Why Credit Risk?:
- Credit Risk refers to the risk that the lenders might have to face as a result of the inability of the borrowers to pay back the debt.
- Credit Risk Management came to the limelight post the financial crisis and the credit crunch that followed.
- Credit Risk Management is a critical component for a comprehensive approach to ascertain risk and is essential for the success of any financial institution.
Challenges to a Successful Credit Risk Management
- Establishing an appropriate credit risk environment – Proper risk modelling framework enables banks to generate meaningful insights from the complex data.
- Inadequate knowledge and control of customer portfolio – not having the right data organized for easy access.
- Ineffective risk measuring tools – real time and robust tools for making informed decision as and when required.
- Complicated manual reporting methods used which overburden resources.
The ERPA Advantage
- Accelerators – Ready Enterprise Data Platform (EDP) with appropriate tools and techniques.
- Availability of business blue prints.
- Governance – Flexible engagement models, delivery QA and proven project approach.
- Assurance – Proven experience and skilled resources.
- Capability – Innovative Cost Model, Global Delivery Model and Right Team.
Minimum 40% reduction in storage using ERPA’s EDP
Increase in Performance 10X of Data jobs
Credit Risk Model is designed to help businesses (that offer various debt instruments in the form of loan, credit card, etc.) to analyse data systematically to improve decision making, especially where there is a risk of default on a debt. Credit Risk Metrics are made available at Risk Groups, Portfolios and Geographical level to Risk Managers with intuitive visualizations by assessing risks at various portfolios.
- Need for maintaining high-quality data that facilitates data reuse, accessibility, and analysis.
- Inefficient and Improper batches result in additional cost of hardware upgrades.
- Consolidating and realizing data assets, consisting of both traditional Enterprise data as well as big data, is a challenge long standing. This scales up especially when mergers/acquisitions bring new data sources.
- Huge volume and variety of dummy data is often required to meet the development and testing needs for application testing.
- Maximizing usability of data with optimal Storage Space Utilization.
- Migrate long running jobs from legacy environments to Big Data.
- Single view of Enterprise data. User Friendly UI with easy maintenance.
- ERPA’s Data Curation service enables Profiling, Data Quality and Standardization of your data before Ingesting data into Data Lake or reservoirs.
- ERPA’s Batch optimization service ensures timely completion of batches within the acceptable SLA.
- ERPA’s Data Virtualization service delivers a unified and integrated view of data, as required, from different source systems.
- With ERPA’s Test Data Generator service, create test data based on rules and constraints.