. Over time, automation reached 51.7% of all traffic with no drop in decision quality.
Within 60 days, 18.3% of traffic was automated — the clear approvals and clear declines that did not require human review. Over time, automation reached 51.7% of all traffic with no drop in decision quality.
With CreditSense, we're not just declining fewer good applicants — we're finding profitable borrowers our old model would have missed entirely.
Name Here
CEO
With CreditSense, we're not just declining fewer good applicants — we're finding profitable borrowers our old model would have missed entirely.
Name Here
CEO
With CreditSense, we're not just declining fewer good applicants — we're finding profitable borrowers our old model would have missed entirely.
Name Here
CEO
See how our Predictive Cashflow Score Engine™ helps lenders approve more good loans, reduce defaults, and make every decision count. Schedule a no-obligation demo with one of our strategists today.
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