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Managing Director

Originate new deal mandates and win client engagements

Enhances✓ Available Now

What You Do Today

Identify and pursue new advisory mandates — calling on corporate executives, private equity sponsors, and board members. Pitch your firm's capabilities and win competitive processes against other banks.

AI That Applies

AI identifies potential deal triggers — earnings misses, activist investors, CEO changes, expiring debt — that create advisory opportunities. Prepares briefing materials and pitch templates.

Technologies

How It Works

The system ingests customer interaction data — transactions, communications, behavioral signals, and profile information. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — advisory opportunities — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Deal origination becomes more data-driven. AI surfaces opportunities from signals you wouldn't have time to monitor manually.

What Stays

Winning a mandate requires trust built over years of relationship building, industry expertise, and the ability to read what a CEO really wants.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for originate new deal mandates and win client engagements, understand your current state.

Map your current process: Document how originate new deal mandates and win client engagements works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Winning a mandate requires trust built over years of relationship building, industry expertise, and the ability to read what a CEO really wants. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support CRM platforms tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long originate new deal mandates and win client engagements takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your board chair or lead independent director

What are the top 5 reasons customers contact us, and which of those could be resolved without a human?

They shape expectations for how AI appears in governance

your CTO or CIO

How do we currently measure service quality, and would AI-assisted responses change that measurement?

They own the technology infrastructure that enables AI adoption

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.