Future-Proofing Finance: How Connected Skills Intelligence Can Reduce Talent Risk
The financial services (FS) industry is undergoing one of its most profound transformations in decades. Fintech startups, major technology companies like Apple and Google, and AI-driven newcomers are rapidly transforming the financial services landscape. These challengers are redefining customer expectations for faster, more personalized, and seamless financial services, pushing traditional banks to adopt AI-driven innovation – or risk falling behind.
JPMorgan Chase’s president and COO Daniel Pinto recently forecasted a $2 billion gain from AI initiatives spanning customer personalization, fraud detection, operational efficiencies, and credit decisioning. The World Economic Forum notes that 86% of employers expect AI and information processing technologies to transform their business by 2030 – rising to 97% in the Financial Services sector.
As EY puts it, AI is becoming “the linchpin of transformative change,” reshaping how financial institutions operate and compete.
But this rapid change brings a growing problem: widening skills and talent gaps. Banks face intense competition with technology companies for critical digital and analytical talent, while the financial sector’s aging workforce adds pressure: American banks are expected to lose roughly a sixth of their workforce to retirement in the next decade, with many opting for an early exit.
Why Talent Risk in Finance Is Critical (And Unique)
Ninety percent of leaders in Financial Services believe their organization needs to consider significant adjustments or total transformation of their reskilling strategy to support the future. – World Economic Forum
Financial services face unique challenges when it comes to talent. Many firms still rely on out-of-date systems (92 per cent of the UK’s financial services companies still rely on legacy technology) and traditional job structures that make it difficult to adapt quickly to changing needs.
Traditionally, hiring and career progression in FS has been based on experience, education, and job titles. However, this model often overlooks qualified candidates. Strict 4-year degree requirements – when only 40% of U.S. workers actually have one, for example – and inflexible job structures are creating a “paper ceiling”, holding FS organizations back.
Forward-thinking companies such as IBM and Accenture have begun removing degree prerequisites for many roles, widening their talent pools and ensuring that candidates are evaluated based on meaningful, measurable criteria – skills (and potential skills). Beyond filling vacancies, this approach enhances productivity, efficiency, and equity in both hiring and career development.
Changing hiring practices and adopting a skills-based approach can expand global talent pools by 6.1x – LinkedIn Skills-Based Hiring Report 2025
At the same time, fewer young professionals are choosing finance careers, even though the demand for specialized skills in areas such as compliance, risk management, data science, and cybersecurity is growing rapidly. This combination of factors has led to significant talent shortages.
“The move away from traditional job structures to a skills-based approach is an inevitable reality for the financial services sector. Put simply, there are not enough people with the right skills, which means firms need to start adapting their approach right now.” – Pete Brown, Global Workforce Leader, PwC
Without urgent action, skills gaps threaten compliance, slow innovation, and expose firms to operational and regulatory risk.
Connected Workforce Intelligence: A New Paradigm
A connected workforce intelligence approach brings together internal HR data with richer external market insights, providing a holistic, up-to-date picture of headcount, skills, costs, and the tasks driving daily work. This integrated view supports more informed workforce planning and talent decisions.
By simulating different workforce scenarios and exploring various “what-if” analyses, leaders can better anticipate the impact of organizational changes before they happen. This helps in defining optimal team structures, consolidating roles, and rationalizing tasks – critical steps in building a resilient, agile finance workforce.
For example, a bank facing new regulatory requirements can model how shifting compliance tasks across teams would affect workloads, costs, and timelines. Similarly, when introducing an AI-driven risk platform, leaders can identify analysts with adjacent skills (such as Python or SQL) that align with the system’s needs. This not only reduces training time and hiring costs, but also highlights opportunities to redeploy existing staff more efficiently.
Unlike static job titles or outdated descriptions, task intelligence breaks work down into specific tasks and the underlying skills needed to execute them. This lets organizations identify not just what jobs employees hold, but what they actually do and can do.
By integrating Talent CRMs, Applicant Tracking Systems (ATS), learning management systems (LMS), and comprehensive job architectures, firms can:
- Spot critical skills gaps and emerging needs before they cause disruption.
- Benchmark skills and tasks against external labor market data, including how competitors price key skills like AML, AI risk modeling, or sustainable finance.
- Create transparent, skills-based career pathways that encourage internal mobility, improve retention, and unlock hidden talent – such as reskilling auditors into data analysts.
- Align workforce capabilities with compliance and risk management priorities to reduce regulatory risk.
Data-Driven Benchmarking & Workforce Planning
With connected data, financial institutions can incorporate external market insights to make strategic decisions on compensation, location, and workforce investments. For example, understanding where cybersecurity skills command premium pay can guide where to establish or grow teams.
Internally, dynamic workforce planning powered by skills and task intelligence supports:
- Real-time identification of skills adjacencies, to spot the employees who could pivot to new roles with minimal training.
- AI-driven recommendations for upskilling and reskilling tailored to evolving business needs.
- More accurate succession planning for fintech, AI, and regulatory roles.
Ethical & Practical Considerations in AI-Powered Talent Management
The adoption of AI in talent functions is still nascent – only 18% of FS executives say their firms are implementing generative AI in HR, compared to 47% in marketing or sales (Deloitte). Yet AI is the key enabler to operationalizing a skills-and-task-based approach, rapidly analyzing and normalizing workforce data, inferring hidden skills, and predicting future needs.
However, AI must be implemented responsibly:
- Data privacy, security, and compliance are non-negotiable.
- Models should be audited regularly for bias.
- Transparency and explainability are vital to maintain workforce trust: 86% of FS workers believe transparency boosts trust (Deloitte).
- Humans must remain central to decision-making, with AI as an augmenting tool.
Proven Benefits of a Skills- and Task-Based Strategy
Organizations embracing this model are likely to see dramatic improvements:
- Skills-based companies are 107% more likely to place talent effectively, 52% more likely to innovate, and 57% more likely to anticipate and respond to change (Deloitte).
- Companies using skills-based hiring platforms saw an average reduction of 25% in time-to-hire, with some organizations experiencing reductions as high as 40%, enabling them to fill critical roles more quickly. (Burning Glass Institute)
- Internal mobility improves retention and engagement, with FS&I employees nearly twice as likely to be committed when they see clear career pathways (Mercer).
How Beamery Helps Financial Services Future-Proof Talent Plans
At Beamery, we work with financial services firms like Wells Fargo, UBS & BBVA to help them make better talent-related decisions. We enable our clients to build dynamic, unified skills and task frameworks in days (not months), cutting complexity by 97%. Our AI-powered platform delivers:
- Real-time visibility into workforce capabilities across jobs and tasks.
- Actionable insights to close skills gaps through hiring, internal mobility, and targeted upskilling.
- Ethical AI-driven talent matching that prioritizes skills and potential, widening candidate pools and reducing bias.
Clients have seen:
- A 270% higher offer rate for resurfaced candidates with strong skills matches.
- A 25% increase in performance for Beamery-sourced hires.
- Up to 90% skills relevance in initial reviews.
Financial services firms adopting a connected workforce intelligence approach gain a crucial edge in managing talent risk: keeping them agile, compliant, and competitive amid continuous change.