Discover
Which business decision matters? Who owns it?
SPONSOR + SCOPEENTERPRISE PROCESS INTELLIGENCE FRAMEWORK / AI
AI is the
intervention.
Not the strategy.
EPIF connects a measurable operating problem to the right AI use case - then to evaluation, human authority, monitoring and a Finance-supported result. If simpler process change wins, we say so.
EPIF / DEPLOYMENT PATHBUILT TO PROVE
CONTROL THE RISKDEFEND THE RETURN
VALUE Is it worth doing?FIT Should AI do it?CONTROL Can it operate safely?PROOF Did it improve the business?
THE EPIF DIFFERENCE
Before the model,
know the work.
Many AI programs begin with what a model can do. EPIF begins with what an operating team needs to improve. It reconstructs the real workflow, identifies the friction and compares the full range of interventions before AI is approved.
For investment banks and other regulated institutions, that means the business case and the control case develop together - not as separate projects after a pilot has already launched.
See the intervention sequence ↗︎ALACER MATRIX / EPIF
AI is a measured decision.
The model is not the business case. EPIF helps establish the process baseline, the controls, the accountable owner, and the proof required before AI is allowed to scale.
Explore the outcomes ↗︎SEVEN DECISIONS / ONE TRACEABLE INVESTMENT
From use case
to evidence.
EPIF is not an alternative to AI governance. It is the transformation discipline that takes a use case through its business, delivery and value decisions.
Model
Where do people, exceptions, data and controls interact?
PROCESS + CONTROL MAPMeasure
What is the baseline for cost, time, quality and risk?
EVIDENCE + ROOT CAUSEPrioritize
Does AI beat simpler ways to remove the constraint?
FINANCE + OPTION GATEDesign
What human authority, data, evaluation and fallback are needed?
CONTROLLED TARGET STATEDeliver
Can offline tests and monitored pilots justify production?
GO / NO-GO EVIDENCESustain
Are quality, control performance and net value persistent?
OPERATING OWNERSHIPINTERACTIVE / WHERE EPIF APPLIES
One method.
Real operating challenges.
Select an operating challenge. The use cases below are illustrative opportunities to evaluate - not deployments or guaranteed client results.
EPIF OPPORTUNITY REVIEWILLUSTRATIVE
FINANCIAL CRIME / KYC + EDD
Shorten case assembly.
Protect investigator judgment.
DIAGNOSE
Map source searches, duplicate outreach, data quality and rework before selecting the tool.
POSSIBLE AI ROLE
Summarize approved sources and prepare evidence packages for human review.
CONTROL GATE
Citation checks, privacy boundaries, escalation, human approval and tested error handling.
VALUE TEST
Investigator touch time, QA rework, case quality and net cost per completed review.
CONTROLLED ADOPTION
Governed from
design to run.
AI governance is a separate, necessary discipline. Risk classification, third-party oversight, independent challenge when appropriate, and accountable human authority must be designed into deployment.
For banking environments, our approach can be aligned to applicable supervisory expectations and the NIST AI RMF, including its generative AI profile. Standards and controls are tailored to the use case and jurisdiction.
Explore responsible AI and model risk ↗︎Know Your Agent: when the customer sends software ↗︎
Know every AI use.
Registered use case, owner, purpose, risk tier and applicable control perimeter.
Test against real failure modes.
Quality benchmarks, factual accuracy, bias where relevant, security tests and independent review proportional to risk.
Keep decisions accountable.
Clear human review, override, escalation and stop/rollback authority before go-live.
Make controls visible in production.
Monitoring, issue management, audit trails and trigger-based revalidation or suspension.
THE CFO + CRO TEST
The deployment
isn't the outcome.
Measure the process, not the demo. EPIF agrees a baseline and an attribution approach with Finance before delivery, while Risk defines the control conditions for scale.
How EPIF measures value ↗︎VALUE ACCOUNTABILITYRUN-RATE / ACTUALS
01Gross operational valueSaved effort, capacity, fewer errors
02Less implementation + run costIntegration, licenses, human review, controls
03Net, attributable impactAgreed with Finance, compared to baseline
04Sustained value and riskQuality, exceptions, drift, control effectiveness
Each measure requires a defined source, timeframe and accountable owner. Savings are not counted as realized P&L impact unless Finance validates the attribution.
A PRACTICAL FIRST ENGAGEMENT
EPIF AI Value &
Readiness Assessment.
Start with one material workflow - not a platform RFP. We find the improvement opportunity, determine whether AI is justified and set out what would make deployment approvable and measurable.
Workflow evidence pack
Current-state process, root causes, baseline metrics and data lineage.
Ranked intervention plan
Eliminate, simplify, standardize, integrate, automate or apply AI - with relative risk and dependencies.
Deployment control outline
Use case inventory, tiering, evaluation needs, human authority and fallback design.
Finance-ready measurement plan
Agreed metrics, attribution hypothesis, full run costs and a sustained-value owner.
The deliverable: a defendable go, redesign or no-go decision - with a clear next step.
Discuss an EPIF assessment ↗︎READY WHEN YOU ARE
One operating decision.
A defensible AI strategy.
Show us one workflow under pressure. We'll help determine what is causing the drag, which changes are worth funding and whether AI deserves to be part of the solution.
Start an EPIF conversation ↗︎Our investment banking expertise ↗︎