Appendix E: Companion Indicator Statistical Analyses

Part 1

Analysis: Active Engagements

Analysis: Active Engagements

Part 1, 4.2.3; Introduction, 4.4.2; Part 1, 2

Part 1

Analysis: Four Measures

Analysis: Four Measures

Part 1, 4.2.1

Part 1

Analysis: Mean Quintiles

Analysis: Mean Quintiles

Part 1, 4.2.2

Part 1

Analysis: Measured Return

Analysis: Measured Return

Part 1, 3.3.1; Introduction, 4.5.5

Part 1

Analysis: Net Associations

Analysis: Net Associations

Part 1, 4.3.1

Part 1

C031

What type of a bank is the customer?

Part 1, 5.1.1

Part 1

C032

What is the outsourcing type?

Part 1, 5.3.1

Part 1

C033

Is the outsourcing engagement Corporate Functional, or Line of Business Operational?

Part 1, 5.3.2

Part 1

C035

How long ago did this specific engagement start, in months?

Part 1, 1.1.2

Part 1

C036

What stage is the engagement in?

Part 1, 1.1.1; Introduction, 4.5.2

Part 1

C037

How many months has the engagement been in its current stage?

Part 1, 1.1.3

Part 1

C038

Per the current plan, how many months from today until the engagement reaches Production/Delivery?

Part 1, 1.1.4

Part 1

C039

If the engagement has not been canceled, how likely is the customer to cancel the engagement?

Part 1, 2.2.1

Part 1

C040

How many people are on the vendor team for this engagement today?

Part 1, 5.6.1

Part 1

C041

What was the peak vendor team headcount on this engagement to date?

Part 1, 5.6.2

Part 1

C042

Per the current plan, how many people will be on the vendor team 12 months from now?

Part 1, 5.6.3

Part 1

C043

How many AI agents are running in production on this engagement today?

Part 1, 1.2.1

Part 1

C044

What is the pricing model for this engagement?

Part 1, 5.4.1

Part 1

C045

What is the contract term of this engagement, in months?

Part 1, 5.4.2

Part 1

C046

What is the annual contract value of this engagement, in USD?

Part 1, 5.4.3

Part 1

C047

I know the KPIs the customer uses to measure success.

Part 1, 3.2.4

Part 1

C048

The customer is happy with the performance of the engagement at this stage.

Part 1, 3.1.2

Part 1

C049

The engagement is meeting delivery dates successfully.

Part 1, 3.2.1

Part 1

C050

The engagement is within budget.

Part 1, 3.2.2

Part 1

C051

The engagement is not achieving stated KPIs.

Part 1, 3.2.3

Part 1

C062

What is the customer's approximate total asset size, in USD?

Part 1, 5.1.2

Part 1

C063

Does the customer operate its own global capability centers?

Part 1, 5.1.3

Part 1

C064

How many months has your employer been serving this customer across all work, not just this engagement?

Part 1, 5.2.1

Part 1

C065

How many agentic AI outsourcing engagements does your employer run concurrently with this customer today?

Part 1, 5.2.2

Part 1

C066

The customer is scaling their agentic AI outsourcing engagements.

Part 1, 5.1.5

Part 1

C067

The customer is increasing the number of agentic AI outsourcing engagements.

Part 1, 5.1.6

Part 1

C068

The customer is shifting more work to their global capability centers.

Part 1, 5.1.4

Part 1

C076

What type of company is your employer?

Part 1, 5.5.1

Part 1

C077

Approximately how many employees does your employer have worldwide?

Part 1, 5.5.2

Part 1

C078

How many years has your employer been delivering agentic AI outsourcing?

Part 1, 1.2.2

Part 1

C079

How many agentic AI engagements does your employer run for banks today?

