Insights Driven Business and Operations Framework
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Banking
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Banking Services Transformation: Unlocking Exponential Value
TCS’ solutions help banks and FIs push traditional boundaries and build cognitive banking enterprises for better value, resilience, and inclusivity. Learn more.
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Drive agility and resilience using data analytics
CHALLENGE
The impact of COVID-19 on businesses has been significant. Capital market firms have especially faced a major jolt as a result of market uncertainty, near zero interest rates, shrinking liquidity and funding, credit tightening, and spike in operational tasks. This has created immense disruption in the short to medium term, leading to decreased consumer confidence, lower margins, increased costs, and reputational risks. To thrive in the post-pandemic world, banks and financial services firms require a data-driven approach to create more value for the business as well as customers.
TCS SOLUTION
TCS’ Insights Driven Business and Operations Framework enables banks to harness banking data using analytics and machine learning to improve operational efficiency and business value. This will help banks overcome the capital market challenges, align their businesses to the post COVID world and explore new revenue opportunities. The key features of the framework are:
- Predictive analytics using TCS’ Digital Twin model to create digital replica of capital markets processes for resilience, risk reduction, and improved efficiencies
- Predicting future cash and liquidity needs and shortfalls by modelling ERP, treasury, GL, and business operations using cash history, capital budget, operating budget, business units, credit facilities, and investments data to adapt to changing market conditions
- Data monetization framework to identify and derive revenue generating data sets and related use cases across domains
- Front-to-back insights to drive business outcomes and to adopt a purpose driven approach
BENEFITS
TCS’ framework drives seamless implementation of AI and machine learning in banking to enable financial services firms to:
- Predict fails to minimize exceptions and conduct root cause analysis of issues to achieve efficient resolution through front-to-back insights using machine learning techniques
- Eliminate waste and optimize work packets through risk-based profiling of transaction data
- Drive incremental business value by delivering purpose-driven client services
- Conduct behavior modelling at each process step using internal and external structured and unstructured data sets to predict all possible outcomes, resulting in business value, risk reduction, and higher efficiencies
- Find new sources of revenue and create business value through monetization of internal and external data
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