Portfolio Analytics

Overview

In this digital age, delivering a personal banking experience that differentiates and drives more business is going to take data.

However, the data that banks and credit unions require to personalize the experience typically resides in disparate systems, each serving only one specific delivery channel.

As long as this data remains siloed, it will be extremely difficult to provide a superior and personalized banking experience.

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Project goal

Our vision for Portfolio Analytics was to be the tool for Relationship Managers to use when dealing with customers.

We did not want to offer an exhaustive list of irrelevant data, rather wanted to focus on the most critical indicators that are deeply personalized to the customers' needs.
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Goal 1:
Leverage advanced analytics, machine learning and contextual engagement to provide a highly personalized experience by delivering uniquely personalized product offers.

Goal 2:
Increase retention by identifying and targeting clients exhibiting attrition risk behavior. Minimize channels cost by identifying and incentivizing activity with lower-cost channels.

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Research

I partnered with a product owner and a business analyst to uncover insights and translate concepts into features that address customer behavior and motivation.
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I talked to a number of Relationship managers at the local banks to understand their current process of offering personalized offers and how they would leverage our product in their day-to-day activities. I also did competitive analysis on similar products.

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Analysis

My research helped me to understand the perspective of financial institutions as well as their customer expectations when it comes to dealing with personal finances. I defined the product with my project partners. I evangelized customer goals and balanced business goals. I prioritized and negotiated features for the initial launch and later releases.

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Ideation

I performed a hierarchical card sort with 10 participants. My aims were to understand how bankers thought about different categories of content and what was most important to them in the context of customer relationship.
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An equally important design challenge was building effective features, some of which were test scenario engines that would handle large amounts of data in order to provide RMs with the most appropriate course of action.

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Validation

Getting the right data in place was only half the battle, I still had to manage the experience without overwhelming users with so many steps required to complete a single task. I worked collaboratively with end users and the team, tested prototypes constantly and iterated progressively.

To test the design, we had a small group of local relationship managers and bank managers who were willing to participate.

Reflection

There needs to be a shift of focus away from simply selling products towards providing relevant and contextual financial advice — in other words, banks need to demonstrate genuine interest and commitment to the customer’s financial wellbeing.

Since the launch, Portfolio Analytics helped retail banks to overcome the data silos and see through the overall customers' activity from 360 degree perspective. It helped them make customer centric decisions, design focused approach towards cross-sell/upsell and attrition. All of this resulted into a better customer retention and satisfaction.

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