The Limits of LLMs: Why Generic AI Is Failing Financial Services

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17 September 2025

Over 95% of organisations aren’t seeing ROI from generic AI and in-house builds are failing. Why? Because traditional large language models (LLMs) lack memory, learning and integration into workflows. They’re disconnected tools which are great at text, but poor at follow-through.

LLMs are built to predict the next word. They’re tools for writing, not decision-making and they hallucinate due to a lack of specific domain knowledge. Financial services need solutions they can trust.

The Rise of Financial AI Agents

Agentic AI is purpose-built for complex work. It supercharges decision-making, automates workflows, and personalises customer interactions transforming banking and financial services in profound ways. It integrates learning, planning, and decision-making into systems that evolve and improve. Unlike LLMs, agents execute workflows, and don't just generate responses. AI Agents can handle complex, regulated financial environments.

Agents within Agentic AI have:

  • Planning and reasoning capabilities

  • Interim evaluation and self-correction

  • Access to multiple APIs and tools

  • Multi-model intelligence tailored to each task

  • Non-linear, adaptive logic

AI Agents Are Not the Future. They’re Already Here.

AI Agents of Galytix; CreditX and ClaimsX are already transforming global finance. The AI Agents not only generate content but also perceive, learn and take actions via integration with tools with minimal involvement based on set goals, enabling continuous adaptation and decision-making. Across 30+ financial institutions and 52 countries, they automate high-value credit and insurance workflows with trust, precision and speed.

  • Built with FIs, for FIs

  • 10 years of domain training

  • Solved trust + hallucination via our AI DataFactory

  • Handles internal + external data in all formats/languages

How Will AI Agents Change Workflows?

Agents automate entire workflows, not just siloed tasks. They sit inside and across your systems, aligned with your policy templates, generating explainable, auditable, bespoke, accurate and verifiable outputs every time.

  • End-to-end automation

  • Embedded policy logic

  • Transparent, trustworthy reasoning

Teams get speed, oversight and confidence. CreditX is currently delivering 30 hours work in 30 minutes for a global bank. The real value is that experts are empowered to do complex analysis quickly and reliably.

How the Technology Works Differently

Galytix has trained its agents on industry specific domain knowledge and proprietary data. Multiple agents using a multi-model approach are applied to solve the end-to-end data and credit/insurance workflows. Ontology – gateway to Agent’s data and domain intelligence – acts as the collective brain for the agents to solve complex, multi-step credit and claims problems with full auditability and traceability.

The Agent handles all data formats and source types, connecting data from multiple sources — across languages, formats and ecosystems. To solve the hallucination, data trust and quality problem, Galytix has built a unique AI DataFactory that combined our proprietary algorithms with a human-in-the-loop approach:

  • Detects, corrects, and repairs data

  • Validates data quality, consistency, and completeness

  • Operates with a “human-in-the-loop” oversight

Exhibit

Differentiating Galytix’ Agentic AI Tech Versus Non-Agentic Tech

GX

Galytix

Use Case: How AI Agents Are Changing Banking

A global bank uses CreditX for automating corporate and commercial credit risk workflows, updating internal ratings and performing ongoing monitoring of counterparts and portfolio. Analysts receive alerts, automated memos and AI-generated risk assessments — within policy.

Credit risk teams across 1st and 2nd Line of Defence get:

  • Faster internal reviews

  • Less admin, better decisioning

  • Greater control and trust

Use Case: How AI Agents Are Transforming Insurance

A European Insurer uses ClaimsX to classify documents, flag risks, unify data from multiple sources and recommend actions. What took days across multiple claims teams now takes minutes. Happier customers, lower costs.

Claims teams:

  • Reduce leakage

  • Improve payout accuracy

  • Enhance customer experience

Use Case: Driving Investment Into Emerging Markets

AI Agents are being deployed into development banks to turn 40 years of emerging markets risk data into trusted insights. With simple instructions in multiple languages, analysts can instantly generate greater credit risk insights, better understand underlying default risk patterns, produce peer comparisons, alerts, and investor-grade reports. Better, more accessible intelligence and data will unlock value in emerging markets and help drive better allocation of capital to where it’s needed most.

Where Next?

By 2026, the most successful AI deployments won’t be prompt-driven pilots, they’ll be trusted, task-completing AI agents that learn, reason and act.

Galytix operates at this application layer, building AI agents trained on financial domain data, validated by experts and is already transforming the way global banks and insurers assess credit, manage claims and ensure data quality.

While others chase hype, Galytix delivers trust, productivity and real ROI — empowering teams to do 30 hours of work in 30 minutes.

This is Financial Services Agentic AI.

And it's live.

Try CreditX here.