Industries
Fintech, Banking, Insurance, Factoring
Functions
Loan Processing, Underwriting, Credit Risk Assessment
Teсhnologies
AI, Big Data Analytics, API Integration, Postgres, React, Node.js
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Objective:
To overhaul the loan processing system for financial institutions by leveraging IT solution to aggregate and structure semi-structured data from various accounting systems, thereby boosting the efficiency and quality of lending services.
Solution Highlights:
SaaS IT solution was designed to work seamlessly with different accounting standards, such as IFRS and US GAAP, and can integrate data from various accounting platforms including QuickBooks, Zoho, NetSuite, Ms Dynamics, Xero, SAP, among others. This capability ensures that financial consolidation is hassle-free, enabling institutions to cater to a broader range of clients with diverse accounting practices.
Enhanced Features:
- Comprehensive Integration: Supports over 157 industry-specific algorithms and covers 95% of banking report formats for in-depth data analysis.
- Advanced Analytics: Utilizes AI for real-time analytics, enhancing loan quality and reducing fraud.
- Efficiency and Savings: Accelerates loan processing by over 50%, with document exchange and decision-making processes significantly faster, resulting in substantial time and cost savings.
Architecture and Integration of the Proposed Solution:
The solution's architecture hinged on a robust data pipeline, incorporating PowerBI for analytics visualization, PostgreSQL for database management, NiFi for data flow automation, Python for data processing and ML, and Airflow for orchestrating workflows. This system is interconnected with SAP S4 for enterprise resource planning.
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Conclusion:
Credit Risk Management IT solution marks a significant step forward in the digital transformation of the financial sector, streamlining loan processing, reducing risks, and enabling cost-efficient operations while accommodating a wide range of accounting systems and standards.
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