Financial services · Playbook 03

I've worked in this sector

Complaints handling

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.

  • Retrieval (RAG)
  • Agents with tools
  • Speech and voice
  • Human in the loop
  • FCA DISP
  • FCA Consumer Duty
  • Financial Ombudsman Service
  • FCA FG21/1
  • UK GDPR

At a glance

The problem
Complaints arrive by phone, letter, email, chat and claims firms, many are never logged, and handlers spend most of their time gathering evidence
Typical volume
Around 5,000 complaints a month across cards, loans and current accounts, with sudden spikes when a redress issue hits the news
Who's involved
Customer relations, the contact centre, product owners, compliance, the Consumer Duty champion, data protection, IT
Pilot
8–10 weeks on one product, after a 3-week discovery
Platforms
AWS, Azure, or a sovereign or on-prem stack

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.

The business problem

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.

What AI changes

  • Every call transcript, chat, email and letter is checked for dissatisfaction, so complaints are caught and logged on the day they're made, with the DISP clock started correctly.
  • Each complaint is classified by product, cause and the FCA's reporting categories, and routed to the right team, with possible vulnerability flagged to a specialist.
  • Before the handler opens the case, the evidence is gathered: account history, contact history, the terms and policies in force at the time, and similar past decisions, including relevant published ombudsman decisions.
  • The handler gets a drafted final response in plain English, with every statement linked to the evidence behind it. They check it, change it and sign it. Nothing is sent without them.
  • Root causes are found across thousands of complaints, not one at a time, and each one is given to a named owner in the business to fix.
  • Consumer Duty monitoring gets clean, consistent complaints data by product and customer group, including vulnerable customers.

How success is measured

Agree these, and measure the baseline, before anything is built. Example targets are typical, not promises.

Complaints caught

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

Responses within DISP deadlines

Final responses sent within eight weeks, or 15 business days for payment services complaints.

ExampleEvery complaint, every month

Handler time on gathering evidence

Time moved from finding information to judging the complaint.

ExampleDown by half

Ombudsman change rate

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

Draft edit rate

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 fixed

Root causes with a named owner, a fix, and a measured fall in the complaints they caused.

ExampleReported to the Consumer Duty board report

UK regulation and controls

Cross-sector rules are on the UK regulation map.

  • FCADISP 1: complaint handling rules

    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.

  • FCADISP 1.3: root cause analysis

    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.

  • FCAConsumer Duty (PRIN 2A)

    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.

  • Financial Ombudsman ServiceDISP 2 and 3, and the 2026 redress reforms

    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.

  • FCAVulnerable customers (FG21/1)

    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.

  • ICOUK GDPR, the Data Protection Act 2018 and automated decisions

    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.

The solution

Showing AWSAzuresovereign / on-prem services. Switch with the toggle; every diagram and table on this page follows it.

Complaints handling: reference architecture
  1. 01Channels

    • Phone and contact centre
    • Email, letters and web form
    • Chat, app and social
    • Claims firms and representatives
  2. 02Intake

    • Amazon TranscribeAzure Speech in Foundry ToolsOpen-weight speech models (e.g. Whisper)Call transcripts
    • Amazon TextractContent Understanding (Document Intelligence)Docling plus an open-weight vision modelLetters and attachments
    • API GatewayAPI ManagementKong, or your existing API gatewayAPI for chat, app and email
  3. 03Intelligence

    • Agent
      Bedrock AgentCoreFoundry Agent ServiceLangGraph on Kubernetes, with open-weight models via vLLMComplaint intake agent
    • Bedrock Knowledge BasesFoundry IQ (Azure AI Search)OpenSearch, or PostgreSQL with pgvectorPolicies and past decisions
    • Agent
      Bedrock AgentCoreFoundry Agent ServiceLangGraph on Kubernetes, with open-weight models via vLLMInvestigation and drafting assistant
    • SageMaker AIAzure Machine LearningMLflow and Kubeflow on KubernetesRoot-cause analysis
  4. 04Orchestration

    • Step FunctionsLogic Apps / Durable FunctionsTemporalComplaint workflow and DISP clock
    • EventBridge + SQSEvent Grid + Service BusApache Kafka or RabbitMQEvents and queues
  5. 05Systems of record

    • Complaints case system
    • Core banking, cards and loans
    • Contact centre and call recording
    • Consumer Duty MI and data platform
  6. 06People

    • Person
      Handler: edits and signs the final response
    • Person
      Vulnerable customer specialists
    • Person
      Root-cause owners and Consumer Duty review
  • Cloud or platform service (AWSAzuresovereign / on-prem)
  • AI agent
  • A person decides
  • Your existing systems
  • Outside your organisation

