Client data in too many places
Core banking, lending, cards and wealth platforms each hold part of the client. No adviser or agent sees the whole relationship.
FINANCIAL SERVICES
Financial institutions want the productivity of AI agents without weakening the controls their licence depends on. We help leadership teams decide where Agentforce belongs, prove the business case and govern the programme, designed with compliance and data privacy teams from the first workshop.
The pressure
The ambition for AI is clear. The path through risk, data and legacy process is not.
Risk review slows every change
AI proposals arrive at risk and compliance late and half-formed. Reviews stall, and good ideas wait in a queue.
Cost to serve keeps climbing
Routine enquiries and manual checks absorb skilled people. Service quality depends on headcount the business cannot keep adding.
Pilots without a business case
Teams experiment with AI in isolation. Few pilots have an owner, a measure of value or a route to scale.
Our advisory approach
Four stages. Each one ends with a decision your executive team can take.
01
Discover
We assess client journeys, data, controls and current AI activity with business, risk and technology leaders in the same room.
Outputs
- AI and agent readiness assessment
- Data and control map
- Opportunity longlist
02
Define
We prioritise the use cases worth funding and set out the value, cost and risk of each in terms a board can challenge.
Outputs
- Prioritised use case portfolio
- Business case
- Risk appetite statement for agents
03
Design
We shape the operating model, guardrails and roadmap for Agentforce, designed with compliance and data privacy teams from the first workshop.
Outputs
- Target operating model
- Agent governance framework
- Phased roadmap
04
Direct
We guide, govern and assure the work your teams and chosen partners carry out, and track value against the business case.
Outputs
- Independent programme assurance
- Value realisation tracking
- Executive reporting
Where agents fit
Each one pairs an agent with a clear point of human control.
Client servicing agent
An agent answers routine account and product questions from approved knowledge. Complaints, vulnerable clients and anything involving advice pass to a person.
Adviser meeting preparation
An agent assembles a client summary, recent activity and open actions before each meeting. The adviser decides what to say and recommend.
Onboarding and document chasing
An agent guides applicants through outstanding documents and keeps the case moving. Staff make every identity and eligibility decision.
Case summarisation for operations
An agent summarises long case histories and drafts the next step. The case handler reviews, edits and owns the outcome.
Relationship signals
An agent watches unified client data in Data 360 for life events and service gaps, then suggests an outreach. A relationship manager chooses whether to act.
Policy and procedure assistant
An agent answers staff questions from current internal policy, with sources shown. Policy owners control the content and review what is asked.
Outcomes
We agree the measures before any work starts, and report against them.
Targets are set with each client against their own baseline.
Cost to serve
The effort spent on routine enquiries and manual handling across channels.
Time to onboard
How long a new client waits between application and an active account.
Adviser capacity
The share of adviser time spent with clients instead of on preparation and administration.
Resolution at first contact
How often a client query is settled without a transfer or a follow-up.
Control adherence
How consistently agent actions stay inside the guardrails your risk teams have approved.
Value against business case
Realised benefit compared with the case the board approved, reviewed at each stage.
Engagement pattern
IllustrativeA regional bank preparing for its first service agent
Situation
A mid-sized lender has several AI pilots running in different departments, none with an agreed owner or measure of value. Its contact centre is stretched, and the risk function has been asked to review proposals it had no part in shaping. The executive team wants a first agent in front of clients, and wants confidence that it will stay inside agreed limits. No one is sure which use case should go first.
How we would approach it
- 01We would assess readiness across data, controls, people and current pilots.
- 02We would prioritise use cases with business and risk leaders together.
- 03We would set out a business case, guardrails and a phased roadmap for board approval.
- 04We would then assure the work carried out by the bank and its chosen partners.
What we would measure
- Cost to serve
- Resolution at first contact
- Escalation rate to staff
- Control adherence
An illustrative scenario describing a typical situation. It is not a client case study and reports no results.