Customer Experience 2020: The Emergence of the Autonomous Financial Institution

In the age of self-driving cars, additive “3D” manufacturing processes, and self-flying delivery drones – how can Financial Institutions capture similar opportunities enabled by continual advances in sensors, artificial intelligence and autonomous process automation?

Financial institutions need deep analytics solutions that:

1.  Start by allowing the definition of the desired business goal like growing market share, decreasing customer churn, increasing profitability – or even simultaneous combinations of these strategies.

2.  Use Artificial Intelligence in a self-learning mode, to continually optimize to the desired goal.

3.  Combine Machine Learning and AI algorithms with effective data management – all linked with opti-channel delivery channels. This gives FI’s the ability to execute sophisticated, automated marketing and customer management programs, with few manual processes and minimal human intervention.

4.  Take advantage of more and more value-creating opportunities (sales, marketing, financially accretive service interactions), to be more responsive to changes in the market place, and to significantly reduce marketing expenditures.

To achieve Customer Experience 2020, FIs need to:

  1. Develop insights faster and be smarter about prioritizing their customer interactions to achieve their financial and other goals…
  2. Act on those insights right away and be more responsive to changes in the marketplace – beating competitors to market opportunities…
  3. Automatically learn from the insights and be more efficient and operate more effectively at the lowest possible cost levels…

To learn more about Customer Experience 2020 and automated FI’s download our full white paper on our main website.

To learn about RedPort’s deep learning analytics technologies click the links below:

SmartBanker: Self-Learning analytics and marketing platform for banks, credit unions and consumer lenders.

SmartInsurer: Self-Learning analytics and marketing platform for insurance providers.

Analytics: Strategy or Tactic?

You can hardly go anywhere or read anything anymore without hearing or seeing something about Big Data. People who aren’t in banking, insurance retail, or consumer marketing could be forgiven for thinking Big Data is like the second coming of Godzilla or something: “Big Data. It’s Everywhere!” But while high-consumer-based merchandisers have been building their businesses around data for quite some time, financial-services operations are just starting to dip their toes in the proverbial water, relatively speaking.

We could engage in the philosophical debate about whether data analytics constitutes a strategy or a tactic. However, there may not be a right or wrong side in that debate. In fact, some organizations might choose to enjoy some of the advantages of data analytics as a tactical approach, even as they re-tool their operating models to make analytics more of a strategic underpinning. Here’s how:

  • Tactical approach: Let’s say you decide to track the performance of one particular product. Maybe it’s an insurance line of business. Maybe it’s consumer-loan offering. And let’s say you have limited tracking capabilities; but you can track the customer segment to which the product is sold, the channel through which it’s sold, the geography in which it’s sold, and the person who sold it. Just having that limited amount of information would enable you to know if the product was a potential winner or loser.
  • Strategic approach: Given what you learned from your tactical experiment, you may decide to extend data analytics farther across the enterprise — or at least beyond one department or a single line of business. At the far end of the spectrum, you may opt to aggregate and analyze data from all your core and ancillary systems and data sources to get a closer look at overall operational performance, to better understand customers, to recognize successful products, to see trends that lead to opportunities, to identify and recognize high-performing employees, to make better marketing decisions, to refine pricing, and to decrease losses and expenses.

Clichés are True

The bottom line is this: You can employ analytics productively as a tactic. Every time you do, you’ll learn something. But you’ll employ analytics more productively if you see your way to employing it as the strategic underpinning for operations and decision-making.

According to the cliché, you can’t manage what you don’t measure. And we’ll agree that there are metrics at least as important as numbers. But if you employ analytics strategically to monitor, measure, and manage all your numbers, many other metrics will take care of themselves.