Components, side by side

Complaints handling: components on AWS, Azure and a sovereign or on-prem stack
LayerAWSAzureSovereign / 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, S3Logic Apps connectors, API Management, Blob StorageYour 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 TranscribeAzure Speech in Foundry ToolsOpen-weight speech models (e.g. Whisper)
Reading letters and attachmentsHandwritten letters and photographed statements are common. Pilot on them, not on clean PDFs.Amazon TextractAzure 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 BedrockMicrosoft FoundryOpen-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 BasesFoundry IQ, built on Azure AI SearchOpenSearch, or PostgreSQL with pgvector
Agent runtimeThe original Bedrock Agents closed to new customers on 30 July 2026; new builds use AgentCore.Amazon Bedrock AgentCoreFoundry Agent ServiceAn 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 platformAzure Machine Learning, with your data platformMLflow 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 FunctionsLogic Apps or Durable FunctionsTemporal, or n8n
Middleware and eventsAmazon EventBridge, SQSEvent Grid, Service BusApache 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 oneAPI Management, plus your existing integration platform if you have oneKong 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 systemIn the handlers' existing complaints case systemIn the handlers' existing complaints case system
GuardrailsBlock drafts that promise redress amounts, admit liability or quote a policy the retrieval didn't return.Bedrock GuardrailsFoundry guardrails (Azure AI Content Safety)Open-source guardrails (e.g. NeMo Guardrails, Llama Guard)
Identity, keys, data protectionIAM Identity Center, KMS, MacieEntra ID, Key Vault, PurviewKeycloak 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, CloudTrailAzure Monitor, Log AnalyticsPrometheus, Grafana, OpenTelemetry
UK data residencyIONOS AI Model Hub runs in German data centres: EU, not UK, residency.eu-west-2 (London)UK South / UK WestYour 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 →

Hybrid and on-prem

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.

The agents

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

May do

  • Read call transcripts, chats, emails and letters as they arrive
  • Spot expressions of dissatisfaction, including ones that don't use the word complaint
  • Classify the complaint by product, cause and reporting category
  • Create a case in the complaints system and route it to the right team
  • Flag possible vulnerability, and complaints that belong to a known redress issue

May not do

  • Decide that something is not a complaint and drop it: unclear cases go to a person
  • Contact the customer
  • Change the DISP deadline or close a case
  • Change account or customer data

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

May do

  • Read the account, transaction and contact history for this customer only
  • Look up the product terms and policies in force at the time of the events
  • Find similar signed-off past decisions and relevant published ombudsman decisions
  • Draft an evidence summary and a plain-English final response, with sources linked
  • Suggest a redress calculation using the firm's approved method, for the handler to check

May not do

  • Uphold, reject or close a complaint
  • Send anything to the customer
  • Pay or agree redress
  • Read other customers' records beyond the anonymised past decisions

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.

Middleware and integration

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.

Process and people

  • A complaints quality team that samples calls and chats every week to check what was and wasn't logged as a complaint.
  • Override rules, so handlers record why they changed a classification or a draft, and those reasons are fed back.
  • A named owner for the policy library and the past-decisions index, so retired policies are dated, not deleted.
  • A monthly root-cause forum where product owners accept or reject each theme, with fixes tracked to closure.
  • A capacity plan for complaint spikes, with the classification for known redress issues set up in advance.
  • Handlers trained before go-live, including what the AI can't see and why the signature is theirs.

Delivery plan

  1. 3 weeks

    Discovery

    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.

  2. Gate · must be true to passBaseline agreed, data access confirmed, DPIA started, compliance and the Consumer Duty champion involved.

  3. 6–8 weeks

    Pilot

    One product, such as credit cards, in shadow mode: the AI classifies and drafts, handlers work as normal, and the two are compared.

  4. Gate · must be true to passClassification accuracy and draft quality within agreed limits, no customer group worse off, compliance sign-off.

  5. 4–6 weeks

    Production

    Drafts and classification go live for the first product, with monitoring, support and a rollback plan.

  6. Gate · must be true to passMonitoring, support model, rollback plan and handler training in place.

  7. Ongoing

    Scale

    Add products one at a time, then switch on root-cause analysis across the whole book and feed it into Consumer Duty reporting.

