ScoreFast for Financial Services
ScoreFast data models help financial services companies optimize sales effectiveness, mitigate risk and improve customer engagement.Industry Challenges
Customer Engagement
Disparate sources of customer data makes it difficult to detect patterns and act on data
Financial Risk
Static rule-based risk assessment and fraud detection fails to capture emerging risks
ScoreFast Solutions
Financial Analytics
ScoreFast enables smarter decisions when calculating profitability, predicting sales and mitigating portfolio risk.
- Debt collection optimization
- Risk assessment
- Propensity to pay models
- Fraud detection
Customer Analytics
Improve customer service by analyzing customer profiles and needs
- Predict customer attrition
- Calculate customer profitability
- Improve CSAT and NPS
- Cross sell/ up sell products
ScoreFast Solutions
Financial Analytics
ScoreFast™ enables you to make smarter decisions by calculating profitability, predict sales and mitigate risk on financial portfolios.
- Debt collection optimization
- Risk assessment
- Propensity to pay models
- Fraud detection
Customer Analytics
Analyze customer profiles to understand their needs, enabling you to serve them better.
- Customer attrition prediction
- Calculate customer profitability
- Improve CSAT ratings, NPS ratings
- Cross sell/ up sell products
Our Approach
Data ingestion
ScoreFast ingests myriad datasets – financial data, customer information, social media, location, and sales & transaction history – for modeling. For example, using financial products and customers information with sales history yields clues for optimized cross-sell/up-sell of products.
Algorithm selection and deployment
To improve financial metrics, loan collections volume, credit risk level etc. ScoreFast sorts through algorithms and selects the best one through iterative comparisons.
Model management and updates
Modeled collection analytics, risk scoring, or fraud detection are monitored for performance and retrained frequently to reflect updates in data and metrics
Our Approach
Data ingestion
ScoreFast can ingest a wide variety of data sets – financial data, customer information, and data related to social media, location, sales and transaction history, for comprehensive modeling and insights generation. For example, using financial products and customers information in conjunction with sales history can yield clues for optimized cross-sell/up-sell of products.
Algorithm selection and deployment
Depending on the objective (improve financial metrics – loan collections volume, credit risk level) ScoreFast sorts through a variety of algorithms and selects the best one through an iterative comparison process.
Model management and updates
Models deployed into the collection analytics, risk scoring, or fraud detection are monitored for performance and are updated routinely. These models are re-trained frequently to reflect updates in data and metrics.
Customer Success
24% Higher Debt Collection
The traditional debt collection procedure is to go after customers with large balances and then work their way down to smaller balances. This process ignores a debtor’s likelihood to pay, which considers the debtor’s behavior with the collections agency. Indicators like ignoring a collector’s call, promising to pay, and frequency of contact number all affect the customer’s likelihood of paying.
Tata Motors Financial – the finance lender for India’s largest auto manufacturer – uses ScoreFast to maximize collections, ultimately increasing collections by 24%.