Unlock the Full Potential of
Agentic AI in Finance
Power smarter outcomes in banking, wealth management and fintech.
The Finance Industry is at a Turning Point
Today, financial services firms are under compounding pressure—and it’s coming from all sides:
Firms Are Sprinting to Stay Ahead
of firms will deploy
AI by 2026
expect agentic AI to
be routine by 2028
of apps will feature
AI agents by 2026
THE AI PARADOX
AI is no longer a competitive advantage—it’s table stakes. Yet most firms remain stuck in AI pilot purgatory, unable to move from experimentation to production-grade deployment. The causes:
01
Infrastructural Fragility
Legacy finance systems, like Temenos, Finacle, and FIS, struggle to deploy AI at production scale in regulated, complex environments.
02
Data Fragmentation
Financial data sits in silos across legacy systems, making it hard to build reliable, contextually aware AI.
03
Regulatory & Governance Pressure
To meet today’s tough regulatory mandates, AI must be auditable, explainable, and sovereign.
04
Knowledge Automation Gap
Over-reliance on manual knowledge management hinders fine-tuning and limits AI insights.
05
No Domain Training for Finance
Because general-purpose LLMs lack finance-specific domain training, they can’t adapt to evolving regulations, rendering outputs unreliable and potentially dangerous.
The Solution Firms Need Now
Meet The Business AI Cloud
Uniphore’s Business AI Cloud is purpose-built for this moment. Sovereign, composable, and secure, it enables financial service firms across banking, wealth management, and fintech to deploy AI agents at scale, encode institutional and regulatory knowledge into fine-tuned Small Language Models (SLMs), and drive measurable outcomes across both customer-facing and back-office operations.
Banking & Capital Markets
- Composable architecture overcomes infrastructure limitations, accelerating AI adoption and time-to-value.
- Zero-data approach unifies fragmented data across core banking, CRM, and risk systems.
- Security guardrails automate AML/KYC compliance, minimizing both risk and overhead.
- Agentic AI optimizes back-office operations and fixes customer experience gaps.
Wealth Management
- Zero-data AI fabric eliminates front-office (CRM) and back-office (portfolio management) data silos
- Contextually aware AI agents drive personalization and communication consistency at scale
- Compliance automation captures necessary documentation accurately and securely
- Intuitive interface enables nontechnical users to automate client onboarding and KYC processes
Fintech
- Composable architecture integrates AI into existing tech stack (APIs, data platforms, etc.)
- Security guardrails provide real-time fraud detection and risk decisioning at transaction volume
- Adaptive AI minimizes compliance complexity—and costs—in highly regulated markets
- Scalable platform can support growing customer base without sacrificing speed or governance
AI Use Cases for Finance
The firms that move from pilot to production all have one thing in common: they start with use cases that link achievable outcomes with measurable ROI.
Automated alert disposition
Financial services firms face an overwhelming volume of transaction monitoring (TM) alerts generated daily by legacy rule-based systems. With AI, firms can accurately and automatically flag TM alerts for escalation while filtering false positives.
Accounts payable contract leakage
Fragmented contract data, time-consuming manual reviews, and lack of structured visibility hinder efforts to identify and reconcile leakage. AI can identify and flag potential leakage risks (missed renewals, unbilled services, over-discounting, etc.) and provide explainable recommendations for corrective action.
Report-to-record
Manual reconciliations are time-consuming and error-prone. AI can optimize the report-to-record (R2R) cycle by connecting data across ERP, sub-ledger, and reporting systems to explain discrepancies, reconcile balances, and support continuous assurance.
Transparent decision narrative generation
Regulators and internal auditors require firms to explain the decisions they made regarding compliance alerts. AI can generate a clear, concise, and justifiable “narrative” for every recommended action to ensure explainability, auditability, and trust.
Client experience friction analysis
Usability issues, missing information, and design gaps in the client experience can drive up call volumes and cost millions in annual service expenses. AI can analyze digital journeys for friction points and generate actionable insights for improvement.
Source-to-pay
Fragmented data, manual validation, and policy inconsistencies limit visibility into the source-to-pay (S2P) lifecycle, making reconciliation difficult and increasing the risk of mispayment and cost leakage. AI can optimize S2P by reviewing contracts, validating terms, and cross-matching invoices with purchase orders and receipts in real time.
Financial statement spreading
Manual reconciliations are time-consuming and error-prone. AI can optimize the report-to-record (R2R) cycle by connecting data across ERP, sub-ledger, and reporting systems to explain discrepancies, reconcile balances, and support continuous assurance.
AI Use Case Guide for Financial Services Firms
Today’s most successful AI implementations anticipate customer behavior, build momentum around those moments, and create a flywheel where every interaction makes the next one smarter.
What Agentic AI
can do for You?
From optimizing business processes to improving client experiences, Uniphore’s AI platform is the agentic foundation for the modern financial firm. Have questions or want to see how AI can help drive specific outcomes?
Book a demo with our experts.
