Related Posts about : banking-financial-services

Most technology leaders have a plan for technical debt. They track it, budget for it, and report on it as part of ongoing modernization. Far fewer have a plan for a quieter risk that starts long before a single line of code is written: requirements debt. Requirements debt accumulates when assumptions replace clarity, when conversations […]

AI often gets talked about as something for big companies with technical teams. Saima Malik, AVP of Enterprise Process and Automation at TD, argues it belongs to every single person, and that the five skills that matter most for AI are ones people already have. She has spent more than 25 years in digital technology […]

AI removed the capacity constraint on software delivery and exposed the governance one. In financial services, the specification is now the control point that decides whether velocity compounds value or risk. Delivery is still breaking down, and the reason is no longer engineering capacity. Timelines slip. Audit evidence gets assembled by hand in the days […]

Seventy percent of banking technology spend goes to keeping existing systems alive. AI-assisted engineering is how that ratio finally changes. Every bank and insurer is running the same arithmetic. Customer expectations move in weeks. Regulatory change arrives on its own schedule. The core systems that process the money were written decades ago in COBOL, and […]

Financial institutions are not constrained by how fast they can build. They are constrained by how much change they can absorb without destabilizing critical services. Financial institutions have spent the past decade accelerating delivery. Continuous integration and continuous delivery are in place. Automation keeps improving. AI is now entering engineering workflows across customer engagement, operations, […]

Only 11 percent of financial firms report measurable ROI from AI. In 2026 the binding constraint is not model quality. It is the governed data foundation underneath the model. The 2025 AI experiments were necessary. Most of them did not move a balance sheet. Boards funded generative and agentic pilots on the promise of transformation […]

More than 80 percent of AI initiatives collapse, and it is almost never the model that fails. It is the governance around it. The number that should concern a financial services board is not an adoption statistic. More than 80 percent of AI initiatives collapse, a failure rate nearly double that of traditional IT projects, […]

Sixty-six percent of banks still report data quality problems that reach the bottom line. In a market moving at the speed of AI, data strategy has stopped being a technology program and become a growth decision. Financial institutions have spent a decade investing in data. Warehouses, then lakes, then platforms, then dashboards. Yet ask a […]

Financial institutions are not failing at AI because their models are weak. They are failing because nobody owns the decisions those models now make. The budget was approved. The pilot worked. The board saw the demonstration and asked when it would reach customers. Then the value disappeared somewhere between proof of concept and production, and […]

Canada’s banks have already won the digital adoption argument. The next decade will be decided by four things they do not yet fully control: experiential banking, open banking, generative AI, and the mega platforms they increasingly rent capability from. The Canadian banking sector is at a crossroads. On one hand, it holds a global reputation […]