What is MotionScore?
MotionScore enhances credit scoring, credit fraud and credit default prediction. It is especially effective at flagging fraudulent intent.
Our patent-pending AI technology identifies hidden patterns in signatures and online or mobile user interactions. These patterns can reflect behaviors and personal characteristics relevant to creditworthiness and reliability.
We can generate prediction models from previously untapped, anonymous client data that enable financial institutions to improve their default and fraud risk scoring significantly.
Proof of Concept
We tested MotionScore on tens of thousands of personal loan customers, where we improved the lender's GINI by more than 10%.
The two overlapping histograms display the predicted default probabilities of the model on the test dataset. The difference between the means and shapes of the two histograms is clearly visible. There are much more non-defaulters than defaulters below the (0.45) threshold.
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Reasons to Choose MotionScore
#1 Improved
Accuracy
Harnessing the power of our patent-pending technology, we provide credit scoring accuracy and reliability that significantly surpasses traditional methodologies. Our models deliver correlations distinctly different from zero, offering a substantial boost to existing methodologies.
#2 Enhanced Predictive Power
#3 Easy
Integration
By analyzing signature patterns, motion data, and user interactions, we unlock previously untapped sources of predictive power that are especially useful for default prediction. This comprehensive approach enables MotionScore to achieve more accurate and nuanced credit scoring.
MotionScore is designed to fit seamlessly into your existing systems and workflows. It allows you to incorporate motion, signature, and interaction data into your predictive analysis effortlessly, either independently or in conjunction with existing methodologies.
#4 Dedicated Support
Our committed customer support team is always ready to assist you. We provide round-the-clock support to ensure that you maximize the benefits of our platform and navigate any challenges you may face.
How MotionScore Works
#1 GDPR Compliant Data Collection
We collect motion data, such as cursor and mobile movement, or signatures on-premise, storing them anonymously, ensuring GDPR compliance and maintaining the highest data security.
#2 Feature Extraction & Profiling
MotionScore employs state-of-the-art algorithms to extract and profile specific features relevant to the individual from the collected user data set, offering a detailed understanding of their characteristics.
#3 Personalized Scoring with Prediction Models
MotionScore employs a prediction model to compute the user's unique MotionScore, a personalized measure derived from their
motion-related characteristics.
#4 Seamless Integration &
Dedicated Support
The resulting MotionScore, combined with user IDs and other calculated parameters, effortlessly integrates into your system, enabling informed decision-making, supported by our dedicated 24/7 customer support.
Key Benefits
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Data
Enrichment
Enriches credit scoring data by incorporating personal attributes derived from motion, augmenting the accuracy of credit or risk assessments.
Explainable
Models
Built on supervised ML, our prediction models provide interpretable parameters, ensuring transparency & easy understanding for operators.
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Fraud
Signals
During model training, MotionScore excels at identifying fraud risks, bolstering security measures and minimizing potential risks.
Customization & Fine-Tuning
Prediction models tailored to different customer segments or loan products can be created & fine-tuned using historical data, increasing accuracy & relevance.
Modularity for Flexibility
As a versatile output module,
MotionScore easily complements other AI/ML-driven credit scoring systems.
Scalability & Fraud Prediction
MotionScore extends its predictive capabilities to detect fraud risks associated with in-branch & online transactions, leveraging signatures & browser usage data.
Secure Data Handling
We prioritize data privacy and adhere to the highest security standards, so you can rest assured that your sensitive
client data is secure.
RWA Value Enhancement
MotionScore contributes to more accurate Risk-Weighted Asset calculations, potentially leading to a more extensive portfolio.
Use Case
A financial institution using MotionScore to calculate the probability of a default when a person applies for a personal loan.
STEP
#1
Client applies
for credit
A person applies for personal loan in a bank branch and signs the application digitally on a signature pad. The individual's motion data is stored in the system according to GDPR.
STEP
#2
Extracting data from e-signature
Extracting data from signature that supports more accurate risk prediction
such as: people with lower levels of education are more likely to push the pen harder when signing their signature and people with lower levels of education are less likely to repay their loans in general.
STEP
#3
Risk assessment with new metrics
The credit risk specialist combines the usual credit risk default model with our additional, state-of-the-art metrics to reach the most accurate prediction and minimize the cost of default for the financial institution.
Projected Default Loss Savings
With a conservative average of 10% GINI improvement and a 3% default rate, integrating MotionScore can result in significant cost savings for lenders. For each $1 billion in loans, the projected annual reduction in default-related losses amounts to $3 million.
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$3+ million per year
for $1 billion in loans
Ready to Unleash the Power of Motion and Signature Data for Financial Risk Prediction?
Get a free evaluation or a POC quote today and discover how MotionScore can revolutionize your risk management!