Source: https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-5-c199/
Author: Phil Hatch
Publisher: Akholi

I have altered client-provided data

Study Data · Part 5 · Indicator Deep-Dive Analysis

# I have altered client-provided data

Indicator C199 · By Phil Hatch · Akholi · October 9, 2026

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## On this page

25 sectionsIndicator SpecificationSummary of FindingsDistribution of ResponsesCoverage and Origin of Written ResponsesDistribution of Written SentimentDescriptive Statistics by SegmentTests of Difference Between SegmentsWritten Sentiment by SegmentAssociation with Cancellation RateAssociation with Customer SatisfactionAssociation with the Engagement Indicator MeanAssociation with Intent to LeaveAssociation of Written Sentiment with the Study MeasuresComparison of Associations Across the Four MeasuresClustering and Effective Sample SizeEquivalence Tests of Null ResultsRobustness ChecksMeasure Independence and Part-Whole CorrectionComparison with the Study NormComparison of Written Sentiment with Other Part 5 IndicatorsCo-Occurring Indicators and ThemesInterpretation of the DataLimitationsDefinitionsSources and Provenance

## Indicator Specification

Table 1. Indicator specificationTable

| Field | Value |
| --- | --- |
| Indicator code | C199 |
| Question as asked | I have altered client-provided data |
| Failure category | Not one of the 100 rated indicators |
| Place in the survey | Challenge Deep Dive > 5.6 Alterations > Client Data |
| Indicator class | Respondent level |
| Indicator type | Yes or no |
| Response scale | Levels: Yes, No |
| Answering base | 839 of 850 respondents gave one of the listed answers. 845 answered, counting I do not know and I prefer to not answer, across 150 of 150 engagements |
| Non-answers | I do not know 1, I prefer to not answer 5, blank 5 |
| Written responses addressing the indicator | 578 responses from 378 respondents on 128 engagements (548 primary, 30 secondary) |

## Summary of Findings

Table 2. Key results: association of the indicator with the four study measuresTable

| Measure | Effect size | n | Value | p |
| --- | --- | --- | --- | --- |
| Cancellation rate | Omega squared, 0 or 1 flag | 135 engagements | 0.269 | < 0.001 |
| Customer satisfaction | Omega squared | 82 engagements | 0.176 | < 0.001 |
| Engagement indicator mean | Omega squared | 135 engagements | 0.415 | < 0.001 |
| Intent to leave | Omega squared | 135 engagements | 0.293 | < 0.001 |

Of the 839 respondents who answered, 421 (50.18%) answered True and 418 (49.82%) answered False. At engagement level, the answer was associated with all four study measures. Engagements whose respondents most often said they had altered data provided by the financial institution were canceled more often (61.84% of 76 engagements against 10.17% of 59), and recorded lower customer satisfaction among active engagements, a lower engagement indicator mean and higher intent to leave.

After Holm correction, the share answering True differed by engagement status and lifecycle stage (chi-square 37.31, Holm p < 0.001, Cramer's V 0.53): the share answering True was highest among respondents on canceled engagements (69.62%, n = 316 respondents) and lowest among respondents on active engagements in Transition/Cut-Over (36.59%, n = 246 respondents). It also differed by respondent role (chi-square 215.77, Holm p < 0.001, Cramer's V 0.51): the share answering True was highest among individual contributors (63.43%, n = 659 respondents) and lowest among portfolio directors (0.00%, n = 30 respondents). It also differed by vendor type (chi-square 19.90, Holm p = 0.007, Cramer's V 0.15): the share answering True was highest among respondents at vendors of the type “BPO specialist” (55.33%, n = 197 respondents) and lowest among respondents at vendors of the type “Pure-play agentic AI firm” (42.67%, n = 75 respondents). Outsourcing model, institution type, process family and class of work showed no difference.

The 578 written responses came from 378 respondents on 128 engagements, and 571 were negative. The respondents who answered C202, on why they altered the data, described data from the financial institution that arrived unusable, every cycle and after earlier cleaning, and access too limited to correct it at source. The respondents who commented under C204 described the alteration as routine and largely out of the financial institution's sight.

