FinTech Predictive Analytics and Machine Learning
Financial services institutions face many internal and external-oriented challenges. From product commoditization, increasing customer demands, increasing acquisition costs to fraud detection and prevention. Meeting these challenges requires accurate and actionable insights on different forms of risk, customer data, operating costs, revenue and various other parameters.
Financial Services organizations can realize the following benefits with our Predictive Analytics solutions:
- Gain insights into your customer needs
- Correlate customer behavior with market trends
- Yield recommendations on new product offerings
- Evaluate what drives customer acquisition
- Improve customer churn prediction
- Identify and maximize cross-sell and up-sell opportunities
Case Studies:
Trading Pattern Categorization
A large US custodian and broker dealer wanted to use machine learning to categorize its retail clients based on their trading patterns and profile data in combination with external time series data such as market movements, proprietary research, general news and global economic data. Three years of trading history were analyzed using proprietary Clustering techniques (including supervised and unsupervised learning). The resulting clusters enabled the firm to discriminate between those with long versus short term perspectives, the general profile characteristics of each cluster and what external data influenced each cluster.
Credit Risk Assessment
A US lending institution, which based its loan decisions largely on client FICO scores, wished to improve the accuracy of its predictions when qualifying a potential new borrower, making loan offers that were better aligned with their customers’ financial states. Rather than rejecting a loan application based on a single risk factor, Softlab360 used proprietary machine learning analytics to create an assessment based on five probable rankings of loan default, enabling the institution to offer modified loan scenarios – lower loan amount, higher interest rate, or a combination of both. Softlab360’s proprietary ML analytics enabled the institution to customize its loan offerings, reducing its lending risk.
