Today, banks are under siege from a horde of fintech companies who are more nimble than the large financial institutions. But the big banks have a deeper expertise and more data, and they can win by harnessing the power of artificial intelligence (AI) and machine learning to reduce costs, increase revenues, and more efficiently comply with regulations.
Learn How Banks use Automated Machine Learning
AI and Banking
As an ever increasing number of fintech companies make an already competitive market even more so, banks are being forced to look for ways to improve the effectiveness and efficiency of their business. AI helps banks improve their bottom line with the people they already have and the data they’re already collecting.
- Optimize customer selection
- Deepen relationships with customers
- Better targeting of new customers
- New products and services powered by AI
- New business models for existing products and services
- Increase customer satisfaction
- Optimize inefficient loan approval processes
- Send market research only to interested investors
- Optimize call center operations
- Build and deploy models cheaper and faster
- Reduce unnecessary AML investigations
- Upgrade Know Your Customer (KYC) programs
- Forecast losses more accurately
- Enhance scenario and stress testing
- Streamline model risk management
- Better detect and prevent fraud
- Enhance cybersecurity detection and prevention
- Access unique Derived Conclusions from technicals, fundamentals, and non-structured data sets
- Optimize your investment and trading strategies with our A.I.-as-a-Service
- Beat the indexes
- Work in concert with portfolio based ROBO advisement
- Audit the trading trail – use historical data to establish “Facts and Circumstances” of the trade
- Improve efficiency of technology spend: Stop using 10% of expensive terminals and use 90% of ELIZE
Model Validation and Risk Management
Banks want to build, deploy, and use predictive modeling to improve the bottom line, but regulation and sound risk management represent significant cost and time to model deployment.
Our competitive advantage in machine learning automation accelerates the efficiency of the 1st and 2nd lines-of-defense by automating time-consuming compliance processes required by regulation. A standardized approach to model building and evaluation, including automated compliance documentation and challenger models means better, safer models in less time.
Six AI Solutions Every Investment Bank Needs
As the cost of doing business rises, so does the need for investment banks to cut costs, and increase revenue – all while providing the highest level of service to their clients. Machine learning and artificial intelligence (AI) represent a huge opportunity for investment banks to improve their highly diverse set of businesses – but how can they get started?
This new eBook highlights practical use cases for AI in today’s investment banking market. Armed with this knowledge, investment bankers can take advantage of the enormous amount of data they generate and transform into AI-enabled enterprises.
Investment banks can use AI in six critical ways:
- RFQ pricing optimization
- Algorithmic trade execution
- Research recommendations
- Operational break and failure prediction
- Trade and communications surveillance
- Regulatory due diligence
AI has the potential to transform the way banks do business, and most banks have only scratched the surface.
Contact ELIZE Solutions today to learn how you can build an AI-driven Bank.
Banking Use Cases
Banks are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from risk analysis and fraud detection to marketing, in order to make data-driven decisions that lead to increased profitability.
Elize Solutions Cloud, powered by Amazon Web Services
To deliver Elize Solutions Cloud, we have partnered with Amazon Web Services (AWS), the world’s most comprehensive and broadly adopted cloud platform. The flexibility and scale of the AWS platform enables Elize Solutions to deliver a robust, secure, on-demand platform to our customers. This allows rapid deployment of Elize Solutions and allows our users to quickly build and deploy highly accurate machine learning models in a fraction of the time.