SYNECHRON'S ARTIFICIAL INTELLIGENCE SOLUTION
Cognitive Machine Learning involves programmed self-learning systems that use data mining, pattern recognition and Natural Language Processing (NLP) to reflect human actions. Within the realm of Artificial Intelligence, machine learning systems are based in computer science verses statistics and have an emphasis on prediction. Building these ‘cognitive’ models, therefore, requires a deep understanding of business operations, data inputs and factors that would impact the model so that it can continue learning and become more accurate with the requisite data.
Synechron’s Artificial Intelligence solutions for Cognitive Machine Learning combine a deep knowledge of data mapping and financial operations with powerful data analysis to conduct complex calculations from intraday liquidity to LCR reporting. To build the solutions, we’ve combined our knowledge of global regulatory requirements and finance, treasury and risk processes to automate calculations and predict future requirements.
HOW WE HELP
Machine learning uses advanced computer science models, data mining and pattern recognition combined with Natural Language Processing (NLP) to predict future outcomes. This technique is best used when applied to the most complex data challenges that require real-time calculations and where a large volume of historical and real-time data can help the model to learn and become increasingly accurate over time.
Synechron’s Machine Learning solutions allow financial services firms to address some of the most complex liquidity, pricing and risk challenges facing financial institutions today. Firms can:
- Streamline complex intraday liquidity calculations
- Automate data collection and analysis
- Enhance liquidity and collateral management processes
- Address intraday and LCR reporting requirements and improve ALM desk liquidity management
PREDICT FUTURE OUTCOMES
Applying Synechron’s Machine Learning solutions, to business processes enables firms to:
- Increase efficiency, turnaround time and accuracy on data modeling and calculations
- Improve quality, reliability and speed in deriving liquidity numbers
- Move to intraday liquidity calculations and toward intraday LCR reporting
- Optimize liquidity to minimize underwriting
- Improve predictability and reliability of liquidity, finance and treasury data required under Basel III and IFRS 9
- Reduce FTE operations cost
- Enhance regulatory reporting and related operations
- Create a reliable price for illiquid OTC instruments to support trading strategies and collateral management
Synechron’s Cognitive Machine Learning solutions are designed specifically to provide applications that can be applied to various scenarios which lend themselves well to a Cognitive Machine Learning solution. Click to read how Synechron’s Cognitive Machine Learning solutions are helping clients to address complex challenges in real time.
Liquidity Coverage Ratio (LCR) Reporting
Forecast values for the current day and computing the liquidity coverage ratio using historical, high-quality liquid assets, inflow, outflow and net cash flows.Read More
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