Software Metrics in Banking’s Digital Transformation Journey in 2024

Published: 29 February 2024

In 2024, banks need an objective means of analysing software development efforts to truly understand the fortunes of their digital transformation journey. This requires the use of metrics throughout the code review process to ensure assessment is data-driven.

This article will take a look at key types of metrics to consider in judging the success of an ongoing digital transformation.

Beyond that, we will consider why organisations must adopt a solution to ensure those metrics can be understood, and business insights can be shared effectively.

The role of code review

In a previous article discussing digital transformation in banking, we covered the continued emphasis on cost-efficiency across the banking sector.

This is achieved in great part by the efficacy of code review practices in identifying vulnerabilities and quality issues as early as possible in the Software Development Life Cycle (SDLC).

A bug or other fault that leaves code open to malware or a data breach can have dramatic financial implications. These threats can rapidly negate the benefits of digital transformation initiatives, as well as putting the fortunes of the wider organisation in jeapordy.

If run effectively, many development issues can be ironed out in the daily standup. However, even the best of these are not without their faults, as it is usually not practical for every team to engage in thorough and objective analysis on a daily basis. 

As a result, daily standups must work alongside a code review process that employs metrics to quantify efficiency and productivity.

Key Metric Categories

Below are some of the essential metric categories banks must track to optimise their software development. Click here for specific metrics which are key to measuring success in the case of an agile transformation.

Code Quality Metrics

With cost-efficiency being a priority, ensuring code quality from the outset is critical.

These metrics assess aspects of code such as complexity, duplication, and adherence to coding standards. 

Tools capable of combining multiple metrics and performing constant static source code analysis can be utilised to streamline the code review process. BlueOptima’s Developer Analytics platform, for example, provides analysis of code maintainability and allows active management of development costs.

Developer & Team Performance Metrics 

Understanding the value delivered by a workforce is fundamental in driving digital transformation.

There are a host of metrics and KPIs that can help analyse the productivity of an individual developer team. Financial institutions can use metrics to identify their top performers. They then use that data to understand why they are top performers. They can define best practices and promote them at scale.

To demonstrate, consider the example of a major bank who used Developer Analytics to identify their best performing development team. Then apply their approach across the organisation to achieve a 30% increase in productivity overall.

Security Metrics 

With the rise of cyber attacks on banks, security metrics are a critical component for banks in their digital transformation.

These assess the effectiveness of security controls and measures protecting software systems and data. They include vulnerability assessment, incident response time and compliance.

Given the importance of a secure software estate for banks, it is not enough for it to be monitored ad hoc. Banks can adopt advanced tools such as Code Insights. They employ machine learning to avoid potential data leaks and code exposure.

User Experience (UX) Metrics 

With banks facing stiff competition and customers enjoying more choice than ever, user experience is often a deciding factor in business retention and acquisition.

These metrics evaluate usability and user satisfaction with software applications. Metrics such as user engagement, task completion rate and Net Promoter Score provide insights that can inform continuous improvement to all customer facing software.

UX metrics therefore require a central role across Engineering, Product and Design in defining and measuring success in digital transformation. 

Finding Meaning in the Digital Transformation Metrics for Banks

Banks must incorporate metrics into their code review processes. However this presents challenges in dealing with masses of new and complex data. In order to add value this information must be understood. Fortunately, solutions exist in the market that can do the heavy-lifting. 

BlueOptima’s suite of products, for example, are designed to translate complex data into relevant and meaningful insights. The Developer Analytics platform shows the productivity of globally distributed teams, while providing a unique metric (Billable Coding Effort) to standardise developer analysis. It simplifies measurements of cost-efficiency and return on investment (ROI).

Meanwhile, the Team Lead Dashboard provides managers with a practical means of promoting increased productivity and code quality.  In 2024, adopting the right metrics is a necessity in banking. The real differentiator will be in having the tools in place to unlock insights from those metrics and act upon them strategically. 

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out of 10 of the worlds biggest banks


of the S&P Top 50 Companies


of the Fortune 50 Companies