Business case and benefits
- Head of customer relations
- A · Accountable
- Product owner
- R · Responsible
- Solutions architect
- C · Consulted
- Technical PM
- C · Consulted
- Engineers
- I · Informed
- Compliance & DPO
- C · Consulted
- Security
- I · Informed
Every complaint caught, whatever channel it came through, answered fairly within the DISP deadlines, and traced back to its root cause. A handler writes and signs every final response.
At a glance
An illustrative scenario. The numbers are typical examples, not a client case study. The cloud services and UK rules were checked on 9 November 2026.
Under DISP, a complaint is any expression of dissatisfaction, spoken or written, whether or not it is justified. Customers rarely say the word. They say it on a call about something else, in a chat message, in a reply to a collections letter, or through a claims management company. In a typical lender, a good share of these never get logged as complaints at all, so they never get the deadline, the investigation or the final response the rules require.
Logged complaints have their own problem. A handler has to pull the account history, the call recordings, the letters sent, the product terms in force at the time, the relevant internal policy and any similar past decisions, before they can even start writing. That gathering takes most of the time. Final responses vary from handler to handler, and the reasons the Financial Ombudsman Service overturns a decision often come down to evidence that was available but not found.
Volumes are also hard to plan for. When a redress issue reaches the news, as motor finance commission did, complaints about it can arrive far faster than usual, and the rules for handling them can change while they are still open. A complaints operation that can only scale by hiring has no good answer to that.
Meanwhile each referral to the ombudsman now costs £680 once the firm's £2,000 free allowance for the year is used up, and complaints data is one of the main ways the FCA and the firm's own board judge whether the Consumer Duty is working.
Agree these, and measure the baseline, before anything is built. Example targets are typical, not promises.
Share of expressions of dissatisfaction in a sample of calls and chats that were logged as complaints. Audited, not self-reported.
ExampleAbove 95% of the audit sample
Final responses sent within eight weeks, or 15 business days for payment services complaints.
ExampleEvery complaint, every month
Time moved from finding information to judging the complaint.
ExampleDown by half
How often the Financial Ombudsman Service changes the firm's answer. The clearest test of whether first responses are fair.
ExampleFalling, measured against last year
How much handlers change the drafts. Very high means it isn't helping; near zero can mean drafts are being signed unread.
ExampleStable, and reviewed weekly
Root causes with a named owner, a fix, and a measured fall in the complaints they caused.
ExampleReported to the Consumer Duty board report
Cross-sector rules are on the UK regulation map.
Complaints must be investigated competently, diligently and impartially, and answered fairly. A final response, or a written explanation of the delay, is due within eight weeks (DISP 1.6), or within 15 business days for payment services and e-money complaints, extendable to 35 in exceptional cases. Complaints resolved by the end of the third business day can be closed with a summary resolution communication (DISP 1.5). The workflow, not the AI, runs these clocks.
Firms must look for recurring or systemic problems in their complaints and fix them, including for customers who didn't complain. The root-cause analysis in this design exists to meet that rule, and every finding goes to a named owner.
There's no AI-specific rulebook. The FCA applies the Duty to AI like any other change. Final responses must be clear and fair, complaints data feeds outcomes monitoring by product and customer group, and the board report shows what was found and fixed.
Every final response tells the customer they can go to the ombudsman within six months. Since 1 October 2026 the ombudsman has new grounds to dismiss complaints, and its fair and reasonable test now looks at the standards in force at the time of the act or omission. So the evidence pack must show the terms and policies that applied then, not today's.
Signs of vulnerability in a complaint, such as illness, bereavement or financial difficulty, are flagged to a trained specialist, never acted on automatically, and never used to treat the customer less favourably.
Complaints often contain health and financial hardship details. That means a DPIA before the pilot, processing in UK regions, a clear retention period, and a contract that stops providers training their models on your data. The AI never decides a complaint, so there's no solely automated decision, and every adverse outcome is a handler's decision.
Showing AWSAzuresovereign / on-prem services. Switch with the toggle; every diagram and table on this page follows it.
