AI-Powered Credit Scoring Platform
for Banks
RiskSeal provides digital footprint analysis for banks, delivering over 400 data points from emails, phone numbers, and IP lookups to streamline operational efficiency.
Key benefits of Digital Footprint
Analysis for banks
Enhance the quality of your credit portfolio
Reduce your default rate by up to 25%, all while simultaneously doubling your approval rate and streamlining loan disbursement.
Reduce operating costs
Streamline your loan origination process by automating key tasks and cutting operational expenses. Get a ready Digital Credit Score in 5 seconds.
Effectively verify your applicants
Simplify identity verification with advanced technologies - Face recognition, Name match intelligence, and Location insights analysis.
Boost your credit portfolio quality with Digital Footprint Analysis
Enhancing credit scorecards
with 400+ digital insights
RiskSeal enhances bank scorecards with over 400 alternative data points drawn from digital footprint analysis. Our data reduces the gray area, providing clarity where traditional methods fall short. RiskSeal automates decision-making with a ready-to-use Digital Credit Score.
Digital footprint insights
Get 400+ alternative data insights to strengthen your decision-making process.
Predictive power increase
Boost your scorecards’ predictive power with an AUC score of 83%, improving the reliability of your credit decisions.
Risk management
Assess account risks using alternative data. Achieve x2 increase in approval rates while reducing default rates by up to 25%.
Identity verification
Unlock advanced identity verification techniques, such as Face recognition, Name matching, and Location insights.
Custom features
Gain access to 400+ explainable data points to develop customized features that align with unique market demands, optimizing model performance.
360-degree user view
Create a comprehensive user profile by integrating digital credit scores, trust scores, and a range of behavioral and solvency metrics.
Results banks achieve with RiskSeal
Credit decision quality
Leverage over 400 real-time data points and strengthen your scorecards for smarter lending decisions.
Customer experience
Accelerate your loan origination process and deliver a faster, more efficient service.
Financial inclusion
Tap into the unbanked population and uncovernew lending opportunities.
FAQ
What data does RiskSeal provide to banks through digital footprint analysis?
RiskSeal analyzes applicants across 200+ platforms, including social media, e-commerce sites, professional services, messaging apps, gambling websites, and more.
By evaluating online behavior, financial habits, and digital presence, RiskSeal helps banks assess credit risk and detect potential fraud.
This data provides deeper insights into solvency, spending patterns, and potential risk factors, enabling more informed credit decisions.
What additional checks does RiskSeal offer to enhance banks' credit decision-making?
RiskSeal provides advanced identity verification tools to improve credit decisioning accuracy. These include face recognition technology, name match intelligence, and location insights analysis.
By leveraging these checks, banks can confidently verify applicants’ identities and detect inconsistencies, further reducing fraud risk and improving decision quality.
How does RiskSeal enhance banking decisions with its Digital Credit Score?
RiskSeal Digital Credit Scoring system offers banks a predictive assessment of a customer’s likelihood to repay, based on their digital footprint.
By analyzing social profiles, professional and educational backgrounds, and lifestyle habits, RiskSeal helps banks identify high-risk applicants early, reducing dependence on traditional KYC and credit bureau checks.
Additionally, the Digital Credit Score strengthens banks’ Machine Learning models, enhancing the accuracy of credit scorecards and improving decision quality.
How quickly can RiskSeal process transactions for banks?
RiskSeal processes transactions in real-time, completing comprehensive checks in as little as 5 seconds, depending on the complexity of the data.
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