How can Banks accelerate technology and optimize productivity?

Banks today are implementing many digital initiatives to improve processes, automate internal operations and enhance customer experience. The application of advanced technologies such as artificial intelligence (AI), big data and automation not only helps optimize costs but also creates sustainable competitive advantages.

Make the most of your technology investment

For many organizations, technology costs including human resources, hardware, software and services often account for the majority of the budget. However, this is also a "black box" for them. Although they know how much money they have spent and whether projects are completed on schedule, they lack insight into the performance of their technology teams and do not fully understand the productivity levels of their teams or whether their investment in improving work efficiency is bringing real value.

When companies measure productivity, they focus on identifying areas where they can improve the speed and accuracy of engineering processes, and finding effective ways to foster innovation. By helping engineering teams work smarter, leading organizations have significantly increased their technology capabilities without increasing their budgets, creating a clear differentiation from the average organization.

Four Key Steps to Improving Engineering Productivity

By measuring engineering productivity beyond just focusing on costs, leaders begin to ask how they can improve productivity measurably, evaluate the ROI of different strategies, and explore how to create a virtuous cycle where better work environments attract talented engineers. To boost technology team productivity, bank leaders can implement the following four strategic steps.

1. Streamline the software development lifecycle to achieve technical excellence

Sometimes executives are surprised by the amount of manual effort that technology teams put into software development. For example, at a large bank, a software developer had to start by sending out requirements to multiple teams to set up their work environments. Once coding was complete, they had to perform extensive manual testing, as automated tests only covered a small portion of the cases. Additionally, other teams would have to perform additional integration and security testing, but only for a limited amount of time.

The software deployment process required approval from multiple individuals and committees. After deployment, the application was handed off to the IT operations team, which required a complex handover process. Each team had control over only a small portion of the overall process. However, instead of automating and optimizing this process, banks are hiring additional project managers and test engineers to handle the workload, increasing the cost and complexity of the process.

2. Implement AI across the entire product lifecycle

AI-enabled software development tools are gaining traction because they save time and automate many processes. Many organizations have experimented with generative AI tools to speed up the coding process. However, scaling these tools faces several challenges, including change management, limited adoption, and tools that do not align with the organization’s coding standards.

Some advanced organizations have implemented generative AI in a different way, making it available to all members of the development process, not just programmers. They also focus on change management and invest in customizing the generative AI tool to their code base. As a result, these banks see a 20-30% increase in productivity thanks to genomic AI, with the tool integrated into every stage of the product lifecycle.

3. Integrate technology and business teams

To increase technology productivity, banks need to change the way engineering and business teams collaborate. The process from ideating a new feature to starting coding typically takes three to six months. Initially, business and product teams must build a business case, apply for funding, get executive buy-in, and draft requirements. While engineers can quickly deploy code once requirements are clear, delays in this preparation phase significantly reduce productivity, as engineers wait up to six months before they can get to work.

Learning from digital natives, some high-performing banks have created joint teams of product managers and engineers (and even operations). Each team operates like a small business, with the product manager acting as CEO, guiding the team toward quarterly goals and key results (OKRs). This approach reduces the need for time-consuming handover tasks, accelerates product development, and improves customer feedback. However, many banks still maintain a traditional project-focused approach rather than a product-focused model.

4. Build Talent Teams with High Expertise

In a rapidly evolving technology environment, banks are shifting their hiring direction from maintaining large teams of less experienced employees to building smaller teams focused on highly skilled engineers with the ability to develop quality software quickly. Although the cost is high, the productivity and efficiency of these engineers is a big benefit, helping to attract more top talent. At the same time, the adoption of AI-enabled development tools also requires highly skilled engineers.

To attract and retain talent in a competitive market, banks need to improve their employee value proposition, change their recruitment process, and invest in employee development. One bank successfully created automated career paths for engineers, along with a talent accelerator program to improve the onboarding process and new hire experience. After three years, the bank’s internal engineering team grew from 30% to 70%, increasing productivity and reducing turnover.

How to Create Productivity

Many organizations struggle to measure productivity and identify actions that deliver high ROI. Engineering teams are often overwhelmed with product development, making these transformations a low priority. Organizations that are successful in focusing on productivity have something in common: early support from the CEO and board, along with five prerequisites:

(1) Vision: Banks encourage technology leaders to set ambitious goals and overcome barriers.

(2) Measurement: Defining baseline productivity and measuring improvement are essential to optimizing ROI.

(3) Business Partners: Business teams must prioritize technical transformation to achieve value.

(4) Leadership Responsibilities: Each member from the functional and infrastructure leaders to the CISO plays a role that requires close coordination. Some organizations have designated a member of the IT leadership team as a “champion,” motivating and coaching teams to effectively implement the necessary changes.

(5) Trust: Early business success is the most effective way to build trust in a productivity-focused strategy. By demonstrating positive impact in areas that business leaders care about, such as mobile applications or core data, organizations can build support and momentum for the transformation.

Once these elements are established, changes can be implemented quickly and have a significant impact without the need for complex platform changes, helping organizations increase productivity and create value quickly for businesses and customers.

Source: Mckinsay & Company

Synthesized by the author team DTSVN - Digital transformation solutions for the Finance - Banking industry.

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