Part 1, 5.5.3

Part 1

Field: Bank Type

Field: Bank Type

Part 1, 5.1.1

Part 1

Field: Class of Work

Field: Class of Work

Part 1, 5.3.2

Part 1

Field: Engagement Age

Field: Engagement Age

Part 1, 1.1.2

Part 1

Field: Engagement Phase

Field: Engagement Phase

Part 1, 1.1.1

Part 1

Field: Headcount

Field: Headcount

Part 1, 5.6.1

Part 1

Field: Outsourcing Type

Field: Outsourcing Type

Part 1, 5.3.1

Part 1

Field: Use Case

Field: Use Case

Part 1, 5.3.3

Part 1

Measure: Cancellation

Measure: Cancellation

Part 1, 2.1.1

Part 1

Measure: Indicator Mean

Measure: Indicator Mean

Part 1, 4.1.1; Introduction, 4.5.1

Part 1

Measure: Satisfaction

Measure: Satisfaction

Part 1, 3.1.1; Introduction, 4.5.3

Part 2

C093

Compared to 5 years ago, is my employer more or less prepared to manage outsourcing engagements?

Part 2, 4.8.1

Part 2

C094

Rate the quality of the customer's data across the systems this engagement depends on.

Part 2, 2.1.1

Part 2

C095

Rate how accessible the customer's data is to this engagement when and where the work requires it.

Part 2, 2.1.2

Part 2

C096

Rate how well the customer's data is normalized, with consistent formats and definitions across source systems.

Part 2, 2.1.3

Part 2

C097

Rate the maturity of the customer's data governance over the data this engagement uses.

Part 2, 2.1.4

Part 2

C098

Rate how well the customer's legacy systems support the integration this engagement requires.

Part 2, 2.2.1

Part 2

C099

Rate the readiness of the customer's technical infrastructure to support the agentic AI this engagement deploys.

Part 2, 2.2.2

Part 2

C100

Rate how completely the customer's processes are mapped and documented to the depth agentic AI requires.

Part 2, 2.3.1

Part 2

C101

Rate the maturity of the customer's processes in scope, meaning how standardized and repeatable they are.

Part 2, 2.3.2

Part 2

C102

Rate how consistently the customer performs the same processes across its business units and regions.

Part 2, 2.3.3

Part 2

C103

Rate the customer's willingness to redesign processes for agentic AI rather than automate them as they are.

Part 2, 2.3.4

Part 2

C104

Rate the agentic AI knowledge and skills of the customer staff working with this engagement.

Part 2, 2.4.2

Part 2

C105

Rate the effectiveness of the customer's management of its side of this engagement.

Part 2, 2.5.1

Part 2

C106

Rate the availability of the customer's subject matter experts when this engagement needs them.

Part 2, 2.4.3

Part 2

C107

Rate the customer organization's readiness to absorb the changes to daily work that agentic AI introduces.

Part 2, 2.4.1

Part 2

C108

Rate the customer's ability to provision the system access and identities that AI agents require.

Part 2, 2.7.1

Part 2

C109

Rate how quickly the customer responds when this engagement raises issues that need customer action.

Part 2, 2.5.2

Part 2

C110

Rate how well the customer's change control process handles the changes this engagement requires.

Part 2, 2.6.3

Part 2

C111

Rate the customer's capacity to govern and oversee the risks of AI agents doing this work.

Part 2, 2.6.2

Part 2

C112

Rate how clearly ownership and accountability for AI are assigned inside the customer organization.

Part 2, 2.6.1

Part 2

C113

Rate the stability of the customer's business case and ROI definition for this engagement.

Part 2, 2.8.1

Part 2

C115

Rate the overall effectiveness of your employer's top leadership team.

Part 2, 4.1.1

Part 2

C116

Rate how well your employer is transforming its commercial model as agentic AI reduces the billable human effort it sells today.

Part 2, 4.1.2

Part 2

C117

Rate how well your employer's internal management processes have been redesigned for agentic AI delivery rather than traditional staffed delivery.

Part 2, 4.2.1

Part 2

C118

Rate the effectiveness of your employer's process and leadership development programs.

Part 2, 4.5.2

Part 2

C119

Rate your employer's ability to manage agentic AI outsourcing engagements end to end.

Part 2, 4.2.2

Part 2

C120

Rate the depth of your employer's knowledge of the financial industry.

Part 2, 4.3.1

Part 2

C121

Rate your employer's ability to manage agentic AI outsourcing engagements for global banks in particular.

