Applied AI for financial services
Applied AI, from decision to delivery.
For financial firms where being wrong is expensive and slow is costly. One team, three kinds of work: Decide, Automate, Deliver.
Small and mid-size funds first. Then wider financial services.
- Approved data only
- If a source is not approved, the job cannot reach it.
- Identity on every request
- Every job resolves to the person who started it. Agents inherit that identity.
- Audit trail to sign-off
- Which model, which sources, what was written, and who reviewed it.
- A named owner
- One person signs each conclusion. Accountability is not delegated to a model.
- Containerized sandbox
- Delivered in a sandbox your risk function can inspect.
Controls scale with the risk tier. The tier is agreed at Frame.
The problem
AI pilots stall between a single user demo and a governed system the whole team can use.
The return on AI is still unproven outside the developer community. Most firms report scale potential, not alpha, until the work is configured and governed.
No accountable owner
A model produces an answer. Nobody signs the conclusion.
Not in the workflow
The prototype sits beside the process, not inside it.
No link to goals
No owner, baseline, or measure, so the work cannot be defended at budget time.
The offer
One team, three kinds of work.
Strategy is an optional front end. Decide, Automate, and Deliver are the work. Transfer closes the loop, so the capability stays with your team.
See the services →Strategy
OptionalBusiness goals, ROI definition, and KPIs, so each project ties back to the business.
Goals and KPI set · Ranked candidate list · Business case
Decide
Agentic research with verified conclusions and a named expert owner.
Bespoke rates or commodities factor model · Deal sourcing and screening
Automate
AI inside existing workflows, with human review at the exception.
KYC screening · ISDA confirmation matching · Candidate and PM sourcing and ranking
Deliver
Agile prototype to production under financial services governance, on containerized infrastructure.
Data · Application development · DevOps · Testing
Transfer
Operating model, roles, runbooks, training, and handover, tied back to the goals set at the start.
Method · Roles · Runbooks · Training
Growth
A decision reaches a conclusion faster, or a sourcing funnel widens.
Efficiency
A workflow runs with less manual handling and fewer breaks.
Risk and control
The control environment improves, and the evidence is there when it is asked for.
Verified agentic research
Answers you can defend.
For decisions where being wrong is expensive. Agents do the discovery, the drafting, and the execution. A named expert owns the verification and the conclusion.
The output is a decision record: the claim, the evidence, the verification, the owner, and the decision. Claims without a locator are labelled as hypotheses or removed.
Built for investment, commodity, and technical teams.
Does a common factor drive long-end yield co-movement?
- Claim
- Common factor share: 20 to 80%
- Evidence
- Primary sources, locator per claim
- Verification
- Independent pass, dropped claims named
- Owner
- Named macro expert
- Decision
- One testable block registered
Every conclusion carries a kill criterion. The record shows what was refused, not only what survived.
Path to alpha
What scaling a model looks like.
A factor model is a useful example. Each step is work, not a promise. Illustrative, not client results.
- 01
Research and build
Frame the question, gather the evidence, build the model, and verify the claims.
- 02
Daily run
The model runs on approved data on a schedule, with an owner and an audit trail.
- 03
Trade ideas
The output becomes candidates a portfolio manager can review, not a signal that trades itself.
- 04
Backtest
Test the candidates against history, with the assumptions and the failures written down.
- 05
Track record
Run it forward, measure it, and keep the record. A track record is earned, not claimed.
Maturity ladder
-
01
Productivity
One person does one task faster, with a verified output.
-
02
Process automation
One workflow runs for the team, with exceptions handled.
-
03
Cross-team scale
Shared data, identity, and governance across desks.
-
04
Alpha
A measured edge that survives out-of-sample and cost.
The rates model has no published track record, so no returns are claimed here.
The harness
A tested toolkit, not a blank page.
The harness is the toolkit behind the work. Four components, tested on live cases. Use them as they are, adapt them, or bring your own. We start from your goals, not our tool.
See the harness →Research and decision engine
Runs the evidence, the verification, and the decision record. Every claim carries a locator; every conclusion carries a kill criterion.
Delivery framework
Plan, build, test, and ship the workflow with an audit trail. The same loop the practice runs, available to your team.
Governance framework
Identity, approved data, logging, and the controls for each risk tier. Inspectable by your risk function.
Managed containerized sandbox
The environment your team and the agents share. Isolated, logged, and reviewed before the first job.
Delivery runs with a small senior team and an established financial services partner. The partner is not named here.
Who it is for
Small and mid-size funds first.
Firms under about 250 people, especially under 100, where the COO, CTO, or business head needs an expert to define the strategy and then help carry it out.
Banks, insurers, and wealth managers come later, when the workflow evidence is stronger.
Large consultancies
Heavy teams and strategy decks. Limited hands-on delivery, and the people who wrote the deck move on.
IT service providers
Delivery capacity, little financial services depth. The best people leave within months.
Point-solution vendors
A tool for one task. No operating model, no link to goals, no transfer.
Our model
One senior team, three kinds of work, delivery and transfer. The work stays in your firm.
How we work together
We do, you do.
Collaboration is explicit at every stage. No black box, no offshore handover.
| Stage | We do | You do |
|---|---|---|
| Frame | Scope the decision or workflow, the success test, and the control requirements. | Name the owner, open data access, and agree the test. |
| Sprint | Build the prototype, verify the evidence, and run the reviews. | Use it on the live case and decide at the gate. |
| Production | Integrate, instrument, and document under your governance. | Provide the change process, security review, and production owner. |
| Transfer | Hand over the method, roles, and runbooks. | Run the next cycle and own the model. |
After Transfer, we check in every two weeks as models and workflows change.
See the full method →Governance
Controls scale with the risk tier.
Not every workflow needs the same controls. We agree the tier at Frame and apply technical, model, and change governance at that level.
Read the governance posture →| Tier | Technical | Model | Change |
|---|---|---|---|
| Ad hoc prototype One analyst, one question | Sandbox, approved data, identity | Prompt and output review | Owner sign-off |
| Daily personal use One person, repeated work | Logging, retention, cost limits | Eval set, drift check | User acceptance |
| Business critical One workflow, a team | Integration, monitoring, access control | Validation, challenger, kill switch | Change board, rollback |
| Shared across the team Many users, one environment | Tenancy, audit export, incident process | Ongoing monitoring, independent review | Release process, training |
Ways to work
Strategy first, or project first.
Both start with one decision or workflow. The difference is whether the goals are already defined.
Strategy first
When the goals, ROI, or KPIs are undefined. We define them, rank the candidate work, and then start one project.
A board or COO who wants a plan before spend.
Start here →Project first
When a live decision or workflow already exists. We frame it, run a 2 to 4 week sprint, then produce and transfer.
A team with a problem that has a date.
Start here →The ladder
- 01
Sprint
A live decision or workflow, 2 to 4 weeks, fixed scope.
- 02
Programme
Continuous work at the same standard, with check-ins.
- 03
Configured framework
Your data, priors, and evaluations encoded in the harness.
- 04
Bespoke
Specialist knowledge or tooling on a defined problem.
- 05
Embedded
Operating model, roles, and governance redesigned around the work.
No published price. The fee is scoped after Frame.
Next step
Bring one decision or workflow.
A short sprint, a working prototype, and a method your team can run next. If the goals are not defined yet, start with strategy.
Or email hello@advancedapplied.ai.