Payment Analytics

FNA Payment Analytics

Predictive Analytics For Financial Infrastructures

FNA Payment Analytics helps financial market infrastructures and central banks model liquidity and operational risks, evaluate alternative system designs and carry out stress tests. 
Combining advanced network theory and agent-based modeling with interactive visualizations.
 
FNA Payment Analytics methodologies are based on leading research in network theory and financial infrastructures by FNA and its collaborations with top universities and central banks. The interactive dashboard makes these advanced analytics easily accessible through a well-thought user interface.

 

Key Features

  • Monitor system participants with comprehensive network maps and risk metrics, including FNA’s SinkRank™ and metrics proposed by BIS/BCBS.
  • Identify emerging liquidity and operational risks with statistical and visual detection of outliers.
  • Build intuition with fast interactive data exploration powered by algorithms that filter signal from noise.
  • Communicate risks with a new visual language understood by quantitative analysts and senior management alike.
  • Quickly carry out predictive stress tests and explore the results visually or numerically.
  • Automate the analysis into real-time dashboards for monitoring and oversight of the system

For Who?

  • Financial Market Infrastructures (FMIs)
  • Central Banks and Regulators

Use Case

Simulations of Alternative Liquidity Saving Mechanisms

Helps payment system operations in choosing which to implement

A Liquidity Saving Mechanism (LSM) was introduced into the Bank of England’s RTGS infrastructure in April 2013. To evaluate alternative methods of LSM, the Bank run a series of simulations using FNA PaymentSimulator. The paper ‘Liquidity Savings in CHAPS - a simulation study’ summarizes the results and finds that aggregate liquidity savings of up to 30% were to be expected. In ex-post analysis, these savings have also mainly materialized.

Network Analytics of BoK-Wire+

Help identify systemically important banks

The project described the network properties of the Korean Interbank payment system (BOK-Wire+), identified systemically important banks, and developed a new intraday liquidity indicator. The project helped Bank of Korea develop monitoring indicators what are especially suited for continuous oversight of intraday liquidity and systemic risks in payment systems. The full results are published in Network Indicators for Monitoring Intraday Liquidity in BOK-Wire+

Recommendations...

FNA Correlations is integral part of our daily risk management process. It draws our attention to emerging risk, and has helped us minimize exposure to troubled assets early.
James Dougall
Managing Director, Secure Wealth Management Ltd

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Download a pdf brochure of PaymentSimulator for more information
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FNA Payment Analytics

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