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Development of a Scalable Data Science Platform for Financial Risk Management and Decision Support

coherentsolutions.com

Financial services

Business Challenges in Financial Risk Management

Financial institutions face regulatory, stakeholder, and auditor demands for verifiable evidence to justify pricing and positions. Legacy systems struggle with contextual analysis, time-series analytics, and auditable documentation, leading to complex verification processes and increased operational risks.

About the Client

A Silicon Valley-based company specializing in decision science, data management, and analytics, delivering software solutions that provide contextual insights for business decision-making.

Project Goals for Enhanced Risk Management Platform

Develop a data-science-driven platform ensuring data integrity and reliability
Enable real-time data quality monitoring and exception identification
Simplify Profit & Loss (P&L) creation and root-cause analysis workflows
Support scenario analysis, trend analytics, and audit documentation generation
Provide scalable processing for large financial datasets with minimal coding requirements

Core System Functionalities and Features

Real-time data quality metrics dashboard
Zero-code root-cause analysis interface
Automated P&L creation workflows
Scenario and trend analysis with price backtesting
Custom dataset generation with lineage tracking
Integrated audit documentation repository

Technology Stack Requirements

Python/R for statistical analysis

Apache Spark for distributed processing

Cloud-native architecture (AWS/Azure)

Time-series databases (e.g., InfluxDB)

React.js for UI components

System Integration Needs

Internal financial data warehouses
Third-party market data APIs
Enterprise audit management systems
Identity and access management (IAM) platforms

Non-Functional Requirements

Horizontal scalability for petabyte-scale datasets
Sub-second latency for real-time analytics
Role-based access control (RBAC) for compliance
99.99% system availability SLA
Automated failover and disaster recovery

Expected Business Impact of the Data Science Platform

The platform will enable financial organizations to reduce operational risk by 40% through automated data validation, accelerate decision-making by 60% via real-time analytics, and achieve 100% audit compliance with automated documentation. It will also lower total cost of ownership (TCO) by 30% through scalable cloud architecture and self-service capabilities.