+40%
More approvals without raising risk
25%
Lower losses across the portfolio
80%
Fewer manual reviews
12x
More risk separation than scores alone
Built on data from financial institutions managing $3.9T
in assets
FourLeaf FCU
4Front Credit Union
Patriot FCU
Altura Credit Union
Genisys
Credit Union
Communitywide FCU
Andrews FCU
Greenwood Credit Union
+ Many more
A score
sees a number.
We see the member.
Two members with the same score can have completely different risk profiles. Traditional underwriting can't tell them apart. Scienaptic can.
Maria
Catering business owner, 12-year member
Bureau Score
658
-
8 years of consistent on-time payments to your CU
-
Cash-flow patterns show recovery after a major client loss
-
Stable address and employment for 9 years
-
No new credit-seeking behavior in 18 months
Approved with confidence
Approval the score alone would have missed
Daniel
New applicant, recently relocated
Bureau Score
742
-
5 new tradelines opened in the last 90 days
-
Balance shuffling pattern across 3 cards
-
Three address changes across two states this year
-
Income claim doesn't match cash-flow signals
Routed for review
Risk the score alone would have missed
What's inside
One platform.
Three decisions.
Alternative data
signals
Alternative data signals
Pull from cash-flow accounts, utility records, telco, rental, and 3000+ pre-built attributes. Score 95% of thin-file applicants the traditional score walks past.
Models
that
learn
Models that learn
Continuous feedback loops recalibrate risk scoring as loans perform. Your models get sharper every quarter without a single rebuild project.
Inbuilt compliance engine
Inbuilt compliance engine
Every decline comes with a rich, regulator-ready set of reason codes. Adverse action transparency. No black box. Your members know exactly what to fix.
The gold
standard for
fair lending
The gold standard for fair lending
Every model attribute runs through fair-lending screens before it ever reaches a member. Approval rates for protected classes go up 45% on average.
The decision path
From application
to answer in
under 2 seconds
Four steps. Real-Time. Every member.
01
Ingest
Application enters via your LOS
Whether the member applies online, in branch, or at a dealer, the application lands in your existing workflow. No change for your team.
02
Enrich
Data orchestrated on demand
Bureau, cash-flow, alternative, and third-party signals pulled only when they add lift. Speed for the easy decisions. Depth for the complex ones.
03
Decide
AI scores meet your rules
Machine-learning models combine with your business rule engine. Your risk appetite, your pricing tiers, your compliance rails. Your decision, automated.
04
Explain
Decision returned with reasons
Approve, decline, or refer with full reason codes. 60 to 80% of applications resolve automatically. The rest land on your underwriter's desk with context.
Scale that proves it works
We've already done this 3 million times this month.
$3.9T
In assets across financial institutions on the platform
3 Million+
Credit decisions processed every month
170+
Lenders trust the platform with their book
$3B
In loan applications evaluated monthly
Plays well with your stack
No rip. No replace. Just lift.
Meridian Link
ORIGENCE
CUDL
Symitar
CRIF Select
temenos
DigiFi
docutech
Episys
+ Many more
Scienaptic helped us approve loans we would have walked past, and protected us on loans that looked clean on paper. That's the whole job of underwriting.
Chief Lending Officer
4Front Credit Union
Built for the regulator in the room
Fair lending
isn't a feature.
It's the foundation.
Disparate impact analysis on every model attribute
Tested for bias before deployment, then monitored continuously in production.
Approval-rate lift for protected classes
45%+ improvement in approval rates for traditionally underserved members, without raising portfolio risk.
Rich adverse action reasons
Beyond the standard four-reason cap. Members get specific, actionable feedback.
Full model documentation
Logic, robustness tests, and limitations documented from day one. Examiners get what they ask for.
100%
of clients have aced their NCUA audits since deployment
Most credit unions run on rule-based decisioning anchored to a score. Scienaptic adds a machine-learning layer that reads 3000+ attributes, including alternative signals traditional scores don't carry. The result is roughly 12x more risk separation than a score alone, which lets you say yes to more good members and no to risk hiding behind clean credit.
6 to 8 weeks for most credit unions. We've pre-built integrations with every major LOS, so there's no custom engineering on your side. Your account team handles configuration, validation against your historical book, and parallel-run testing. You go live with full support.
No. The platform automates 60 to 80% of decisions, which are the routine ones your underwriters spend most of their day on. The complex applications still come to your team, but they arrive with a complete risk picture, alternative data signals, and a recommendation. Your underwriters spend their time on judgment calls, not data entry.
Every attribute used in scoring goes through disparate impact analysis before deployment. Production models are monitored continuously for fair-lending drift. Adverse action reasons are documented in plain English. Model logic, robustness tests, and limitations are generated as audit-ready documents. 100% of our clients have aced their NCUA audits.
Yes. The platform can score 90%+ of applicants without a traditional credit history by reading cash-flow, utility, telco, rental, and behavioral signals. This is where the biggest approval lift typically comes from for community-focused credit unions.
Yes. The Business Rule Engine sits alongside the AI models and runs your policies as configured. Your risk appetite, your pricing tiers, your compliance rails. The AI scores. Your rules decide. Both work together in a single decision call.
Questions, Answered.
The honest FAQ.
Run your portfolio through the platform.
No slides. Just signal.
We'll take a sample of your historical decisions and show you exactly which approvals you missed and which losses you could have avoided. 30 minutes. Your numbers.
API-first | 6-8 week deployment | Built for compliance | NCUA audit-ready