## Distribution of Responses

Table 3. Distribution of responses, respondent levelTable

| Answer | Respondents | Share of answered (base 839) | Cumulative share | Engagements with at least one | Share of 150 engagements | Distressed |
| --- | --- | --- | --- | --- | --- | --- |
| Yes | 421 | 50.18% | 50.18% | 127 | 84.67% | Not applicable |
| No | 418 | 49.82% | 100.00% | 147 | 98.00% | Not applicable |
| I do not know | 1 | Not in base | Not in base | 1 | 0.67% | Not applicable |
| I prefer to not answer | 5 | Not in base | Not in base | 4 | 2.67% | Not applicable |
| Answered, total | 839 | 100.00% | | 150 | 100.00% | |

Of the 839 respondents who answered, 421 (50.18%) answered True and 418 (49.82%) answered False. The non-answers were I do not know (1) and I prefer to not answer (5). Each engagement was assigned the answer given by the largest number of its respondents. True was the assigned answer on 76 engagements and False on 59, and 15 engagements were tied and carry no assigned answer.

## Coverage and Origin of Written Responses

Figure 1. Written responses addressing the indicator, by question answered and written score (n = 578 responses)ExhibitNote: Each bar is one survey question. C202 and C204 and C208 and C210 and C214 are the written-answer questions of the indicator's survey section, so their responses are primary. The responses to every other question are secondary. Segments wide enough to hold a label carry their count. C202 asked: “Why did you alter client provided data?” C204 asked: “Comment” C208 asked: “Why did you alter client processes?” C210 asked: “Comment” C214 asked: “Why did you alter AI outputs?” C114 asked: “Add any comments on the customer organization that the ratings in this section do not capture.” C198 asked: “Add any comments on the third-party ecosystem that the ratings in this section do not capture.”Table 4. Written responses by originTable

| Origin | Responses | Respondents | Engagements | Negative | Strongest negative (−10) | Positive | Mean written score |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Primary | 548 | 362 | 123 | 542 of 548 (98.91%) | 235 of 548 (42.88%) | 5 of 548 (0.91%) | −7.0 |
| Secondary | 30 | 30 | 26 | 29 of 30 (96.67%) | 11 of 30 (36.67%) | 1 of 30 (3.33%) | −6.5 |
| All responses | 578 | 378 | 128 | 571 of 578 (98.79%) | 246 of 578 (42.56%) | 6 of 578 (1.04%) | −7.0 |

The primary responses numbered 548, written in answer to C202, C204, C208, C210 and C214, the written-answer questions of the indicator's survey section. The remaining 30 responses, 5.19% of the total, were secondary and came from 2 other questions. That secondary share ranked 2nd from the highest among the 13 Part 5 indicators with 30 or more written responses, against a median of 2.00%. Respondents who wrote both a primary and a secondary response numbered 14. Negative responses made up 98.91% of primary responses (542 of 548) and 96.67% of secondary responses (29 of 30).

The 281 responses to C202 gave the reasons for altering the data. Across 94 responses, respondents named access: a legacy platform with no way in for an agent, a security team that would not approve a connection, read-only or expired credentials, or data copied off the display because no export existed. Respondents named missing, blank or dropped rows and values in 48 responses, a format or layout that changed between deliveries in 42, data that did not match between systems or a field that meant different things in different feeds in 44, and data that arrived dirty again after the team had cleaned it in 41. Reference data years out of date appeared in 33 responses and duplicate records in 28. Several added that decisions came after the deadline they were needed for, or that the AI tool gave a different result on each run.

The 247 responses to C204 described how the alteration was handled. Respondents placed it every day, cycle, week or file, or on most cases, in 161 responses. Respondents said the alteration was not reported, logged or raised, or was done quietly, in 78 responses, and that the financial institution was not told, or that they did not know whether it was, in 38. The team lead or manager appeared in 88, most often as someone who knew and could not change the source. Five responses across the indicator said the financial institution had been told or had asked for the corrections. Several respondents said they had become quick at spotting a bad file, and several said the work had worn them down.

Twelve responses described a private sheet, list, mapping file or tracker kept by the respondent to correct the data before each run. The responses to C208, C210 and C214 described altering the financial institution's processes or AI outputs as well as data, often because no one would make a decision in time.

