White Papers

Banking, financial services, and insurance (BFSI) institutions are servicing their customers across multiple channels. Customers expect the experience across all the touch points, including online, app, IVR banking, in-person banking, and personal banking among others, to be not just seamless but also highly personalized.

In India, despite the introduction of digital services, millions of customers still visit bank branches to carry out different types of transactions that include withdrawing or transferring funds, updating their passbooks, opening a fixed deposit or trading account, or taking a loan. On the other hand, digital transactions through online and banking apps are gaining significant traction, with millions of consumers from diverse demographics purchasing goods and groceries through digital wallets across physical stores, ecommerce sites, and other shopping apps. Many more customers are buying or selling securities and bonds online, and even paying utility bills through the banking apps. Interacting with these hundreds of millions of diverse customers is a difficult proposition. Banks often find it difficult to understand and anticipate the unique needs of their customers, who are becoming all the more selective and demanding when it comes to the level of service they expect and the satisfaction they derive from their banking experience.

Key Takeaways:

• Understanding Customer Data & Challenges
• Customer Preferences
• Moving beyond Siloed Systems
• Predictive to Prescriptive Analytics

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Predictive Intelligence, if and when applied to the entrepreneurial arena, helps companies amplify the ROI and improve additional sales. With businesses primarily focusing on growth, it is important for them to offer personalized customer experiences for improving the ROI. PCI, therefore, leverages this essential business requirement and amalgamates existing data sets with a host of external tidbits; precisely for automating the entire process of analysis.

In a nutshell, Predictive Intelligence applied to the customer oriented sphere, helps companies preempt the customer profile creations, according to company requirements. Once created, the profiles can be used for gauging scopes of overall engagement, buying patterns and overall customer behavior

Banking organizations have taken the concept of Predictive Customer Intelligence to a whole new level. However, the ways PCI tools function have actually helped the entire BFSI sector maximize the world of possibilities associated with the same.

In a nutshell, PCI benefits are increased exponentially as they have helped enterprises combat challenges that were previously mentioned in the discussion.

IBM PCI plays a pivotal role in this discussion as it helps identify optimized customer interactions, acts on the subsequent predictions, segments the customer base according to the lifetime value and even assigns necessary marketing campaigns for select audience bases.

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There are differning views about AI and its usefulness. At one side is entrepreneur Elon Musk who has warned that artificial intelligence could become humanity’s “biggest existential threat.” At the other side is the more optimistic view of futurist Ray Kurzweil who believes that AI can help us make “major strides in addressing the world’s major challenges.”

The truth is, it all depends on how we manage the transition to an era of AI, and how we choose the impact of AI in our lives. To fulfil the promise of AI as a new factor that can reignite economic growth, relevant stakeholders must be thoroughly prepared—intellectually, technologically, politically, ethically, socially—to address the challenges that arise as artificial intelligence becomes more integrated in our lives. The starting point is understanding the complexity of the issues.

Nonetheless, the spread of AI will be limited to useful applications unless and until we can build systems that people bond with and want to have as part of their lives. Once we can build such systems-which must necessarily be able to understand human motivations, needs, and tastes-people will readily spread AI.

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The landscape of customer engagement is changing rapidly. That is largely because the customer has changed, due to the choices, options, information and connectivity, that the web has bestowed.

The expectations of the customer have changed – she expects businesses now to know what she wants, when and where. She wants her purchasing to be pre-empted with personalized communications and offers that she is really interested in. ‘One size fits all’ customer engagement approaches will not do anymore.

This calls for an investment from businesses into a new strategic approach to customer engagement, one that is the built on a revolutionary new customer data ecosystem and customer engagement framework.

Predictive Customer Analytics is the solution and the way forward for businesses and marketers,looking to maximize their customer lifetime value returns.

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