By Sam Barton, Group Technical Director, Smart
Sam Barton is Group CTO at Smart, the global retirement technology provider backed by JP Morgan, LGIM and others. Sam outlines 7 transformational trends with the power to move the financial industry forward to meet the new needs of Americans.
Just three months into the new decade, the world as we knew it has changed so much that we have all had to reinvent our daily lives, as working and learning from home has become an international responsibility. Throughout this unprecedented time, core tech workers have become the unsung heroes who have kept the lights on for the financial services industry.
For years the industry was happy to keep the hardware on-premises and the systems to support them, but a sudden loss of office staff has created an inflection point in how we interact with the systems that support our work. 2021 kicked off these initiatives in earnest, but it’s clear there’s still work to be done. So what does 2022 and beyond hold for us?
1 – Process automation vs human processes
The industry has long opted for paperless processes or screen-scraping programs that extract data from discordant systems. It’s also not uncommon to use third-party workflow tools that add automation as a veneer on systems that can’t be automated. Either way, the end result is always people driven. To be more resilient and take full advantage of the cloud-based solution, these journeys must be fully automated, including when it comes to taking advantage of customer self-service opportunities to minimize business processes.
Automation brings huge cost savings because computers run 24/7, are less error-prone, and don’t need paid time off. Yet process automation is often overlooked in the transformation project because the goal of achieving a new cloud-based solution is more visible as a deliverable. However, in order to take advantage of new real-time data and scalable solutions, automated processes need to replace the overnight batch jobs, retired on the journey to the cloud.
Likewise, when an organization builds cloud-based infrastructure, new deployment pipelines are required. Instead of a team provisioning a new server and promoting a pre-production environment to production, the same process is now written as code (Infrastructure as Code) using templates that set environment variables, the build and even the operating system of the instance. the software will be installed. Instances are created and destroyed in minutes through automated deployment processes (CI/CD) that have built-in tests to report on their performance.
As the company embarks on this transformation, it must light every funnel and ensure that every department meets the new target architecture.
2 – Economic intelligence vs artificial intelligence
All businesses rely on data to monitor various performance metrics. These business intelligence reports have always existed in one form or another, and have become “Big Data” as information has moved away from paper and has become more digital. What is new is the way this data is extracted and managed.
The artificial generation of these reports will be a high priority when the transformation projects are nearing completion. As more data is captured, BI reporting must also accelerate and old ways of inspecting data must be reinvented. For example, it is understood that fraud is best detected by machine learning tools that flag values that fall outside a defined tolerance. Moving this defined tolerance to one that is reassessed in real time by a more responsive, ML-based decision tree (AI) is a necessary step.
3 – Security by design
Each stage of the transformation journey offers a potential entry and exit point for customer data or important financial information. Much like Point BI, this data is now changing at a faster rate, which means automation is needed to scan for vulnerabilities and detect problems in real time, which includes integrating automated threat detection. in real time. We’re not going to remove these annual penetration tests, but we’ll be adding more defenses, which means the next penetration test will have less to report.
This is as much a software issue as it is a cultural one, as the software engineering mindset needs to adapt to the new architecture. The continuous integration server test suite should include security testing, and the continuous deployment pipeline should also be augmented to check for vulnerabilities. At the same time, those writing the code need new development guides that spell out best practices, and the quality engineers testing the feature need to inspect for security weaknesses while ensuring the feature meets intended business requirements. .
Security by Design is not a one-size-fits-all policy, but a cultural shift that sees a business unit take ownership of the security of its products and services.
4 – Hybrid cloud vs native cloud
To stay relevant with customers demanding a more engaging digital experience, companies have invested heavily in cloud-based technologies. But as those budgets were approved, no one thought to also transform the business processes and culture of the people who support legacy systems, creating a pair of competing political interests pulling in opposite directions. The inevitable compromise was to agree on a hybrid cloud model. Legacy administration products remained on-premises and a new cloud-based digital experience layer was introduced. It made logical sense in pre-pandemic times. But just as working from home became mandatory for the employee, the idea of a fully cloud-native solution quickly became mandatory for the business.
2021 was the year to accept this revelation, and 2022 will see the death knell for the on-premises solution. Businesses will move entirely to the cloud, not only to protect against customer migration, but also to reduce internal productivity losses and to create better disaster recovery solutions.
5 – Serverless vs microservices
Going fully cloud native is not a turnkey business. The initial attempt to simply move the on-premises software into an equivalent cloud-based machine will soon reveal incompatibilities. Legacy software was not designed to take advantage of cloud-native hardware.
Lambda functions, a product offered by AWS, allow the rapid introduction of features that do not require complex infrastructure to support them, which makes them much more agile both in delivery and in the processes of supply and approval. There is simply less for business and technology staff to review. It’s an effective way for the company to get a foothold in a cloud-native solution for the first time and is expected to see greater adoption once the precedent is set.
The concept of a service-oriented architecture (SOA) is not new, and in fact, microservices are considered contemporary in the financial industry today. But if the service is written in a way that depends on an on-premises solution, its performance is limited to the limits of that machine. By moving the same functionality to a serverless solution, a solution where the infrastructure scales seamlessly behind it, the small (micro)service scales to become serverless and the business can rightly say that it has crossed its first step on its digital transformation roadmap.
6 – Cloud Data vs. Legacy Policy Documents
By their nature, startups disrupt established markets. Project managers overseeing digital transformation for established companies share this aspiration. While it is often easy to agree on a technical strategy, the hardest part of a transformation project is less visible at the start of the project. Much like legacy software, business operations are hard-coded into policy documents and have shaped the very DNA of the company. Long-standing practices can shape everything from business processes to workplace culture. The 2020 nighttime lockdown led to a strategic evaluation of many of these policies, as operational teams suddenly had to access customer data while working from home. But while we accept this new normal, the political bandage has not yet been removed.
So, as we introduce new technologies, it is equally important to question documents that are not suitable for cloud-based solutions.
The end goal is to move customer data from on-premises hardware to a scalable cloud-based solution. Software and data can finally be brought together in a real-time solution and those overnight batch jobs are finally gone, marking another major milestone on the transformation roadmap.
7 – Responsibility and sustainability
The financial services industry is no stranger to sustainability. Clients want to ensure that their money is invested responsibly, and ESG funds are the mainstay of any wealth management product today. But while this external accreditation has been met, the new emphasis is on the footprint that the companies themselves leave behind.
Original on-premises solutions have been implemented in data centers designed to meet the demands of the busiest day of the year. But today’s cloud-based architecture can scale smartly on demand as customers rush to use the product online, and scale back again during quieter hours. using less electricity. This simple example saves money while contributing to the company’s sustainability report. The same logic applies to the whole company. Offices know when someone is working from home and turn off their workstation and associated office lights.
The aforementioned topics collectively add to a necessary to-do list for any business that has withstood the challenges of lockdown and is looking for a better set of defenses going forward. Achieving these goals brings business benefits while meeting the demands of today’s customers. This constitutes a vital evolutionary shift as the world adjusts to a post-pandemic era.