Basel III regulations will change the way bank address, manage risk and finance. The new emphasis on risk management that is inherent in it requires the introduction/evolution of a risk management framework that is as robust as the existing finance management
infrastructures. As well as being a regulatory regime, Basel III in many ways provides a framework for true enterprise risk management, which involves covering all risks to the business.
To deliver compliance against Basel III, all banks must now ensure that risk and finance teams have quick and easy access to centralized, clean, and accurate data. This data must reflect their bank’s credit, market, concentration, operational, impairment,
and liquidity risk. Thus it will also going to impact bank activities/process which will require to undertake and will revolve around aggregating, standarizing and analyzing data to derive high quality insights for internal and regulatory framework. But current
reality is many banks data is managed in silos. Bank department use systems that suits department specific needs and store data in varying incompatible formats. Integrating these disparate systems will be time-consuming and costly undertaking especially since
the amount of data generated by the bank exposed in the past decade. According to a 2011 report by the Tower group, mid-tier bank's data output grew by 150 times over the previous seven to eight years. Thus banks need to have a centralised data model which will
be able to respond faster and more efficiently even when regulator clarify critical issues. It will further streamlining their compliance and reporting processes
All banks will also need to calculate the enhanced capital, new liquidity ratios, and new leverage ratios to be in a position to start reporting to local supervisors—in the multiple formats. Hence banks need to increase their quality of capital by focusing
on liquidity and common equity : improve supervision of firm-wide risk management and provide detail reporting on regulatory capital and calculation of capital ratios like liquidity coverage. Banks need to maintain higher capital against risky instruments
like structured products and thus they need to review their trading books. Liquidty metrics need to be reported on daily basis that means bank need to create data points which can be many (thousands or more) across the organization to capture it. Thus the
ideal solution would be which can consolidate, calculate, and report the organization’s capital, liquidity, and leverage ratios from a single, centralized reporting platform. It would seamlessly integrate with other source systems and have strongdata quality
checking and storage capabilities.
Hence bank need a solution or platform which can seamlessly integrate with other source/legacy systems and which can provide strong data quality checking and storage capabilities. It can also be extended for consolidating, calculating, stress test,
and reports for organization’s capital and liquidity risk. Implementing all this would streamline the process, allowing risk managers to focus their attention toward primary risk management activities rather than the time-consuming data extraction, quality,
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