Services · Mobile app development · Banking AI agents
Codeeo provides banking AI agent development London firms can put in front of a risk committee without apology. We build agents for retail banks, private banks, branches of overseas groups and authorised fintech lenders in the capital: agents that gather onboarding evidence, prepare sanctions alerts, answer payment queries and draft complaint files. Each one hands a reasoned recommendation to a named person, logs every step, and works inside the permissions your security team grants.
London banking runs at City volume with City scrutiny. An agent that saves an analyst an hour is only useful if the audit trail behind that hour survives a skilled person review, so we treat traceability as a feature from the first sprint. That also makes it easier to extend the agent later, because every new permission is added against a documented baseline.
200+ companies servedFrom a first store to an ADX listed developer
Agents London banks ask for
London concentrates the hardest version of almost every banking task. Corporate clients arrive with ownership chains that cross several jurisdictions. Payments touch correspondent banks in other time zones. Private clients expect a relationship manager who already knows the file. Regulatory output from the FCA in Stratford and the PRA at Threadneedle Street lands every week, and someone has to read it.
An AI agent is a model that can use tools: it searches your systems, reads documents, fills in a structured template and asks a person when it reaches the edge of its permissions. The agents below are the ones that suit London workloads best. None of them approves an account, releases a payment or closes a complaint on its own. They do the gathering, the cross-checking and the first draft, so your specialists spend their time on judgement rather than copy and paste.
The agent pulls Companies House filings and the register of people with significant control, compares them with what the client supplied, and traces ownership through overseas holding companies where documents allow. Gaps, mismatches and unverified links go into a checklist for the onboarding analyst rather than being guessed.
Analysts start each case with a complete, sourced ownership picture.
For each screening hit, the agent gathers the list entry, the customer record and any transaction context, scores name and date of birth similarity, and drafts a disposition note that cites OFSI guidance where relevant. The analyst confirms or rejects; the agent never clears an alert itself.
Faster disposition of false positives, with reasoning kept on file.
Missing beneficiary details, returned funds and recall requests eat hours in London payment teams. The agent reads ISO 20022 message data, checks the status trail, drafts the query to the correspondent and tracks the reply, so investigators handle exceptions instead of chasing paperwork.
Payment queries answered sooner, with fewer stalled cases.
Before a private client meeting in Mayfair or a call with a corporate treasurer, the agent assembles recent activity, open service requests, upcoming maturities and notes from previous conversations into a short brief. It flags anything that touches suitability so the banker, not the model, decides what to raise.
Bankers walk into meetings prepared in minutes, not an afternoon.
The agent watches policy statements, consultation papers, Dear CEO letters and Handbook notices, summarises what changed, and maps each change to the internal policies and owners it affects. Compliance reviews the mapping and assigns actions; the agent keeps the tracker current.
Regulatory change reaches the right owner the week it is published.
When a complaint arrives by email, chat or phone note, the agent identifies the product, gathers the account history, flags signs of vulnerability, and drafts a timeline against DISP deadlines. Handlers write the final response and the agent checks it mentions Financial Ombudsman Service referral rights.
Complaint files built consistently, and deadlines visible from day one.
Commuters and residents report authorised push payment scams across every channel. The agent collects the payment details, the customer account of events and any Confirmation of Payee result, checks the claim against your reimbursement policy, and prepares the case for an investigator. Customers who appear vulnerable or distressed are routed to a person straight away.
Scam claims reach investigators complete, so reimbursement decisions are made sooner.
London customers bank in dozens of languages. A customer facing agent can answer balance, card and account servicing questions in the languages you choose, verify identity through your existing authentication, and pass anything involving money movement, disputes or distress to a person with the conversation attached.
Routine questions handled at any hour, with clean handover when it matters.
The agent reads process maps, supplier contracts and incident records and keeps the dependency picture behind each important business service up to date. When a supplier or system changes, it highlights which impact tolerance scenarios need retesting and drafts the note for the resilience team.
Resilience mapping that stays current between annual self assessments.
Every agent we deploy reports into one console: the actions it took, the sources it used, overrides by staff, error rates against the evaluation set, and the senior manager it sits under. Model risk and internal audit can sample cases without asking engineers for logs.
Second and third line can see exactly what each agent did.
Who this suits
The right first agent depends less on the size of your balance sheet than on where your people lose time. These are the London situations we see most often, and how an agent fits each one. Good AI agent development for banks in London starts with a narrow, measurable task that a named team already owns, because that team will judge whether the agent helps. If your situation is different, discovery will show that quickly, and we will say so if an agent is the wrong tool for the problem.
City branches often run lean operations with group systems designed elsewhere. An agent can bridge local requirements, such as UK sanctions screening notes or PRA reporting inputs, and group platforms without a full system rebuild. We plan data flows so that information leaving the UK follows your group transfer arrangements and UK GDPR, and we document which decisions stay with London staff.
Useful where group IT cannot prioritise UK specific changes.
Client service is personal, files are long and relationship managers carry heavy portfolios. Briefing agents, document chasing and meeting note summaries return time to bankers without putting a chatbot between them and their clients. Anything near investment advice remains with qualified staff, and the agent is configured to stop and flag rather than suggest.
Agents stay behind the banker, never in front of the client.
Growth outpaces headcount in operations, complaints and financial crime. An agent built on your existing stack can absorb document checks, arrears contact preparation and complaint drafting while you hire. We work with your engineers in your repositories, so the agent becomes part of your codebase rather than a vendor box nobody can open.
Big programmes need a working proof inside policy, not a slide deck. We build a narrowly scoped agent against one process, with the evaluation evidence, model documentation and control mapping your model risk function expects, so the pilot can pass internal approval and scale from there.
A pilot designed to pass governance, not just impress a steering group.
Working together
Codeeo has no London office. Our team works remotely with London clients, with discovery, design reviews and demos held by video call and documents shared in your own collaboration tools. We are a team of 80+ across Dubai, Riyadh and Karachi, have delivered 200+ projects across the UAE and the US, and are rated 4.7 from 23 Google reviews.
Most banks start with a fixed scope pilot on a single process. After approval, work continues on a retainer for new agents and model updates, or through a dedicated team that sits inside your delivery governance and change calendar.
A defined build with a deadline
We agree what the product has to do, write it down with a price and a date, and build exactly that. Changes are priced before they are made, not discovered on the invoice.
A product that keeps evolving
Named engineers who work your hours, join your standups and stay on the codebase. You direct the backlog; we own the quality of what ships.
Something live that needs looking after
A monthly block of hours for improvements, fixes and the small requests that otherwise wait months. Unused hours carry for a quarter.
Technology
Model choice follows your data policy: commercial models through UK or EU cloud regions, or open weight models in your own tenancy where data cannot leave it. We use typed tool definitions, retrieval over approved document stores, and integrations with the case, screening and core banking systems your London teams already run. Where a London bank already has an enterprise AI platform approved by its architecture board, we build on that platform instead of introducing a second one, which shortens security review and keeps support simple for your own engineers.
01Mobile
02Data and cloud
03Marketing and tracking
Remotely, by video call, inside your own environment.
Our engineers work in your cloud tenancy or development environment under your access controls, so data does not move to our systems. Workshops, sprint reviews and demos happen by video call, and every decision is written down in a shared document. This suits most London banks well, since their own delivery teams are usually spread across several sites and already work this way.
Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.
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