Personal Financial Management Research

A product discover case study for the Absa Mobile banking app focused on user testing and enquiry

About the Project

Understand how users currently manage their money and define the Jobs To Be Done

Evaluate Meniga technological offering and features as a partner in the Personal Financial Management (PFM) space to validate it against user Jobs To Be Done

Client

Absa

Industry

Fintech

Personal Financial Mamangement

Duration

June - October 2021

Objective

Gain insight into financial behaviour across demographics, with the aim of to inform the roadmap of the savings business'.

The Problem

Customer challenge:

The level of financial literacy in South Africa is very low. Basic financial concepts and management skills are only present within a small portion of the population.

Low financial literacy in South Africa limits the potential user base for financial management solutions. The offering risks low adoption and negative sentiment if behavioral suggestions are perceived as prying or predatory.

Technical challenge:

Personal Financial Management (PFM) solutions require deep integration with various technologies, building large-scale ecosystems, and personalized experiences to deliver real value.

Achieving this within legacy banking systems presents significant technical hurdles. The decision to either build from scratch or partner with external technology enablement partner. A choice which has risks on both sides.

Business challenge:

The bank has a predominately aging customer base. Within South Africa's population of 59.31 million, only 36% of them are active mobile internet users*, and an even smaller percentage are active ‘mobile bankers’.

To increase our customer base, we have to formulate a business case to show how targeting the younger population can be a revenue generating proposition

Research approach

Qualitative & Attitudinal interviews

Because the product demo from the tech third party used dummy data we aimed at leaning into qualitative interviews guided by different Financial events prompted by the Conceptual mockups and the web demo.

Each session was divided into two parts. Part one a usability test, and part two was concept testing with more contextual enquiry.

Participants

60 min

Session duration

R 0 - R 65K

Monthly income

18 - 50

Participants Age

Pt 1 - Evaluating usability risks
of the partner & offering

The usability test focused on how participants engaged with the 3rd-party technology, specifically how they interacted with the demo platform and dummy data.

Through qualitative questioning, we explored their mental models and attitudes towards money management, helping to identify usability risks and areas for improvement.

Pt 2 - Addressing value risk
via concept testing

We presented mid-fidelity mockups to assess user sentiment toward potential non-typical features. This helped us understand how users might respond to bank-suggested behavior changes, reducing uncertainty around feature adoption and feasibility.

Research Synthesis

Step 1:

Affinity
map

Affinity map

The first important step is Identify surface level patterns by grouping responses by common themes in responses and observations to uncover the “Stories to be told”

Step 2:

Using sentiment
as a  lens

A key outcome here was the disproving of the hypothesis that LSM grouping is not as relevant when grouping financial behaviour. Financial maturity proved to be the golden thread to our insights.

Step 2:

Using sentiment
as a  lens

A key outcome here was the disproving of the hypothesis that LSM grouping is not as relevant when grouping financial behaviour. Financial maturity proved to be the golden thread to our insights.

Step 3:

Develop Segment archetypes

We created 3 segments based on the core financial maturity and behavioural cause. This model was used to create feature based patterns and recommendations per segment. This served as our feature priority matrix.

Step 3:

Develop Segment archetypes

Step 4:

Segment lens and
PFM categories

Segment lens and PFM categories

We grouped and gathered participant responses based on feature behaviour, and on their segment, in order to guide and inform product roadmap.

Step 4:

Segment lens and PFM categories

We grouped and gathered participant responses based on feature behaviour, and on their segment, in order to guide and inform product roadmap.

Key findings

Behaviour based segments

We identified a strong correlation between financial responsibility and the perceived value of budgeting.

This insight led to the creation of three segments: Financial Dependents, Newly Independent, and Financial Providers. Tailoring solutions to these segments presents an opportunity to drive value by addressing their specific financial needs.

Value: Financial planning vs Spend tracking

For Financial Dependents, budgeting and planning tools were often misunderstood and seen as less valuable.

Instead, spend tracking was identified as a more effective tool for managing their money. This suggests that a shift toward simpler spend-tracking features could enhance usability and value for this segment.

Value: Financial planning vs Spend tracking

For Financial Dependents, budgeting and planning tools were often misunderstood and seen as less valuable.

Peer comparison as
a financial benchmark

Peer comparison as a financial benchmark

Participants had mixed feelings about being compared to peer data. However, when this comparison was paired with a challenge to improve their finances, users responded more positively.

This opens up an opportunity to integrate peer comparisons as part of a gamified financial challenge, potentially increasing user engagement and value perception.

Peer comparison as
a financial benchmark

Participants had mixed feelings about being compared to peer data. However, when this comparison was paired with a challenge to improve their finances, users responded more positively.

This opens up an opportunity to integrate peer comparisons as part of a gamified financial challenge, potentially increasing user engagement and value perception.

What I learned

Personal Financial Management (PFM) represents a significant, underserved opportunity in FinTech due to its complex ecosystem requirements and sophisticated data processing needs.

However, relying on a third-party "black box" solution for intelligence and data processing poses a substantial risk. While it may offer short-term benefits, it could severely limit future innovation and create a strategic bottleneck if we lack transparency into the data and resulting insights.