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The Strategic Analytics Unit and Customer Retention

Dunia was active in customer reward and progression and relationship deepening with activities such as credit card limit increases and cross-selling of other financial products. The cross-selling approach was used for existing customers and was similar to the frequently heard “Would you like fries with that?” at fast-food restaurants in the United States. Essentially, cross-selling was the strategy of selling multiple products to existing customers so that their balances (and Dunia’s earnings) increased. The strategy was beneficial in two ways: The opportunity to cross-sell increased the lifetime value of the customer, and known customers were less risky because Dunia had data on their behavior. The Dunia system was set up to identify customers it could generate a profit from yet be nimble enough to take appropriate corrective actions if actual performance varied from expectations. Overall, cross-selling was less risky than acquiring new customers, required less investment to maintain, and increased probability of customer retention.

From a risk management perspective, determining which customers were eligible for cross-selling was the credit department’s responsibility; once customers were cleared by that group, SAU could target them. SAU had the technical tools and historical performance, and DWH could therefore perform robust targeting.

To facilitate this approach, strong analytical capabilities were required in the form of three key elements: people, system infrastructure/technical tools, and accurate data. Dunia SAU scored high on all three counts.

Hurbas reported to Kakar (see Exhibit 2-4), ensuring independence of the critical analytics function. In most other banks and financial institutions, analytics would be a part of the credit function and called “Credit MIS,” or would exist partly within marketing, finance, or IT. All analytics team members who dealt with data were gathered under one roof at Dunia, ensuring not only a single source of data—or “source of truth”—but also a broad exposure to the same team of people who handled data across all aspects of the business, as opposed to preparing reports on a one-dimensional basis within a narrow focus on a single functional area. Kakar and the rest of Dunia’s senior management were the biggest supporters of analytics and promoted a culture of analytics-based decision-making throughout the organization, making analytics a part of Dunia’s DNA.

To ensure that the SAU stayed sharp, Hurbas hired the team carefully. He looked for individuals who were either fresh from top schools around the world or who only had a few years’ experience—always with a strong programming foundation and quantitative abilities—who also demonstrated in-depth business, financial, product, and process understanding. Because individuals bearing all of those skills were scarce, talent was incubated through senior-level, cross-functional interaction with many other departments, where training cut across various disciplines, such as finance, marketing, operations, IT, and sales.

Nesimi Monur, an industrial engineer, was Hurbas’s first hire. Gauri Sawant and Ram Naveen joined the SAU team later on with IT and consumer finance backgrounds, respectively. More recently, Hurbas hired Maksym Gadomsky, who had an applied mathematics degree; Cagatay Dagistan, who had a master’s in industrial engineering; and Sahil Kumar, a computer engineer with an MBA. This diverse and eclectic team helped bring added breadth, which made analytics-based decision-making more meaningful.

Parallel to Dunia’s growth, the analytics function, which was one of the firm’s key growth engines, was expanding. By 2012, the core SAU team was seasoned, scalable, and ready to take on more people and train them on the analytics tools and techniques, as well as on the business processes such as cross-selling.

Any customer who had previously opted out of all promotional offers was excluded from cross-sell efforts. For each product, a list of eligible customers would be extracted using behavioral criteria (for example, past delinquency incidence). Pricing and loan quantum would also be driven by SAU segmentation.

Credit card usage patterns, for example, provided a wealth of information. Every instance of a customer’s credit card swipe could provide valuable insights about the customer’s lifestyle and life stage and offer pointers for understanding customer needs and preferences. That way, Dunia could tailor appropriate products to meet these needs and preferences, in line with the principle of customer centricity. Dunia SAU was instrumental in taking this volume of data and extracting meaningful intelligence about the client. Dunia could offer solutions for problems customers did not know they had (for example, a new home loan may coincide with moving expenses, a hotel stay, or household furnishing purchases).

The process of contacting customers was a strategic decision, and each combination carried a different cost (Table 2-3). Efforts were made to maximize the customer response, yet Dunia was mindful not to contact a customer too frequently. Telesales calls did not exceed three per customer. SAU would give the validated list to call center agents for action.

Table 2-3 Channel Choice Cost Sample

Channel Choice

Cost (UAE Dirhams)

Cost (U.S. Dollars)

E-mail only



E-mail + 1 call



E-mail + 2 calls



E-mail + 3 calls



Source: Dunia. Used with permission.

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