As Distinctive Insights passes its first year since launch, we are beginning to set out the research agenda that will shape the next phase of our work.

Over the past year, our research has focused on how artificial intelligence is beginning to reshape operational workflows, decision processes, system architectures and technology ecosystems across financial services. Much of the public discussion around AI remains centred on models, interfaces and general capabilities. Our focus has instead been on the practical realities of deployment inside financial institutions and market infrastructure environments.

This next phase of research will significantly expand that scope.

Expanding the Distinctive Insights Research Model

As part of this next phase, we are also continuing to develop what we internally describe as our 3 Pillar Industry Intelligence Model.

This combines three complementary forms of industry intelligence:

• Deep thematic research into operational workflows, AI deployment models, enterprise architecture and industry transformation patterns
• Vendor landscape analysis focused on technology capabilities, market positioning and emerging competitive dynamics
• Industry engagement and survey-driven intelligence designed to validate emerging themes and identify developing areas of market focus

Across these areas, our objective is not simply to catalogue AI use cases. Instead, the focus is on understanding how AI is changing the structure of financial workflows, operational coordination, decision-making processes and enterprise technology environments.

Current Research Agenda

Capital Markets, Trading & Infrastructure

Capital Markets Front Office

Focus Areas:
AI-enabled trading and execution, pricing and market interaction, real-time position management, signal interpretation, execution intelligence, adaptive pricing controls, exposure monitoring, bounded agentic orchestration, feedback-loop risk and embedded governance across live front-office decision environments.

Middle Office & Operations (Buy-side and Sell-side)

Focus Areas:
Operational coordination, exception management, trade support, reconciliations, lifecycle processing, cross-system workflow management and the emergence of AI as an operational intelligence layer across fragmented systems and operations environments.

Market Facing Treasury

Focus Areas:
Liquidity management, collateral workflows, funding operations, market monitoring, treasury decision support and the convergence between real-time market activity and increasingly intelligent treasury infrastructure.

Market Risk Management

Focus Areas:
AI-driven signal analysis, scenario modelling, contextual risk interpretation, exposure monitoring, governance integration and enterprise-wide market risk coordination across increasingly complex trading and investment environments.

Custody, Clearing & Market Infrastructure

Focus Areas:
AI deployment across custody operations, clearing workflows, settlement infrastructure and broader market ecosystems, including operational resilience, intelligent exception handling, interoperability, surveillance, workflow coordination and increasingly automated infrastructure control environments.

Treasury, Lending & Enterprise Risk

Corporate Treasury

Focus Areas:
AI-enabled liquidity and cash management, funding and capital decision systems, treasury risk orchestration, continuous exposure monitoring, forecast-to-action workflows, hedge decision support, treasury control fabrics, bounded agentic coordination and governance across complex balance sheet and funding environments.

Corporate Lending

Focus Areas:
AI-enabled origination, underwriting, borrower assessment, document analysis, monitoring workflows and the balance between automation, contextual interpretation and human credit judgement.

Enterprise Credit Risk Management

Focus Areas:
Enterprise-wide credit exposure monitoring, portfolio oversight, data enrichment, signal detection, narrative analysis, governance integration and AI-driven risk coordination frameworks.

Investment Management

Portfolio Management & Monitoring

Focus Areas:
Portfolio monitoring, investment review, market interpretation, investment intelligence workflows, signal management and AI support for continuous monitoring across increasingly information-dense investment environments.

Advisor & Allocator Market

Focus Areas:
Manager research, allocation workflows, investment due diligence, advisor support processes, comparative analysis and AI-driven information synthesis across broad manager and allocator ecosystems.

Private Markets Investment Research & Deal Origination

Focus Areas:
AI-driven sourcing, thematic research, market mapping, company analysis, investment opportunity identification and the evolving structure of private markets research and deal discovery workflows.

Private Markets Due Diligence & Evaluation

Focus Areas:
Diligence workflows, document analysis, operational assessment, investment evaluation, contextual reasoning, retrieval systems, workflow acceleration and governance within high-value investment decision environments.

LP Servicing & Management

Focus Areas:
Investor servicing, reporting coordination, information delivery, relationship management and AI deployment across increasingly complex private markets communication and reporting environments.

Wealth Management

UHNW / HNW Wealth Management Investments

Focus Areas:
High-touch investment advisory, portfolio monitoring, client servicing, investment intelligence, advisor augmentation, personalisation and the interaction between AI systems and relationship-driven wealth models.

Mass Affluent & Retail Wealth Management Investments

Focus Areas:
Scaled investment servicing, digital advisory models, portfolio guidance, client engagement, AI-driven personalisation and operational scalability across platform-based wealth management environments.

And we’re starting with:

Middle Office & Operations

The first major research area within this agenda will focus on AI in Middle Office & Operations across both buy-side and sell-side institutions.

This research will examine how AI is being deployed across operational coordination, exception management, workflow orchestration, reconciliations, lifecycle processing and cross-platform operational intelligence. We expect this area to become one of the most important environments for enterprise AI deployment within financial services over the coming years.

Further details on this research programme – including associated industry surveys and supporting analysis – will be published shortly.