Technical debt is a well-known problem in the software world, but it is becoming more and more of a priority for banks, particularly banks undertaking a cloud transformation. Deciding what to do about technology debt usually involves looking at the trade-offs between different approaches.
What is technology debt?
Technological debt occurs when:
1. Software products are released before they are fully debugged and do everything they were intended to do, with the intention of getting them up and running quickly and fixing minor issues later; either
2. Software becomes outdated and doesn’t work well with more advanced systems, so “quick and dirty” workarounds are implemented to avoid starting from scratch with a newer version. Software that is not actively managed can quickly rack up this type of debt.
When comparing technology debt to financial debt, you can imagine faulty or outdated code as the principal that must be paid off eventually. Tech debt is interest, the escalating cost of working on and fixing old code, which keeps piling up as you delay payment. The longer you wait to pay off your debt, the more you’ll end up paying in the end.
Banks know they need to regularly update their technology, but because they must do so without taking their system offline, it’s a complex process and the costs can be enormous. A major upgrade not only costs money, but also personnel, time, and focus, all of which are in short supply at many banks. As a result, they tend to put off these necessary updates for as long as possible. Many banks prefer to prioritize developing new products that can generate revenue quickly, rather than spending time and money fixing the problems that cause technology debt. In the meantime, they make do with their old systems or fix them with workarounds.
The cost of tech debt
We surveyed 148 banks migrating to the cloud on how product debt/tech debt affects them.
What happens when banks accumulate technology debt?
The longer technology debt is allowed to accumulate, the more expensive and complicated it will be to correct. Additionally, as technology debt spreads across various systems and business units, the business becomes less competitive, slower, and more vulnerable to security risks.
Some of the main problems that can arise with technology debt include:
Inhibited innovation and new product development: Tech debt leaves the bank’s developers without the latest tools to create cutting-edge products. It also slows down the product cycle because legacy code is likely to create bugs and make robust testing difficult.
Customer dissatisfaction: When technology debt affects customer-facing products, such as mobile banking apps, customers may be unable to complete their transactions or find the app too slow. Back-end technology debt can also cause customer frustration by slowing down the processing of credit applications and other time-sensitive bank operations.
Balloon flight costs: When software maintenance costs are not regularly budgeted for, the result is a much higher one-time expense when all this work must be done within a year’s budget, perhaps with great urgency.
Security risks: Banks know that constant vigilance is required to keep their data and systems safe from cyberattacks. Code that is gradually patched over time (or worse, ignored) can make a bank more vulnerable to attack.
Loss of talent: Banks with significant technology debt create a more challenging work environment, both within your DevOps team and across the bank. Developers are less likely to be drawn to a workplace with outdated and buggy software, because they will spend more time fixing problems than working on exciting new projects. In other parts of the bank, poorly functioning systems are likely to frustrate staff and accelerate burnout and turnover.
Can banks use AI to fight tech debt?
“The true holy grail in banking will be the use of generative AI to radically reduce the cost of programming while drastically improving the speed of code development, testing and documentation.”
– Mike Abbott, Accenture Global Head of Banking
Generative AI is shaking up many business functions and software is no exception. In 2021, GitHub Copilot was released as an AI-assisted tool for writing code. Amazon has since followed suit with its own tool, CodeWhisperer. With these tools, some development teams have substantially reduced the time it takes to generate new code by having the AI generate the first draft. In a GitHub experiment, coders using Copilot completed a programming task about 55% faster than coders without Copilot. While programs will still need to be reviewed, debugged, and tuned to fit the exact user requirements, the initial time savings could reduce the investment needed to address technology debt and speed up timelines. However, questions remain about who owns the AI-generated code and about liability related to bugs that affect the end user. Gen AI coding tools can be a cheap way to get a lot of work done, but as with any new software, the resulting code should always be carefully reviewed and tested before implementation.
What can banks do with their technology debt?
Many banks now face significant levels of technology debt, which has become increasingly apparent as those banks orchestrate their plans to move operations to the cloud. Banks generally view their options as a trade-off between two priorities:
1. Prioritize modernization paying off your tech debt ASAP so they don’t bring it to your new cloud infrastructure.
2. Prioritize speed in the cloud Temporarily moving your tech debt to the cloud so it doesn’t slow you down.
Let’s look at the advantages and disadvantages of each approach.
Prioritizing modernization: benefits
- Tech debt is fully paid off so the bank can start from scratch.
- The bank gains the tools to be more innovative and bring cutting-edge products to market faster.
- Banks can build a better defense against security breaches because legacy software is removed.
- The bank can attract the best talent because they will work in a debt-free cloud environment that supports greater agility and innovation.
Prioritizing modernization: drawbacks
- Clearing technology debt can significantly slow the progress of a cloud migration because more work needs to be done up front.
- Modernizing all at once will increase the initial expense of cloud migration.
- This approach can increase the number of disruptions, or perceived disruptions, during the migration because legacy systems will be gone. Training and upskilling of staff will be more critical.
Prioritize speed: benefits
- The bank can realize the value and cost savings of the cloud more quickly.
- Cloud-only applications can be deployed earlier.
- The flexibility and scalability of the cloud will become available to the bank as it addresses technology debt.
- Current staff will have more time to adapt and improve their skills.
Prioritize speed: drawbacks
- Tech debt continues to accumulate longer, increasing the overall cost of addressing it.
- The bank can migrate problematic software, such as programs with security vulnerabilities, to its cloud-based systems.
- Older software and applications may not work as well within the new cloud framework.
What approach should your bank take?
There is no single solution to technology debt. Instead, it is critical to understand the trade-offs and how they affect the bank’s business objectives. Tech debt conversations should be part of any cloud strategy planning.
We work with banks to determine the extent and cost of their technology debt, which features can most easily be upgraded and moved to the cloud, and how to resolve their remaining technology debt so they can meet their cloud migration goals.
To discuss your bank’s technology debt and how to address it during your cloud migration, contact me. To learn more about the many factors to consider during your bank’s cloud journey, be sure to keep reading our latest research on the banking cloud altimeter.