As COVID-19 induced socio-economic volatility continues unabated, the financial services industry is faced with grave concerns about counterparty risk. Banks are struggling to assess the riskiness of their vast customer portfolios. The traditional methods using ratings and financial statements provide post facto analysis. In order to ensure proactive risk management, banks must efficiently track, assess, and manage counterparties’ riskiness on a near real-time basis.
TCS’ Early Warning Framework for Proactive Risk Management facilitates real-time and objective assessment of the riskiness of counterparties. It drives lexicon-based search of news articles relating to counterparties and crawls the news websites acknowledged and followed by banks. Powered by a machine learning based algorithm, the framework analyzes the newly published articles and generates a ‘risk score’ for each counterparty in near real time. If the defined hurdle rate is breached, it automatically triggers mails to identified personnel within the bank, who can then activate mitigation measures.
The framework is built on an open source stack that allows configuration of external sources for news capture and provides machine learning powered news analytics, real-time dashboards and alerts, and has the ability to slice and dice data for investigation.
TCS’ framework helps banks and financial services firms to:
- Continuously track large number of counterparties Practice forward-looking risk management
- Offer multi-lingual support for a comprehensive global view
This framework can also be cross-leveraged for similar use cases in fraud management, KYC, and liquidity risk as well as market risk assessment and mitigation.