Part 2, 4.2.3

Part 2

C122

Rate your employer's current supply of qualified agentic AI talent against what its engagements need.

Part 2, 4.5.1

Part 2

C123

Rate the adequacy of your employer's investment in training its workforce.

Part 2, 4.5.3

Part 2

C124

Rate how well your employer's training programs build practical agentic AI skills.

Part 2, 4.5.4

Part 2

C125

Rate how well your employer's training programs build financial industry knowledge.

Part 2, 4.5.5

Part 2

C126

Rate the maturity of your employer's playbook for taking agentic use cases from concept to governed production.

Part 2, 4.6.1

Part 2

C127

Rate your employer's quality assurance capability for agents whose outputs are not identical every run.

Part 2, 4.6.2

Part 2

C128

Rate your employer's ability to price agentic work profitably when billable hours no longer measure the value delivered.

Part 2, 4.1.3

Part 2

C129

Rate how well the technical platforms your employer builds or licenses are optimized for agentic AI outsourcing.

Part 2, 4.6.3

Part 2

C130

Rate your employer's readiness to take accountability when an agent it operates makes a costly error.

Part 2, 4.7.1

Part 2

C131

Rate the depth of your employer's knowledge of agentic AI.

Part 2, 4.3.2

Part 2

C132

Rate the depth of your employer's experience running agentic AI systems in live production, beyond pilots.

Part 2, 4.4.1

Part 2

C133

Rate your employer's ability to operate large numbers of agents in production, including monitoring and exception handling.

Part 2, 4.4.2

Part 2

C134

Rate your employer's overall qualification to deliver elite agentic AI outsourcing services to banks.

Part 2, 4.2.4

Part 2

C136

Rate how effectively the customer and vendor jointly manage this engagement now that agents perform part of the work.

Part 2, 3.1.1

Part 2

C137

Rate how clearly the two firms have settled who decides what agents may do without human approval.

Part 2, 3.1.2

Part 2

C138

Rate how clearly ownership of each workflow step is assigned when agents, vendor staff, and customer staff work in the same process.

Part 2, 3.1.3

Part 2

C139

Rate how clearly accountability lands on one firm when an agent's action causes a problem in this engagement.

Part 2, 3.1.4

Part 2

C140

Rate how well the two firms maintain a single shared view of the risks that agent work introduces.

Part 2, 3.2.1

Part 2

C141

Rate how effectively the two firms manage issues arising from agent work as one team rather than through two separate processes.

Part 2, 3.2.2

Part 2

C142

Rate how well the speed of joint issue resolution matches the speed at which agent-caused problems can spread.

Part 2, 3.2.3

Part 2

C143

Rate how quickly the two firms together can stop an agent that is behaving badly in live operations.

Part 2, 3.2.4

Part 2

C144

Rate how well the joint change control process keeps pace with the speed of agent behavior changes.

Part 2, 3.3.1

Part 2

C145

Rate how well agent updates made by one firm become visible to the other firm before they take effect.

Part 2, 3.3.2

Part 2

C146

Rate how well the two firms jointly govern changes agents make to their own behavior between formal releases.

Part 2, 3.3.3

Part 2

C147

Rate how well human review points are placed across the two firms at the moments where agent errors would matter most.

Part 2, 3.4.1

Part 2

C148

Rate how well joint human review capacity keeps up with the volume of output the agents produce.

Part 2, 3.4.2

Part 2

C149

Rate how much genuine scrutiny agent outputs receive at human review points rather than routine approval.

Part 2, 3.4.3

Part 2

C150

Rate how reliably the joint quality assurance loop catches agent errors before they reach live operations.

Part 2, 3.4.4

Part 2

C151

Rate how well the quality measures both firms use capture the kinds of errors agents actually make.

Part 2, 3.4.5

Part 2

C152

Rate how fully each firm can see what the other firm's agents actually did when questions arise.

Part 2, 3.5.1

Part 2

C153

Rate how closely the speed of joint decision making matches the speed at which the agents act.