  8. Gate · must be true to passEach new product passes the same pilot gate.

Roles and RACI

Who is responsible, accountable, consulted and informed, by activity
ActivityHead of customer relationsProduct ownerSolutions architectI can fill thisTechnical PMI can fill thisEngineersI can fill thisCompliance & DPOSecurityI can fill this
Business case and benefitsAccountableResponsibleConsultedConsultedInformedConsultedInformed
Target architectureInformedConsultedAccountable and ResponsibleConsultedConsultedConsultedConsulted
DPIA and Consumer Duty reviewAccountableConsultedConsultedInformedInformedResponsibleConsulted
Build and integrationInformedConsultedAccountableResponsibleResponsibleInformedConsulted
Accuracy testing on real complaintsInformedAccountableResponsibleConsultedResponsibleConsultedInformed
Go-live decisionAccountableResponsibleConsultedResponsibleInformedConsultedConsulted
Run, monitor and improveInformedAccountableConsultedConsultedResponsibleConsultedConsulted

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

Target architecture

Head of customer relations
I · Informed
Product owner
C · Consulted
Solutions architect
A/R · Accountable and Responsible
Technical PM
C · Consulted
Engineers
C · Consulted
Compliance & DPO
C · Consulted
Security
C · Consulted

DPIA and Consumer Duty review

Head of customer relations
A · Accountable
Product owner
C · Consulted
Solutions architect
C · Consulted
Technical PM
I · Informed
Engineers
I · Informed
Compliance & DPO
R · Responsible
Security
C · Consulted

Build and integration

Head of customer relations
I · Informed
Product owner
C · Consulted
Solutions architect
A · Accountable
Technical PM
R · Responsible
Engineers
R · Responsible
Compliance & DPO
I · Informed
Security
C · Consulted

Accuracy testing on real complaints

Head of customer relations
I · Informed
Product owner
A · Accountable
Solutions architect
R · Responsible
Technical PM
C · Consulted
Engineers
R · Responsible
Compliance & DPO
C · Consulted
Security
I · Informed

Go-live decision

Head of customer relations
A · Accountable
Product owner
R · Responsible
Solutions architect
C · Consulted
Technical PM
R · Responsible
Engineers
I · Informed
Compliance & DPO
C · Consulted
Security
C · Consulted

Run, monitor and improve

Head of customer relations
I · Informed
Product owner
A · Accountable
Solutions architect
C · Consulted
Technical PM
C · Consulted
Engineers
R · Responsible
Compliance & DPO
C · Consulted
Security
C · Consulted

R ResponsibleA AccountableC ConsultedI Informed· not involved

Where I'd fit

Option A

Lead the architecture

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

Support your architect

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.

Where this goes wrong

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

On the horizon

Changes already announced or under way that affect this design. More in the UK horizon scan.

  1. Early 2027
    Motor finance: the Upper Tribunal hears challenges to the FCA's redress scheme. Depending on the outcome, commission complaints are handled through the scheme or individually within the normal eight weeks.

    Keep commission complaints as their own stream, and plan capacity for both outcomes.

  2. From 1 January 2027
    The FCA's new single complaints return, COM001, replaces five existing returns, with fixed half-year reporting periods starting January to June 2027 (PS25/19).

    Map the classification to the new return's fields before go-live, so reporting comes straight from the case data.

  3. Q1 2027
    The FCA's policy statement on the scope and proportionality of the Consumer Duty (consulted on in CP26/23).

    Keep complaints MI split by product and customer group, so it fits the board report whatever its final shape.

  4. 2026–2027
    Further ombudsman reform: a registration stage piloted from October 2026, starting with fraud and scams, a consultation on case fees, and a 10-year time limit for complaints in the Financial Services and Markets Bill now before Parliament.

    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.

  5. 2026–2027
    The ICO's code of practice on AI and automated decision-making, required by regulations in force since May 2026.

    Keep the classification log, the drafts, the edits and the signatures in a form you could show the ICO.

Questions to ask your partner or vendor

Good answers are specific. Vague answers to any of these are worth following up.

Copy them into your next supplier meeting

  1. How will we measure the complaints we're missing today, not just the ones we already log?
  2. Where do the DISP deadlines live, and what happens to them if the AI is switched off?
  3. How does the assistant know which version of a policy applied on the date of the events?
  4. Which actions can the agents take without a person, and where is that enforced?
  5. Where is our data processed and stored, and is it used to train anyone's model?
  6. What does it cost to run per thousand complaints, including during a sudden spike?

Planning something like this?

Whether you need someone to lead the design or to support the architect you already have, let's talk it through.

Sam Naseem
Sam NaseemBirmingham, UK · UK & Europe
Available now