01Channels
02Intake
03Intelligence
04Orchestration
05Systems of record
06People
| Layer | AWS | Azure | Sovereign / on-prem |
|---|---|---|---|
| Intake: email, letters, chat, filesClaims firms' bulk submissions need their own route, with letters of authority checked by a person. | Amazon SES, API Gateway, S3 | Logic Apps connectors, API Management, Blob Storage | Your mail server, Kong, Ceph or IONOS S3 Object Storage |
| Call transcriptionUse the recordings the contact centre already keeps. Test on real calls, with accents and background noise. | Amazon Transcribe | Azure Speech in Foundry Tools | Open-weight speech models (e.g. Whisper) |
| Reading letters and attachmentsHandwritten letters and photographed statements are common. Pilot on them, not on clean PDFs. | Amazon Textract | Azure Content Understanding (includes Document Intelligence) | Open-source parsing (e.g. Docling) plus an open-weight vision model |
| Reasoning, classification and draftingAWS and Azure both offer a choice of models, including Claude. On-prem and sovereign options run open-weight models. | Amazon Bedrock | Microsoft Foundry | Open-weight models served with vLLM on your own GPUs, or IONOS AI Model Hub |
| Policies and past decisions (retrieval)Index product terms and policies by the date they applied, plus signed-off past decisions and relevant published ombudsman decisions. | Bedrock Knowledge Bases | Foundry IQ, built on Azure AI Search | OpenSearch, or PostgreSQL with pgvector |
| Agent runtimeThe original Bedrock Agents closed to new customers on 30 July 2026; new builds use AgentCore. | Amazon Bedrock AgentCore | Foundry Agent Service | An open-source agent framework (e.g. LangGraph) on Kubernetes |
| Root-cause analysisGroups complaints into themes over weeks and months. A person decides which themes are real root causes. | Amazon SageMaker AI, with your data platform | Azure Machine Learning, with your data platform | MLflow and Kubeflow on Kubernetes, with your data platform |
| Workflow and deadlinesThe DISP clocks live here, in code with tests, not in a prompt. | AWS Step Functions | Logic Apps or Durable Functions | Temporal, or n8n |
| Middleware and events | Amazon EventBridge, SQS | Event Grid, Service Bus | Apache Kafka or RabbitMQ |
| Link to the case system and core bankingReuse the integration layer you have. Don't buy a new one for this. | API Gateway, plus your existing integration platform if you have one | API Management, plus your existing integration platform if you have one | Kong or your existing API gateway, plus your existing integration platform if you have one |
| Human reviewHandlers review and sign where they already work, not in a new screen. | In the handlers' existing complaints case system | In the handlers' existing complaints case system | In the handlers' existing complaints case system |
| GuardrailsBlock drafts that promise redress amounts, admit liability or quote a policy the retrieval didn't return. | Bedrock Guardrails | Foundry guardrails (Azure AI Content Safety) | Open-source guardrails (e.g. NeMo Guardrails, Llama Guard) |
| Identity, keys, data protection | IAM Identity Center, KMS, Macie | Entra ID, Key Vault, Purview | Keycloak or your existing Active Directory; OpenBao or HashiCorp Vault; an HSM |
| Monitoring and auditLog every classification, every draft, every edit and every signature, with the evidence used. | CloudWatch, CloudTrail | Azure Monitor, Log Analytics | Prometheus, Grafana, OpenTelemetry |
| UK data residencyIONOS AI Model Hub runs in German data centres: EU, not UK, residency. | eu-west-2 (London) | UK South / UK West | Your own UK data centre, or a UK or EU provider |
On a phone, the table shows the platform you pick. Sovereign / on-prem means open, portable components you can run in your own data centre or with a UK or European provider; IONOS is shown as one example, and others exist. What sovereign cloud means →
Many organisations keep core systems and sensitive data on their own servers. This is how the same design works across both.
Stays on-prem
Core banking, the card and loan platforms, call recording and, in many banks, the complaints case system stay where they are. Nothing in this design needs them to move.
Uses cloud AI
Transcription, classification, retrieval and drafting can run in AWS or Azure UK regions, or on your own GPUs with open-weight models if complaint data must not leave your estate.
How they connect
A private link (AWS Direct Connect or Azure ExpressRoute) and the API layer. Only the fields needed for a case are sent, and results come back as events onto your queue and into the case system.
If the link drops
Complaints keep being logged by the contact centre and the case system, and the DISP clocks keep running on your side. Handlers work cases as they did before the AI, and queued items are classified when the link returns.
What each agent may do through its tools, what it may not, and where a person signs off. The limits are enforced by the platform, not the prompt.
Complaint intake agent
Where a person signs offA team leader reviews a daily sample of what the agent logged and what it didn't, and every case it isn't sure about. The agent's permissions are enforced by the platform's identity and policy controls, not by instructions in a prompt.
Investigation and drafting assistant
Where a person signs offThe handler decides the outcome, edits the draft and signs every final response. Redress over an agreed amount, and every complaint flagged as vulnerable, also needs a second person's approval.