Part 2, 3.5.2

Part 2

C154

Rate how well today's joint governance model fits work performed by agents rather than work performed by people.

Part 2, 3.5.3

Part 2

C155

Rate how ready the joint management model is for the level of agent autonomy you expect in this engagement within two years.

Part 2, 3.5.4

Part 2

C157

Rate the factual reliability of the AI tools' outputs on this engagement before any human review.

Part 2, 5.2.1

Part 2

C158

Rate the accuracy of citations, references, and quotations the tools produced against the real sources.

Part 2, 5.2.2

Part 2

C159

Rate the consistency of the tools' outputs when given the same input and instructions more than once.

Part 2, 5.2.3

Part 2

C160

Rate the end-to-end reliability of the tools on multi-step tasks, from first step to finished output.

Part 2, 5.2.4

Part 2

C161

Rate the predictability of the tools' token consumption for a given volume of work.

Part 2, 5.4.1

Part 2

C162

Rate the efficiency of the tools' token use, considering retries, loops, and reprocessing needed to complete work.

Part 2, 5.4.2

Part 2

C163

Rate how completely the tools kept each client's and each session's information isolated from every other client and session.

Part 2, 5.5.1

Part 2

C164

Rate how reliably the tools retained instructions and constraints given earlier in long tasks and sessions.

Part 2, 5.3.1

Part 2

C165

Rate how completely the tools captured material facts located anywhere in long documents, including mid-document content.

Part 2, 5.3.2

Part 2

C166

Rate the integrity of the tools' persistent memory against contamination by incorrect or malicious content encountered during work.

Part 2, 5.3.3

Part 2

C167

Rate the tools' resistance to hostile instructions embedded in the content they read and process.

Part 2, 5.5.3

Part 2

C168

Rate how consistently the agents took only intended and authorized actions when operating connected tools and systems.

Part 2, 5.6.1

Part 2

C169

Rate how safely the tools handled sensitive data, with no exposure through outputs, logs, or connected systems.

Part 2, 5.5.2

Part 2

C170

Rate how reliably the tools' built-in guardrails and safety controls held during production use.

Part 2, 5.6.2

Part 2

C171

Rate the overall production readiness of the AI tools for bank-grade work as experienced on this engagement.

Part 2, 5.1.1

Part 2

C172

Rate how accurately the tools' own reports of success or failure matched the actual outcomes of their work.

Part 2, 5.8.1

Part 2

C173

Rate the tools' ability to explain and evidence how each output was produced, at the depth an audit requires.

Part 2, 5.8.2

Part 2

C174

Rate how well the tools supported reliable testing, meaning correct behavior could be proven before work went live.

Part 2, 5.7.1

Part 2

C175

Rate the stability of the tools' behavior over the engagement when nothing changed on the engagement side.

Part 2, 5.7.2

Part 2

C176

Rate the quality of the tools' logs, traces, and usage telemetry for detecting and diagnosing failures.

Part 2, 5.8.3

Part 2

C178

Rate how well the agents on this engagement are protected from breaking silently when a third party changes something without warning.

Part 2, 6.2.1

Part 2

C179

Rate the quality of the fallback the engagement has ready when a critical third-party feed, platform, or model stops working.

Part 2, 6.7.1

Part 2

C180

Rate the security posture of the third-party tools, platforms, and sub-processors the engagement's agents connect to.

Part 2, 6.6.1

Part 2

C181

Rate the quality of advance notice third-party providers give before changes that can affect the agents on this engagement.

Part 2, 6.1.1

Part 2

C182

Rate how reliably word of an upcoming third-party change reaches the people who operate the affected agents in time to act.

Part 2, 6.1.2

Part 2

C183

Rate the engagement's monitoring for unannounced changes in the third-party APIs, data feeds, and models its agents depend on.

Part 2, 6.2.2

Part 2

C184

Rate how well the contracts with third-party providers deal with provider changes that can break the agents on this engagement.

Part 2, 6.4.1

Part 2

C185

Rate how well the engagement absorbs model version deprecations and retirements forced by model providers.

Part 2, 6.3.2

Part 2

C186

Rate the availability of true machine interfaces, rather than screens built for humans, across the third-party systems the agents must use.

