Mathematical optimization is a well-established, essential technological tool in the financial services industry. For over 50 years, mathematical optimization technologies have been used by leading companies across the financial services ecosystem (including institutional and consumer banks, wealth management firms, hedge funds, insurance providers, and fintech players) to:
- Address a wide variety of complex business problems including portfolio optimization, cash management, trade settlement, and asset-liability management.
- Make optimal, data-driven decisions that deliver improved operational efficiency, profitability, and regulatory compliance as well as reduced risk and costs.
Opportunities for Optimization
Mathematical optimization is used by financial services companies today to optimize many different customer-facing and back-office functions. Here are some of the main applications of mathematical optimization in the financial services industry:
- Asset Management: Portfolio Optimization, Collateral Allocation, Portfolio Replication, Bond Management, Hedging Strategies, Debt Management, Credit Swap Management, Trade Settlement, Asset-Liability Management, Payment Netting, Systemic Risk Management
- Operations Management: Cash Management, Collection Management, Branch Network Optimization, Fraud Cost Reduction, Credit Card Offering Optimization, Appointment and Field Service Scheduling
With mathematical optimization technologies, financial services companies can tackle their complex business problems, optimize their decision making, and achieve their business goals by:
- Maximizing returns
- Boosting resource utilization and operational efficiency
- Improving regulatory compliance
- Reducing operating, transaction, and customer acquisition costs
- Increasing processing speed
- Improving customer service
- Maximizing profitability
Read the Financial Services Industry Solution Sheet