“Cross-functional meetings can easily devolve into data knife fights if teams look at or interpret the same data through different lenses,” says Ali Yaakub, Head of BI and Analytics at Tamara. Datatechvibe spoke to him about speaking the same data language so that fraud risk, credit decisions and customer experience teams can get what they need from the data
How do you deliver exceptional customer experience while securing business objectives?
“We have implemented a decision engine that is not only fast but also scalable and reliable, even during peak traffic periods. Our aim is to provide an exceptional customer experience while maintaining a positive repayment record in the books,” says Ali Yaakub, Head of BI and Analytics at Tamara.
Tamara, the shopping and payments platform in Saudi Arabia, understands the power of data-driven insights in navigating key risk areas such as credit and fraud while simultaneously delighting customers.
Excerpts from the interview;
What advice would you give business leaders to work with cross-functional teams to create access to insights for different business use cases?
Cross-functional meetings can easily devolve into data knife fights if teams look at or interpret the same data through different lenses. Weeks can be wasted simply trying to understand how each team arrived at their numbers and why those numbers differ from those presented by another team. To mitigate this, ensuring that all teams are on the same page regarding which data to analyse and what the data signifies is crucial. While there may be multiple versions of the truth, each version should be documented in a format that is accessible to all teams. Establishing robust data governance practices is fundamental to the creation of meaningful insights.
Once the foundations are in place, the next step is to make the data explorable and accessible to all teams. Empower teams to examine the data from their unique perspectives and engage in discussions based on their findings. It is important to resist the temptation to jump to conclusions and search for evidence in the data that confirms preconceived beliefs. To mitigate this, it is essential to separate observations from inferences. A recommended process is to start with clear business objectives, outline one’s understanding of the current situation, and identify expected observations in the data. Next, gather and visualise the data, and compare it with the earlier list of expectations. If discrepancies arise, conduct further analysis to understand the reasons or revise the understanding of the situation. This process should be repeated as necessary.
How do you use data and analytics for controls around key risk areas?
In Tamara, a critical area of concern is undoubtedly credit and fraud risk. With millions of dollars in loans being issued daily, the potential for giving away free money is a looming threat if we lack adequate monitoring and controls. To effectively monitor these risks, we require a robust data architecture that can provide real-time or near-real-time insights into customer onboarding, purchase behaviour and transaction origins. Our system is equipped with proprietary rules and flags that promptly generate alerts in case of any anomalies, allowing us to investigate further.
In addition to fraud risk, credit decisions also need to be made swiftly, as the time between customer signup and online checkout can be a matter of seconds. As we are aware, faster and smoother experiences in the ecommerce sector generally result in higher conversion rates. Therefore, we have implemented a decision engine that is not only fast but also scalable and reliable, even during peak traffic periods. Our aim is to provide an exceptional customer experience while maintaining a positive repayment record in the books.
Can you give us an example of how you use analytics to inform business decisions and product developments?
A key aspect of fostering a data-driven organisation is the establishment of meaningful Key Performance Indicators (KPIs) that accurately reflect our business objectives. These KPIs undergo a rigorous and ongoing evaluation process to ensure they capture what we are striving for and serve as reliable measures of our progress. Each department within the company is then assessed on a recurring basis using department-specific KPIs. Our esteemed data team ensures the data’s accuracy, consistency, and timeliness in these evaluations. The insights derived from this data drive various business decisions throughout the organisation.
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