Business intelligence for banking
Discover how our business intelligence team helped a neobank reduce financial losses caused by frequent fraudulent activities, identify new revenue streams, improve operational efficiency, and optimize the customer experience.
2020 — present
About the client
Our client is a US-based neobank that has been gaining popularity among young people thanks to their app’s visuals, functionality such as cashback and rewards, and collaborations with popular streaming platforms, online services, and restaurants. One of the bank’s killer features is a comprehensive wealth management module with an educational component that helps customers track their expenses, analyze their spending habits, and carry out financial planning.
Our client identified substantial financial losses caused by fraudulent activity. Fraudsters took advantage of transaction processing times to withdraw money and then request refunds from the bank. In addition to this scheme, analysts recognized more fraudulent activities that required urgent fraud prevention solutions to:
- detect suspicious activities and behaviors
- automatically block fraudulent activities
Building a reliable fraud-prevention system
For this, Yalantis specialists:
- developed a custom rule-based fraud detection module to prevent or minimize suspicious activities and mitigate the risk of a successful fraud attack
- utilized business intelligence (BI) best practices to reduce fraud-related financial losses by improving fraud monitoring, providing data-based foundations for blocking suspicious activities, and accelerating decision-making
Implementing business intelligence tools
We integrated the client’s solution with business intelligence tools including Amazon Redshift and Amazon QuickSight. We also:
- duplicated the production database to carry out all analytical activities on a copy of the database. This way, we minimized the impact on the production database and preserved its stable performance.
- integrated all tools and set up a proper data exchange flow among them through multilayered SQL scripts written in Python to analyze relevant real-time data.
- created dashboards with real-time data visualization and enabled advanced custom report generation using Amazon QuickSight.
- implemented charts to visualize historical data and trends, revealing anomalies and atypical behavioral patterns.
Reducing financial losses through data-based fraud identification
After implementing business intelligence processes, our BI specialists:
- analyzed historical data, identified patterns of fraudulent behavior, and pointed out all possible vulnerabilities in the client’s security system and business logic
- used BI insights to develop a system of rules with threshold-based metrics to help signal potential fraud attacks
- implemented a rule-based fraud protection module to block possible fraudulent operations and prevent the client from losing money
Automating business processes
Having analyzed business processes based on their level of complexity and resource consumption, our experts:
- segmented all processes and evaluated the need for manual intervention
- automated business processes that don’t require human intervention in order to unburden staff, increase their productivity, and improve operational efficiency
We’ve achieved the following results with the implementation of business intelligence:
40% decrease in fraud-related financial losses per quarter thanks to the rule-based fraud prevention system
5% increase in the user adoption rate within a quarter thanks to new revenue streams
Better operational efficiency and human resource optimization thanks to process automation
ENGAGE DATA-DRIVEN DECISION-MAKING FOR OPERATIONAL EXCELLENCE
Yalantis will help you implement business intelligence and set up all necessary data analytics processes