Strengthening Onboarding Security with AI-Powered Pre-KYC Screening
A global bank wanted to enhance onboarding security with pre-KYC screening - verifying users with minimal details before full KYC checks.
Outcomes
40%+
Early Identification of Fraudulent Behaviour
25%
Customer Drop-Off Reduction
0%
Production Data Exposed
$100k
Average PoC Cost Saving Per Vendor
Technology Vendors Suited to Evaluation
Business Problem
The bank’s onboarding process lacked early-stage fraud prevention, allowing fraudulent accounts to progress deep into the pipeline before detection. Traditional KYC procedures added friction for legitimate customers, leading to drop-offs and poor experience.
The bank needed a secure, proactive pre-KYC mechanism to identify risk earlier, reduce fraud exposure, and maintain a smooth onboarding journey.
Challenges
- High Initial Fraud Exposure: Without early-stage identity checks, fraudulent accounts were frequently discovered only after significant onboarding efforts.
- Customer Friction: Traditional KYC checks at early stages discouraged legitimate customers due to lengthy processes.
- Reactive Approach: Fraud detection primarily reactive rather than proactive, delaying identification and response.
From Idea to Evidence with NayaOne
The bank used NayaOne’s secure sandbox to validate multiple pre-KYC screening solutions safely and efficiently, simulating real onboarding scenarios without exposing sensitive data.
- Accelerated Testing: Pre-KYC models were assessed using synthetic profiles and anonymised behavioural datasets, allowing for rapid evaluation without privacy risks.
- Risk-Free Experimentation: Multiple vendor solutions were tested in parallel within the sandbox, significantly shortening vendor selection timelines.
- Realistic Behaviour Modelling: Synthetic user behaviour and risk profiles were generated to train and benchmark predictive models under realistic onboarding conditions.
- Predictive Analytics: AI vendors’ solutions applied real-time scoring to user interactions, analysing device fingerprints, IP addresses, and session behaviour to identify early fraud indicators.
The controlled, data-secure environment enabled the bank to identify high-performing solutions capable of detecting fraudulent intent at the pre-KYC stage, enhancing both security and customer experience
Impact Metrics
PoC Timeline Reduction
8 weeks with NayaOne vs 12 – 18 months traditionally
Time Saved in Vendor Evaluation
1+ year
Decision Quality
The bank gained hard evidence that early stage fraud detection significantly reduced downstream fraud management efforts.
KPIs
- Fraud Detection Rate (%): Accuracy in identifying fraudulent users during pre-KYC screening.
- False Positive Rate (%): Percentage of legitimate customers incorrectly flagged as high-risk.
- Onboarding Conversion Rate (%): Number of legitimate customers completing onboarding after pre-KYC screening.
- Average Screening Time (seconds): Time taken to complete initial risk assessment per user.
- Fraud Loss Reduction (%): Decrease in financial losses due to early fraud detection.
- Compliance Alignment (%): Adherence to regulatory standards and internal KYC policies.
Validate Pre-KYC Screening Solutions Before Deployment
Use NayaOne’s secure sandbox to test AI-powered pre-KYC solutions with synthetic data and behavioural analytics — evaluating fraud detection accuracy, onboarding speed, and compliance performance before production rollout.