## Distribution of Written Sentiment

Figure 2. Distribution of written sentiment (n = 578 responses)ExhibitNote: Column height is the share of the 578 responses. Labels give the count and the share.Table 5. Summary statistics of written sentimentTable

| Statistic | Value | Basis |
| --- | --- | --- |
| Mean written score | −7.0 | 95% CI −7.2 to −6.8, cluster bootstrap by engagement, 10,000 draws, n = 578 responses |
| Median written score | −5.0 | n = 578 responses |
| Negative responses | 571 of 578 (98.79%) | 95% CI 97.86% to 99.62% of 578 responses, cluster bootstrap by engagement |
| Strongest negative responses (−10) | 246 of 578 (42.56%) | Statements of totality, constancy or serious harm |
| Positive responses | 6 of 578 (1.04%) | +5 or +10 |
| Net balance | −97.75 percentage points | Share positive minus share negative, base 578 responses |
| Respondent-level mean | −7.0 | Mean of each respondent's own mean written score, n = 378 respondents |

Of the 578 responses, 571 (98.79%, 95% CI 97.86% to 99.62%) were negative and 246 (42.56%) carried the strongest negative score of −10. Positive responses numbered 6 (1.04%), and 1 was neutral. The mean written score was −7.0 (95% CI −7.2 to −6.8, n = 578 responses), and the median was −5.0.

## Descriptive Statistics by Segment

Table 6. Descriptive statistics by segmentTable

| Segment | Base | Answered | Answer rate | Engagements | Yes, share | No, share |
| --- | --- | --- | --- | --- | --- | --- |
| Study set | 850 | 839 | 98.71% of 850 | 150 | 50.18% | 49.82% |
| Outsourcing model | | | | | | |
| CXM | 232 | 230 | 99.14% of 232 | 42 | 52.61% | 47.39% |
| ITO | 244 | 238 | 97.54% of 244 | 40 | 44.96% | 55.04% |
| BPO | 209 | 207 | 99.04% of 209 | 37 | 51.21% | 48.79% |
| KPO | 165 | 164 | 99.39% of 165 | 31 | 53.05% | 46.95% |
| Institution type | | | | | | |
| Asset management | 132 | 132 | 100.00% of 132 | 24 | 53.79% | 46.21% |
| Wealth management and private banking | 140 | 135 | 96.43% of 140 | 23 | 45.93% | 54.07% |
| Investment banking (advisory and capital-markets origination) | 105 | 104 | 99.05% of 105 | 19 | 55.77% | 44.23% |
| Insurance (life, property and casualty, health) | 78 | 76 | 97.44% of 78 | 14 | 50.00% | 50.00% |
| Commercial and business banking | 82 | 81 | 98.78% of 82 | 13 | 53.09% | 46.91% |
| Payments and merchant acquiring (networks, acquiring, processing) | 71 | 70 | 98.59% of 71 | 13 | 44.29% | 55.71% |
| Credit card and payments issuing | 73 | 73 | 100.00% of 73 | 12 | 56.16% | 43.84% |
| Retail and consumer banking | 73 | 72 | 98.63% of 73 | 12 | 45.83% | 54.17% |
| Markets and trading (sales and trading, global markets) | 57 | 57 | 100.00% of 57 | 11 | 49.12% | 50.88% |
| Private equity and private capital | 39 | 39 | 100.00% of 39 | 9 | 41.03% | 58.97% |
| Process family | | | | | | |
| Corporate and back-office functions | 248 | 246 | 99.19% of 248 | 47 | 56.10% | 43.90% |
| Technology engineering and operations | 204 | 204 | 100.00% of 204 | 35 | 42.65% | 57.35% |
| Client servicing and communications | 94 | 93 | 98.94% of 94 | 16 | 55.91% | 44.09% |
| Trade, settlement and reconciliation | 80 | 79 | 98.75% of 80 | 15 | 49.37% | 50.63% |
| Payments, cards and disputes | 73 | 72 | 98.63% of 73 | 12 | 38.89% | 61.11% |
| Credit, underwriting and suitability | 57 | 57 | 100.00% of 57 | 9 | 45.61% | 54.39% |
| Regulatory, audit, tax and legal | 51 | 46 | 90.20% of 51 | 9 | 47.83% | 52.17% |
| Financial crime and client onboarding | 43 | 42 | 97.67% of 43 | 7 | 69.05% | 30.95% |
| Class of work | | | | | | |
| LOB Operational | 451 | 442 | 98.00% of 451 | 76 | 49.32% | 50.68% |
| Corporate Functional | 399 | 397 | 99.50% of 399 | 74 | 51.13% | 48.87% |
| Engagement status and lifecycle stage | | | | | | |
| Active, Build-Out | 175 | 175 | 100.00% of 175 | 31 | 41.71% | 58.29% |
| Active, Transition/Cut-Over | 250 | 246 | 98.40% of 250 | 43 | 36.59% | 63.41% |
| Active, Production | 103 | 102 | 99.03% of 103 | 20 | 37.25% | 62.75% |
| Canceled | 322 | 316 | 98.14% of 322 | 56 | 69.62% | 30.38% |
| Respondent role | | | | | | |
| Individual Contributor | 667 | 659 | 98.80% of 667 | 150 | 63.43% | 36.57% |
| Engagement Manager | 150 | 150 | 100.00% of 150 | 150 | 2.00% | 98.00% |
| Portfolio Director | 31 | 30 | 96.77% of 31 | 31 | 0.00% | 100.00% |
| Customer Management Executive | 2 | 0 | 0 of 2 | 0 | 0 | 0 |
| Vendor type | | | | | | |
| IT services major | 316 | 309 | 97.78% of 316 | 59 | 44.34% | 55.66% |
| BPO specialist | 198 | 197 | 99.49% of 198 | 37 | 55.33% | 44.67% |
| Consulting firm | 117 | 115 | 98.29% of 117 | 23 | 50.43% | 49.57% |
| Boutique or specialist provider | 87 | 87 | 100.00% of 87 | 17 | 50.57% | 49.43% |
| Pure-play agentic AI firm | 75 | 75 | 100.00% of 75 | 14 | 42.67% | 57.33% |
| Not reported, recovered by engagement | 57 | 56 | 98.25% of 57 | 47 | 73.21% | 26.79% |

