Predictive vs Prescriptive analytics
Let’s see what are the key differences between predictive and prescriptive analytics:
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Testing complex digital banking systems
Today’s digital world has proven that manual testing is ineffective and unable to cope with the increasing number of interconnected systems, APIs, open-source components, mobile, DevOps pipelines and containers etc.
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How do we define and measure technical debt?
Technical debt (also known as code debt, but can be also related to other technical endeavors) is a concept in software development that reflects the implied cost of additional rework caused by choosing an easy (limited) and fast solution now instead of using a better approach that would take longer. In short, when developers take shortcuts that enable them to quickly deliver features or functionality to keep up with deadlines and customer demand but with the risk of compromising software quality and maintainability.
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ConnectIQ Smart Data Analytics: Drive value with ‘Next Best Product’
The pressure is on for banks to become digital and make sure their customers are happy. They are becoming more customer-centric to keep up with the competition and survive. The better a bank knows its customers, the better it can anticipate the products, services and actions that will create a positive and profitable customer relationship. Done right, you can serve customers better with an understanding of their customers’ behaviour and patterns using predictive analytics.
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