The client is a world-leading professional services company operating across several sectors. They were looking for trained consultants who could provide financial advisory and data analytics support to their Financial Crime Department.
The client’s banking customers were struggling to grapple with data management and visualisation, make sense of vast amounts of financial data and derive meaningful insights from it. Their existing processes were cumbersome, inefficient, and lacked the ability to provide real-time data-driven solutions.
They required a solution that could ingest data from various sources, standardise it, and store it in a structured database for efficient analysis. Additionally, the client sought a user-friendly tool to create visually appealing and interactive charts that could be easily filtered to extract specific insights.
Core Consultants provided a a wide range of expertise in data analytics and programming to aid the development of a powerful Python application. The key features of the solution included:
- Data Ingestion: The Python application was designed to ingest data from banks in any format, ensuring flexibility and compatibility with various data sources.
- ETL Process: The application included a robust ETL process that converted and stored the data in a SQL library. This facilitated easy access and retrieval of data for analysis.
- Interactive Data Visualisation: One of the highlights of the application was its ability to produce aesthetically pleasing and interactive charts.
The Python application yielded positive outcomes for the client and their banking customers:
1. Increased Efficiency
The application significantly streamlined the data management and analysis process, reducing the time spent on these tasks and enabling more effective decision-making.
2. Enhanced Data Insights
By visualising the data through interactive charts, banking clients gained deeper insights into their financial operations, leading to improved risk management and fraud detection.
3. Cost Savings
The adoption of the Python application led to substantial cost savings for the client's banking customers, as they no longer required expensive licenses for data visualisation tools.
4. Greater Control
The application's flexibility allowed for quick updates and modifications, giving the banking clients greater control over their data analysis processes.
5. Real-time Monitoring
The real-time filtering feature of the charts allowed for proactive monitoring of financial activities and immediate action in response to potential financial crime.
6. Positive Impact on Services
The Python application positively impacted how the client's banking customers delivered their financial services, empowering them with data-driven insights to provide better and more secure experiences for their own customers.