Each share is computed on the respondents who answered in that row. Rows with fewer than 10 respondents report counts only.

## Tests of Difference Between Segments

Table 7. Tests of difference between segmentsTable

| Segment family | Unit | Chi-square | df | p | Holm p | Cramer's V | Test for p | Levels excluded |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Outsourcing model | Engagement | 2.57 | 3 | 0.463 | 1.000 | 0.14 | chi-square | None |
| Institution type | Engagement | 6.03 | 8 | 0.660 | 1.000 | 0.22 | Monte Carlo, simulated | Private equity and private capital, n = 9 |
| Process family | Engagement | 6.28 | 4 | 0.182 | 0.729 | 0.23 | Monte Carlo, simulated | Credit, underwriting and suitability, n = 7, Regulatory, audit, tax and legal, n = 7, Financial crime and client onboarding, n = 7 |
| Class of work | Engagement | 0.63 | 1 | 0.429 | 1.000 | 0.07 | chi-square | None |
| Engagement status and lifecycle stage | Engagement | 37.31 | 3 | < 0.001 | < 0.001 | 0.53 | chi-square | None |
| Respondent role | Respondent | 215.77 | 2 | < 0.001 | < 0.001 | 0.51 | chi-square | Customer Management Executive, n = 0 |
| Vendor type | Respondent | 19.90 | 5 | 0.001 | 0.007 | 0.15 | chi-square | None |

Segment families recorded at engagement level were tested on engagements, and respondent role and vendor type on respondents. After Holm correction, the share answering True differed by engagement status and lifecycle stage (chi-square 37.31, Holm p < 0.001, Cramer's V 0.53): the share answering True was highest among respondents on canceled engagements (69.62%, n = 316 respondents) and lowest among respondents on active engagements in Transition/Cut-Over (36.59%, n = 246 respondents). It also differed by respondent role (chi-square 215.77, Holm p < 0.001, Cramer's V 0.51): the share answering True was highest among individual contributors (63.43%, n = 659 respondents) and lowest among portfolio directors (0.00%, n = 30 respondents). It also differed by vendor type (chi-square 19.90, Holm p = 0.007, Cramer's V 0.15): the share answering True was highest among respondents at vendors of the type “BPO specialist” (55.33%, n = 197 respondents) and lowest among respondents at vendors of the type “Pure-play agentic AI firm” (42.67%, n = 75 respondents). Outsourcing model, institution type, process family and class of work showed no difference.