Part 2, 6.5.1

Part 2

C187

Rate the stability of the third-party APIs and data structures the agents depend on, from one provider release to the next.

Part 2, 6.3.1

Part 2

C188

Rate the quality of the data arriving from third-party feeds, judged by whether agents can use it without human cleanup.

Part 2, 6.5.2

Part 2

C189

Rate how well third-party rate limits and quotas hold up under the volume the agents on this engagement generate.

Part 2, 6.5.3

Part 2

C190

Rate the engagement's ability to still perform by hand the manual workarounds that once absorbed third-party quirks and breakage.

Part 2, 6.7.2

Part 2

C191

Rate how completely the engagement knows where humans used to quietly fix third-party data and interface problems before agents took over.

Part 2, 6.7.3

Part 2

C192

Rate how deliberately the quiet human fixes for third-party quirks were replaced with explicit checks when agents took over the work.

Part 2, 6.7.4

Part 2

C193

Rate how well the engagement manages its dependence on a small number of model and cloud providers.

Part 2, 6.6.2

Part 2

C194

Rate how well this engagement could keep operating if it had to switch its primary model or cloud provider.

Part 2, 6.6.3

Part 2

C195

Rate how well third-party licenses on this engagement cover work done by agents rather than named human users.

Part 2, 6.4.2

Part 2

C196

Rate how completely the engagement has mapped every third and fourth party its agents depend on, down the full chain.

Part 2, 6.8.1

Part 2

C197

Rate how well the engagement manages agent dependence on gated external rails such as payment networks and regulatory submission systems.

Part 2, 6.8.2

Part 4

Analysis: Experience by Intent

Analysis: Experience by Intent

Part 4, 6.1.1

Part 4

C005

What is your role on this engagement?

Part 4, 1.1.1

Part 4

C007

How many years of experience do you have in your career?

Part 4, 1.2.1

Part 4

C008

How many years of experience do you have with agentic AI?

Part 4, 1.3.1

Part 4

C009

How many years have you been working in the outsourcing industry?

Part 4, 1.2.2

Part 4

C010

How many years have you been working within the financial industry?

Part 4, 1.2.3

Part 4

C011

How many agentic AI outsourcing engagements have you worked on across your career, including this one?

Part 4, 1.3.2

Part 4

C012

How well do you know the financial industry?

Part 4, 1.4.1

Part 4

C013

How well do you know agentic AI specific to the financial industry?

Part 4, 1.4.2

Part 4

C014

Rate your overall agentic AI expertise.

Part 4, 1.4.3

Part 4

C015

What professional certifications do you have?

Part 4, 1.5.1

Part 4

C016

What AI certifications do you have?

Part 4, 1.5.2

Part 4

C017

Where did you gain your AI knowledge?

Part 4, 1.5.3

Part 4

C018

How happy are you with your current job?

Part 4, 3.1.1

Part 4

C019

How likely are you to leave your current job in the next 12 months?

Part 4, 5.1.1; Introduction, 4.5.4

Part 4

C020

How happy is your extended team with the current engagement?

Part 4, 3.1.2

Part 4

C021

How likely are members of your current team to leave their jobs in the next 12 months?

Part 4, 5.1.2

Part 4

C022

Compared to 5 years ago, I am happier with the work I am doing now.

Part 4, 3.2.1

Part 4

C023

Compared to 5 years ago, I am more likely to seek a new job.

Part 4, 5.2.1

Part 4

C024

Compared to 5 years ago, the team I work with seems to be happier.

Part 4, 3.2.2

Part 4

C025

Compared to 5 years ago, the team I work with is more likely to seek a new job.

Part 4, 5.2.2

Part 4

C026

I want to continue working on projects in the global financial industry.

Part 4, 5.3.1

Part 4

C027

I would prefer to work directly for a bank in one of their global capability centers.

Part 4, 5.3.2

Part 4

C028

Working directly for a bank would be better than working for an outsourcing vendor.

Part 4, 5.3.3

Part 4

C069

I trust the customer.

