September 16, 2024

Setting the tone for a personalization strategy in the banking sector

Assessing maturity and defining a strategic roadmap for Data & Analytics in mass-market retail banking

Setting the tone for a personalization strategy in the banking sector

At a glance

Challenge

In private and corporate banking, personalized service is crucial. With the growth of mass-market retail banking, banks aim to scale personalized service. Our client sought a data strategy roadmap to leverage advanced analytics for a data-driven, tailored approach, transitioning from descriptive to predictive and prescriptive analytics to drive decision-making and boost market share growth.

Solution

Individual interviews and workshops were conducted with stakeholders to understand the bank’s strategy and objectives. Key issues such as communication, governance, data quality, and literacy were identified. Initiatives were prioritized into three strategic axes: commercial precision, hyper-personalization, and efficient processes.

Results

Over three weeks, an analytics roadmap was developed to address foundational challenges. Key initiatives included creating a rebranded Data & Analytics team, mandatory training for executives, and a task force for data quality. Expected outcomes include a 17% increase in client acquisition, 8% rise in average revenue per client, and a 2% increase in total sales, contributing to a 12% revenue growth over three years.

Challenge

In private and corporate banking, personalized service is crucial. With the growth of mass-market retail banking, banks aim to scale personalized service. Our client sought a data strategy roadmap to leverage advanced analytics for a data-driven, tailored approach, transitioning from descriptive to predictive and prescriptive analytics to drive decision-making and boost market share growth.

Approach

Solution

Individual interviews and workshops were conducted with stakeholders to understand the bank’s strategy and objectives. Key issues such as communication, governance, data quality, and literacy were identified. Initiatives were prioritized into three strategic axes: commercial precision, hyper-personalization, and efficient processes.

Results

Over three weeks, an analytics roadmap was developed to address foundational challenges. Key initiatives included creating a rebranded Data & Analytics team, mandatory training for executives, and a task force for data quality. Expected outcomes include a 17% increase in client acquisition, 8% rise in average revenue per client, and a 2% increase in total sales, contributing to a 12% revenue growth over three years.

Our
AI-generated
summary

Our AI-generated summary

Our AI-generated summary

In private and corporate banking, a premium personalized service is the norm. With a limited clientele, there is a unique opportunity to establish personal relationships and tailor the approach to each client’s specific needs and preferences.

As the mass-market retail banking sector expands in emerging countries, banks feel the need to adapt their commercial strategies to follow high standards of bespoke service also in this segment. They see the possibility of personalized service at scale as an opportunity to differentiate themselves from the competition.

To remain competitive in this evolving scenario, our client recognized the role that data intelligence could have in guiding decision-making processes and allowing a personalized approach. This recognition led them to seek a recommendation for a data strategy roadmap that maximized the potential of advanced analytics initiatives and surpassed competitors in market share growth.

Our challenge was to guide the bank’s transition from a purely descriptive mindset to advanced predictive and prescriptive analytics, empowering all teams with the necessary tools to make data-driven decisions.

To gain a comprehensive understanding of the bank’s operations, the first step was conducting individual interviews. These interviews took place to understand in detail the bank’s overall strategy, the data strategy in place, and the level of analytical maturity. Participants in these interviews ranged from members of the Executive Committee to key stakeholders across the various business sectors, as well as the heads of data departments. This approach ensured that we captured diverse perspectives from within the organization, enabling us to form a holistic view of the bank’s operations and objectives.

After consolidating the valuable insights gathered from these sessions, we moved on to the next step: co-creating data & analytics opportunities. Four workshops were conducted focusing on distinct core areas of the bank: Operational Efficiency, Customer Centricity, Product Strategy and Client Acquisition & Onboarding. The participants included business stakeholders and members of the data team who collaborated in heterogeneous groups, tasked with identifying challenges that could be addressed through advanced data and analytics initiatives. Each workshop started with a short inspirational talk, followed by brainstorming and the election of the ‘champion’ initiatives.

As the workshops were taking place, we had the opportunity to take part in the group discussions that brought to light the main pain points of the bank and the areas of misalignment between business and data teams. Key issues related to communication, governance structures, data quality, and data literacy emerged as fundamental challenges requiring attention to strengthen the bank’s foundation as a data-driven institution.

After the workshops, the best initiatives that came up were refined and prioritized according to the strategic objectives of the bank, the effort needed and the value derived. They were clustered into 3 main strategic axes: commercial precision, hyper-personalization and efficient processes.

By the end of the three weeks of close collaboration, we were able to determine the analytics roadmap as well as a set of parallel initiatives aiming to tackle the issues in the bank’s foundations.

Our AI-generated summary

Our AI-generated summary

Within the governance category, the creation of a rebranded Data & Analytics team was suggested. Our recommendation emphasized embedding this team within a more business-centric framework, to bridge the separation between business objectives and data strategies. Additionally, we proposed mandatory training sessions for business executives and the formation of a dedicated task force to ensure data quality.

Initiatives within the second and third groups were divided into short-term (less than 4 months) and mid-term (less than 12 months) priorities, to provide clear guidance for the bank’s immediate course of action.

A significant impact is expected from the implementation of these initiatives, including a 17% increase in client acquisition rate, 8% increase in average revenue per client and 2% increase in total sales. This adds up to an increase of around 12% in total revenue over three years.

The project resulted in concrete initiatives that could be split into 3 groups: governance changes, people & data enablers, predictive and prescriptive analytics initiatives for an AI-driven bank.


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