## Written Sentiment by Segment

Figure 3. Written sentiment by engagement status and lifecycle stage, share of each group's responsesExhibitNote: Each bar is the whole of its group's responses, divided by written score from −10 at the left to +10 at the right. Segments large enough to hold a label carry their share.Table 8. Written sentiment by segmentTable

| Segment | Responses | Respondents | Engagements | Mean written score | Negative | Strongest negative (−10) |
| --- | --- | --- | --- | --- | --- | --- |
| Engagement status and lifecycle stage | | | | | | |
| Active, Build-Out | 93 | 66 | 27 | −6.8 | 91 of 93 (97.85%) | 37 of 93 (39.78%) |
| Active, Transition/Cut-Over | 125 | 80 | 33 | −6.7 | 122 of 125 (97.60%) | 48 of 125 (38.40%) |
| Active, Production | 55 | 34 | 13 | −6.7 | 55 of 55 (100.00%) | 19 of 55 (34.55%) |
| Canceled | 305 | 198 | 55 | −7.3 | 303 of 305 (99.34%) | 142 of 305 (46.56%) |
| Respondent role | | | | | | |
| Individual Contributor | 561 | 362 | 127 | −7.0 | 555 of 561 (98.93%) | 235 of 561 (41.89%) |
| Engagement Manager | 16 | 15 | 15 | −8.4 | 16 of 16 (100.00%) | 11 of 16 (68.75%) |
| Portfolio Director | 1 | 1 | 1 | ‡ | 0 of 1 | 0 of 1 |
| Customer Management Executive | 0 | 0 | 0 | No responses | | |

Note: ‡ Base under 10. No statistic is reported.

Written sentiment did not differ by engagement status and lifecycle stage across the 128 engagements with a written response (Kruskal-Wallis H 6.50, df 3, p = 0.090). Of the groups with 10 or more responses, responses from canceled engagements were the most negative (mean −7.3, 305 responses) and responses from active engagements in Transition/Cut-Over the least negative (mean −6.7, 125 responses).

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 561 responses, engagement managers 16 and portfolio directors 1.

## Association with Cancellation Rate

Cancellation rate is the share of engagements canceled by the study date, measured at engagement level (150 engagements, 56 canceled). Canceled engagements were rated after cancellation. The association is therefore a descriptive contrast and not a forecast of cancellation. Each test compares the engagements by their assigned answer, within the study set and within each segment.

Table 9. Association with cancellation rate by answer levelTable

| Answer level | Engagements | Canceled | Cancellation rate |
| --- | --- | --- | --- |
| Yes | 76 | 47 | 61.84% |
| No | 59 | 6 | 10.17% |
| I do not know | 0 | No engagements | |
| I prefer to not answer | 0 | No engagements | |

Table 10. Association with cancellation rate, tests across answer levels by segmentTable

| Segment | Engagements | Chi-square | df | p | Holm p | Cramer's V | Test for p |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 135 | 37.19 | 1 | < 0.001 | < 0.001 | 0.52 | chi-square |
| Outsourcing model | | | | | | | |
| CXM | 37 | 13.71 | 1 | < 0.001 | 0.001 | 0.61 | chi-square |
| ITO | 39 | 9.55 | 1 | 0.002 | 0.008 | 0.49 | chi-square |
| BPO | 33 | 8.97 | 1 | 0.003 | 0.008 | 0.52 | chi-square |
| KPO | 26 | 5.85 | 1 | 0.016 | 0.031 | 0.47 | chi-square |
| Institution type | | | | | | | |
| Asset management | 22 | a | | | | | |
| Wealth management and private banking | 22 | 1.47 | 1 | 0.378 | 0.378 | 0.26 | Fisher exact |
| Investment banking (advisory and capital-markets origination) | 17 | a | | | | | |
| Insurance (life, property and casualty, health) | 12 | a | | | | | |
| Commercial and business banking | 11 | a | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 11 | a | | | | | |
| Credit card and payments issuing | 11 | a | | | | | |
| Retail and consumer banking | 10 | a | | | | | |
| Markets and trading (sales and trading, global markets) | 10 | a | | | | | |
| Private equity and private capital | 9 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 43 | 11.55 | 1 | < 0.001 | 0.003 | 0.52 | chi-square |
| Technology engineering and operations | 34 | 15.94 | 1 | < 0.001 | < 0.001 | 0.68 | Fisher exact |
| Client servicing and communications | 14 | a | | | | | |
| Trade, settlement and reconciliation | 13 | a | | | | | |
| Payments, cards and disputes | 10 | a | | | | | |
| Credit, underwriting and suitability | 7 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 7 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 68 | 12.55 | 1 | < 0.001 | 0.002 | 0.43 | chi-square |
| Corporate Functional | 67 | 26.92 | 1 | < 0.001 | < 0.001 | 0.63 | chi-square |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | | b | | | | | |
| Active, Transition/Cut-Over | | b | | | | | |
| Active, Production | | b | | | | | |
| Canceled | | b | | | | | |

Note: ‡ Base under 10. No statistic is reported. a Not tested: fewer than two levels of 10 or more engagements. b Not tested: no variation in cancellation.