Part 4, 4.1.1

Part 4

C070

The customer knows and cares about me.

Part 4, 4.1.2

Part 4

C071

I talk with peers inside the customer regularly.

Part 4, 4.2.1

Part 4

C072

I talk with engagement management inside the customer regularly.

Part 4, 4.2.2

Part 4

C073

I talk with the customer's leadership team regularly.

Part 4, 4.2.3

Part 4

C074

I know how the customer feels about my team.

Part 4, 4.1.3

Part 4

C075

I know how the customer feels about the engagement I am on.

Part 4, 4.1.4

Part 4

C080

My manager is effective.

Part 4, 2.1.1

Part 4

C081

My manager knows the financial industry well.

Part 4, 2.1.2

Part 4

C082

My manager knows agentic AI well.

Part 4, 2.1.3

Part 4

C083

My manager cares about me.

Part 4, 4.3.1

Part 4

C084

My manager cares about the larger team.

Part 4, 4.3.2

Part 4

C085

My manager knows how to manage agentic AI outsourcing engagements.

Part 4, 2.1.4

Part 4

C086

My manager knows how to manage agentic AI outsourcing engagements for global banks.

Part 4, 2.1.5

Part 4

C087

My employer cares about me.

Part 4, 4.4.1

Part 4

C088

My employer cares about the team.

Part 4, 4.4.2

Part 4

C089

My employer's top leadership team cares about my wellbeing and development.

Part 4, 4.4.3

Part 4

C090

I trust my employer.

Part 4, 4.4.4

Part 4

C091

I trust my manager.

Part 4, 4.3.3

Part 4

C092

I am being used effectively by my employer.

Part 4, 4.4.5

Part 4

Field: CME Respondents

Field: CME Respondents

Part 4, 1.1.1

Part 4

Field: IC Respondents

Field: IC Respondents

Part 4, 1.1.1

Part 4

Field: PD Respondents

Field: PD Respondents

Part 4, 1.1.1

Part 4

Field: Total Respondents

Field: Total Respondents

Part 4, 1.1.1

Part 5

Analysis: Alterations by Role

Analysis: Alterations by Role

Part 5, 2.1.1

Part 5

Analysis: Manager Alterations

Analysis: Manager Alterations

Part 5, 2.2.1

Part 5

C052

The dashboard and performance reports given to the customer are accurate.

Part 5, 1.4.1

Part 5

C053

The vendor manipulates the dashboard and performance reports given to the customer.

Part 5, 1.4.2

Part 5

C054

Compared to 5 years ago, is manipulation of the dashboards and performance reports given to the customer more or less common now?

Part 5, 1.4.3

Part 5

C057

I fully understand how these laws, regulations, and similar affect the outsourcing engagement.

Part 5, 7.1.1

Part 5

C058

My management team fully understands these laws, regulations, and similar, and how they affect the engagement.

Part 5, 7.1.2

Part 5

C059

The customer's team actively discusses these laws, regulations, and similar with our team.

Part 5, 7.2.1

Part 5

C060

The training available to me effectively teaches me about these laws, regulations, and similar.

Part 5, 7.3.1

Part 5

C199

I have altered client-provided data

Part 5, 1.1.1

Part 5

C200

I discussed the data alteration with internal management

Part 5, 4.1.1

Part 5

C201

I or my management discussed data alteration with the client

Part 5, 4.2.1

Part 5

C203

My greater team regularly alters client provided data.

Part 5, 1.1.2

Part 5

C205

I have altered client processes

Part 5, 1.2.1

Part 5

C206

I discussed the process alteration with internal management

Part 5, 4.1.2

Part 5

C207

I or my management discussed process alteration with the client

Part 5, 4.2.2

Part 5

C209

My greater team regularly alters client processes.

Part 5, 1.2.2

Part 5

C211

I have altered AI outputs

Part 5, 1.3.1

Part 5

C212

I discussed the AI output alteration with internal management

Part 5, 4.1.3

Part 5

C213

I or my management discussed AI output alteration with the client

Part 5, 4.2.3

Part 5

C215

My greater team regularly alters AI outputs.

Part 5, 1.3.2