The complaints case system stays the record. Every complaint, deadline and decision lives there, and the AI reads and writes through the API layer like any other system. If you already run an integration platform, it uses that.
Each new transcript, email or letter becomes a message on a queue. If the case system or core banking is slow, items wait safely and nothing is lost or logged twice. Every message carries an ID, so a retry never creates a duplicate case.
The DISP clock starts when the firm receives the complaint, not when the AI gets round to it. The workflow records the receipt time from the source channel and runs the eight-week and 15-business-day timers itself, with alerts well before each deadline.
The AI can be switched off without stopping the business. If it's paused, complaints are logged and handled by people exactly as they were before.
Map today's process across every channel, measure the baseline (including unlogged complaints in a call sample), check data access and pick the first product.
Gate · must be true to passBaseline agreed, data access confirmed, DPIA started, compliance and the Consumer Duty champion involved.
One product, such as credit cards, in shadow mode: the AI classifies and drafts, handlers work as normal, and the two are compared.
Gate · must be true to passClassification accuracy and draft quality within agreed limits, no customer group worse off, compliance sign-off.
Drafts and classification go live for the first product, with monitoring, support and a rollback plan.
Gate · must be true to passMonitoring, support model, rollback plan and handler training in place.
Add products one at a time, then switch on root-cause analysis across the whole book and feed it into Consumer Duty reporting.
Gate · must be true to passEach new product passes the same pilot gate.
| Activity | Head of customer relations | Product owner | Solutions architectI can fill this | Technical PMI can fill this | EngineersI can fill this | Compliance & DPO | SecurityI can fill this |
|---|---|---|---|---|---|---|---|
| Business case and benefits | Accountable | Responsible | Consulted | Consulted | Informed | Consulted | Informed |
| Target architecture | Informed | Consulted | Accountable and Responsible | Consulted | Consulted | Consulted | Consulted |
| DPIA and Consumer Duty review | Accountable | Consulted | Consulted | Informed | Informed | Responsible | Consulted |
| Build and integration | Informed | Consulted | Accountable | Responsible | Responsible | Informed | Consulted |
| Accuracy testing on real complaints | Informed | Accountable | Responsible | Consulted | Responsible | Consulted | Informed |
| Go-live decision | Accountable | Responsible | Consulted | Responsible | Informed | Consulted | Consulted |
| Run, monitor and improve | Informed | Accountable | Consulted | Consulted | Responsible | Consulted | Consulted |
R ResponsibleA AccountableC ConsultedI Informed· not involved
Option A
If there's no architect on the programme, I'd own the design end to end: the target architecture, the integration with your case system, contact centre and core banking, the DISP clock logic, and the gates. I'd report to your programme board and work closely with your customer relations and compliance leads.
Option B
If your partner or your own team already has an architect, I'd take on the retrieval, the drafting assistant and the case-system integration under their lead, and give them a second senior opinion on the rest. Where the work needs more hands, I bring in people I trust.
Goes wrong
The pilot only used logged complaints, so it never tested the hardest part: spotting the ones nobody logged.
How the design avoids it
Include a sample of ordinary calls and chats in the test set, labelled by your quality team.
Goes wrong
The assistant quotes today's terms for a complaint about something that happened three years ago.
How the design avoids it
Index policies and terms by effective date, and make the retrieval filter on the date of the events.
Goes wrong
Drafts read well, so handlers start signing them without checking the evidence.
How the design avoids it
Show the source behind every statement, track edit rates, and sample signed responses every week.
Goes wrong
Root-cause themes go into a slide deck and nothing changes.
How the design avoids it
Every theme gets a named owner in the business and a measure that shows whether the fix worked.
Goes wrong
A redress spike arrives and the classification has no category for it.
How the design avoids it
Set up streams for known issues before they peak, and keep the taxonomy owned and versioned.
Changes already announced or under way that affect this design. More in the UK horizon scan.
Keep commission complaints as their own stream, and plan capacity for both outcomes.
Map the classification to the new return's fields before go-live, so reporting comes straight from the case data.
Keep complaints MI split by product and customer group, so it fits the board report whatever its final shape.
Keep evidence packs complete and dated, so a case can move to the ombudsman quickly and stand up on the standards in force at the time.
Keep the classification log, the drafts, the edits and the signatures in a form you could show the ICO.
Good answers are specific. Vague answers to any of these are worth following up.
Whether you need someone to lead the design or to support the architect you already have, let's talk it through.