David Robertson, Director of Enterprise Structure, Exeter Finance
In an interview with CIOReview, Mr. David Robertson, Director of Enterprise Structure at Exeter Finance, discusses the challenges and rising traits on the planet of bespoke software program engineering, sharing his insights into successfully navigating them.
David Robertson is the Director of Enterprise Structure at Exeter Finance, the place he leads innovation in cloud-native platforms and automation in bespoke and AI integration. With a robust deal with scalability, safety, and effectivity, David makes a speciality of integrating AI, DevOps, and sustainable automation practices. He brings a long time of expertise in driving innovation, enhancing engineering excellence, and aligning expertise technique with enterprise objectives to ship measurable, long-term worth.
Present Position & Duties
I function the Director of Enterprise Structure at Exeter Finance, a premier auto finance firm. My crew is answerable for constructing and automating the bespoke techniques that run crucial elements of our automotive lending enterprise. The techniques we assist are tailor-made in-house—designed to satisfy the corporate’s distinctive wants and to evolve as these wants change.
The core focus of my position is figuring out alternatives to reinforce effectivity, scalability, and resilience. A good portion of our efforts is devoted to lowering the guide and repetitive features of platform growth and deployment. By automating these areas, we allow our groups to commit extra time to high-value work, together with crucial problem-solving and knowledgeable decision-making that straight impacts the enterprise. Extra lately, we’re additionally exploring how generative AI can improve our platforms as an embedded functionality that provides worth inside the techniques themselves.
Challenges in Bespoke Improvement
One of many constant challenges in bespoke software program engineering is safety. The problem is especially urgent when organizations aren’t simply integrating third-party instruments however constructing software program from the bottom up. Past assembly purposeful necessities, the software program have to be safe and performant by design.
To handle this, we’ve built-in automation into our safety workflows. This helps mitigate dangers with out requiring each crew member to be an professional in each safety element. Automation acts as a bridge, filling information gaps and imposing consistency, which permits us to remain targeted on delivering the options and capabilities the enterprise really wants.
The Worth of a Studying Mindset
A number of years in the past, my crew and I have been tasked with one thing fully new for the group: constructing a customer-facing software within the cloud. On the time, this was a major departure from our conventional method, which relied closely on non-public knowledge facilities. We have been ranging from scratch—new structure, new instruments and restricted inner expertise with cloud-native growth.
The training curve was steep, however the realization got here rapidly that automation could be the important thing to scaling effectively. We developed tooling to automate infrastructure provisioning, software deployment and testing processes. This allowed us to streamline the complete growth lifecycle—from spinning up environments to publishing modifications—without having to create a number of groups to handle every step manually. By embracing automation early, we are able to speed up supply and set up a basis for long-term agility and operational effectivity.
Imaginative and prescient for the Future
AI continues to dominate headlines, however the focus is shifting from novelty to sensible software. Reasonably than treating AI as a standalone characteristic, the objective is to embed it as a core functionality or one other software within the engineering toolkit used to unravel current enterprise challenges extra successfully. Over the following 12 to 18 months, the main target will probably be on purposeful integration slightly than experimentation.
There may be additionally a rising array of AI instruments designed to spice up productiveness, corresponding to copilots, digital assistants, and clever automation. These can ship significant positive aspects, however their effectiveness is dependent upon how nicely they align with current workflows and enterprise goals. Success will come from deploying AI with clear intent and measurable outcomes.
When evaluating AI instruments—whether or not off-the-shelf or custom-built—it’s price contemplating extra than simply options and performance. Governance, threat, and safety ought to be entrance and middle, particularly when working with delicate knowledge like buyer information or proprietary enterprise info. Understanding the place knowledge is saved, the way it’s processed, and the way lengthy it’s retained is crucial.
On the expertise facet, long-term viability issues simply as a lot as short-term efficiency. Some instruments could also be closely marketed however face regulatory uncertainty or lack monetary stability. Taking the time to evaluate the platform’s maturity, funding sources, and compliance posture will help keep away from surprises later. The objective isn’t simply to undertake AI—it’s to embrace it responsibly.
