Industries / Banking, Financial Services & Insurance

Where the cost of a mistake is measured in headlines, not just dollars.

Banks and financial institutions run on decades-old core systems, strict regulatory reporting, and a fraud and incident volume that no manual review process can keep up with. We build agents that operate inside those constraints, with an audit trail regulators can actually read.

70% faster incident response US regional bank, agent-run incident triage
100% of agent actions logged, replayable & reversible
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KEY CHALLENGES

Legacy core systems that resist change
Decades of custom logic make even small changes high-risk.
Regulatory reporting that eats engineering capacity
Compliance work competes directly with product roadmaps.
Fraud and incident volumes outpacing manual review
Review queues grow faster than headcount can follow.
Customer expectations shaped by fintech, not banks
Digital-native competitors set the bar for response time.
Audit requirements most AI vendors weren't built for
Generic AI tooling rarely survives a real compliance review.

WHERE WE START

Agent Orchestration

Agent Orchestration

Fraud triage and incident response run by agents directly connected to your core banking and case-management systems, with every action logged.

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OUR BANKING TECHNOLOGY EXPERIENCE

Microsoft Azure
AWS
Microsoft Dynamics 365
Snowflake
Salesforce
70% faster incident response

US regional bank, agent-run incident triage

Read the case study

Ten industries. One audited standard.

Different regulations, different systems of record — the same discipline every time: agents that run inside guardrails and leave a record you can read.

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Banking, Financial Services & Insurance case studies

Challenge, solution, results. Four engagements in this sector.

Anonymised at the client's request. Each card states the pain point, what we built, and what changed. Plus the service type and country.

04 studies
AI Agents USA

Loan-document triage for a Texas credit union

Regional credit union, Texas

Challenge
Loan officers were spending the first two hours of every day opening member uploads, checking pay stubs and bank statements against a checklist, and chasing missing pages by email. Applications sat in the queue for three or four days before anyone looked at the numbers.
Solution
We built an agent that reads each upload as it lands, classifies the document type, extracts the fields the underwriting checklist needs, and flags gaps back to the member automatically. Nothing is approved by the agent; it assembles a complete file and an audit log, then hands off to an officer.
Results
  • Time to first underwriter review cut from 3.5 days to 1
  • Missing-document requests sent within 20 minutes of upload
  • Live across 11 branches after an 8-week build
Service type · AI AgentsCountry · USA
Web UK

Mortgage application portal for a building society

Mutual building society, North of England

Challenge
The society took mortgage applications through a PDF form that brokers emailed in, then keyed into the core system by hand. Re-keying errors meant roughly one in eight cases bounced back to the broker, and nobody could tell an applicant where their case was without ringing the branch.
Solution
We replaced the form with a broker and applicant portal on Azure, validating each field against the society's lending rules before submission and writing straight into the core system through a hardened integration layer. Every status change is timestamped and visible to the applicant, the broker and the underwriter.
Results
  • Re-keying errors down 82% in the first quarter
  • Broker status calls to branches fell by roughly 600 a month
  • Delivered in 14 weeks, including FCA-aligned penetration testing
Service type · WebCountry · UK
AI MVPs USA

First-notice-of-loss summarisation pilot for a regional insurer

Regional property and casualty insurer, Midwest

Challenge
Claims handlers received first-notice-of-loss reports as call transcripts, emails and photos, then wrote a summary and severity estimate by hand before assigning the claim. The write-up took 25 to 40 minutes per claim and varied enough between handlers that supervisors were re-reading most of them.
Solution
In an eight-week MVP we built a summariser that drafts the loss narrative, lists the evidence received, and proposes a severity band with the passages it relied on highlighted. Handlers edit and sign off; the draft, edits and final version are all kept so the insurer can measure drift over time.
Results
  • Summary drafting time down from 32 minutes to 9 on average
  • Handlers accepted 71% of severity suggestions without change
  • Pilot completed in 8 weeks on 1,400 real claims
Service type · AI MVPsCountry · USA
Apps UK

Complaints handling app on Dynamics 365 for a motor insurer

Mid-market motor insurer, Midlands

Challenge
Complaints were logged in a shared spreadsheet, with the eight-week Financial Ombudsman deadline tracked by colour-coding cells. Root-cause reporting for the board was assembled by hand each quarter, and two complaints had breached the deadline in the previous year because the spreadsheet owner was on leave.
Solution
We built a complaints module inside the insurer's existing Dynamics 365 tenant with a Power App front end for handlers. Deadlines, escalations and final-response letters are driven by workflow rather than memory, and every action is recorded against the case. Quarterly root-cause reporting now comes from a Power BI page.
Results
  • Zero deadline breaches in the 12 months since go-live
  • Quarterly board pack preparation reduced from 3 days to 2 hours
  • Built and adopted by 14 handlers in 10 weeks
Service type · AppsCountry · UK

FAQ

Banking, Financial Services & Insurance + agentic AI: questions, answered.

How can AI agents help banks reduce fraud and incident response times?

AGS agents triage fraud alerts and run incident response directly inside your core banking and case-management systems, escalating only what needs a human. Because review queues grow faster than headcount, agents clear the routine load in seconds and log every action. One global bank cut incident response time by 70% with agent-run triage.

Is agentic AI safe for regulated financial services and audits?

Yes. AGS agents are built for examiners, not just engineers. Every action is logged, checked, and reversible, agents run under least-privilege identity, and human-in-the-loop gates guard consequential decisions. Our controls are aligned to ISO 27001 and SOC 2, so an audit becomes a query against a complete record rather than a scramble for evidence.

What back-office banking processes can AGS automate?

AGS automates reconciliation, exception handling, regulatory reporting, and service-desk resolution across millions of transactions. Agents match, flag, and escalate exceptions your team once chased manually, freeing engineering capacity that compliance work used to consume. Each step runs inside guardrails and leaves a defensible record, so throughput rises without adding audit risk.

How does AGS handle compliance and audit trails for banking agents?

Every autonomous action is captured as an action-level audit log that maps to the systems it touched, with least-privilege identity limiting what each agent can reach. Reversibility means any step can be unwound, and human sign-off gates the decisions that warrant it. Regulators get a record they can actually read, not vendor assurances.

Can autonomous agents work with legacy core banking systems?

Yes. AGS agents connect to decades-old core systems, ledgers, and case-management tools without a rip-and-replace programme. Agents operate through existing interfaces under controlled, least-privilege access, so you modernise how work gets done while the systems of record stay in place. Migration-tested infrastructure keeps the underlying operations resilient and available.

Talk to a team that's built for the audit.

Tell us the workflow that matters most in your operation.

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