Of the engagements whose respondents most often answered True, 47 of 76 (61.84%) were canceled, against 6 of 59 (10.17%) of those whose respondents most often answered False (chi-square 37.19, p < 0.001, Cramer's V 0.52, n = 135 engagements). The difference reached significance and held after Holm correction in 8 of the 9 segment levels tested.

## Association with Customer Satisfaction

Customer satisfaction is the percentage recorded against each engagement. The primary estimate uses the 94 active engagements.

Table 11. Association with customer satisfaction by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Yes | 29 | 57.4 | 10.9 |
| No | 53 | 67.8 | 10.2 |
| I do not know | 0 | No engagements | |
| I prefer to not answer | 0 | No engagements | |

Table 12. Association with customer satisfaction, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 82 | 17.74 | 1, 54.5 | < 0.001 | < 0.001 | 0.176 | 0.073 to 0.307 |
| Outsourcing model | | | | | | | |
| CXM | 23 | a | | | | | |
| ITO | 24 | a | | | | | |
| BPO | 19 | a | | | | | |
| KPO | 16 | a | | | | | |
| Institution type | | | | | | | |
| Asset management | 11 | a | | | | | |
| Wealth management and private banking | 14 | a | | | | | |
| Investment banking (advisory and capital-markets origination) | 8 | ‡ | | | | | |
| Insurance (life, property and casualty, health) | 7 | ‡ | | | | | |
| Commercial and business banking | 7 | ‡ | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 9 | ‡ | | | | | |
| Credit card and payments issuing | 6 | ‡ | | | | | |
| Retail and consumer banking | 6 | ‡ | | | | | |
| Markets and trading (sales and trading, global markets) | 7 | ‡ | | | | | |
| Private equity and private capital | 7 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 24 | 8.33 | 1, 15.8 | 0.011 | 0.021 | 0.251 | † |
| Technology engineering and operations | 24 | a | | | | | |
| Client servicing and communications | 6 | ‡ | | | | | |
| Trade, settlement and reconciliation | 6 | ‡ | | | | | |
| Payments, cards and disputes | 8 | ‡ | | | | | |
| Credit, underwriting and suitability | 6 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 4 | ‡ | | | | | |
| Financial crime and client onboarding | 4 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 40 | 7.57 | 1, 26.0 | 0.011 | 0.021 | 0.144 | 0.026 to 0.335 |
| Corporate Functional | 42 | 10.51 | 1, 24.9 | 0.003 | 0.013 | 0.203 | 0.060 to 0.388 |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 26 | a | | | | | |
| Active, Transition/Cut-Over | 38 | 10.58 | 1, 21.0 | 0.004 | 0.013 | 0.222 | 0.067 to 0.415 |
| Active, Production | 18 | a | | | | | |
| Canceled | | b | | | | | |

Note: ‡ Base under 10. No statistic is reported. † Base under 30. No interval is reported. a Not tested: fewer than two levels of 10 or more engagements. b Not tested: canceled engagements fall outside the active population.

Among active engagements, customer satisfaction had a mean of 57.4% (n = 29 engagements) where respondents most often answered True and 67.8% (n = 53 engagements) where they most often answered False (Welch F 17.74, p < 0.001, omega squared 0.176, n = 82 engagements). The difference reached significance and held after Holm correction in 4 of the 4 segment levels tested.

## Association with the Engagement Indicator Mean

The engagement indicator mean is the mean of an engagement's ratings across the rated indicators, measured at engagement level. The indicator is not a rated indicator and does not enter the mean.

Table 13. Association with the engagement indicator mean by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Yes | 76 | 3.1 | 1.1 |
| No | 59 | 5.1 | 1.2 |
| I do not know | 0 | No engagements | |
| I prefer to not answer | 0 | No engagements | |

Table 14. Association with the engagement indicator mean, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 135 | 93.60 | 1, 115.9 | < 0.001 | < 0.001 | 0.415 | 0.316 to 0.505 |
| Outsourcing model | | | | | | | |
| CXM | 37 | 46.40 | 1, 25.8 | < 0.001 | < 0.001 | 0.561 | 0.382 to 0.689 |
| ITO | 39 | 23.72 | 1, 36.9 | < 0.001 | < 0.001 | 0.368 | 0.183 to 0.537 |
| BPO | 33 | 14.03 | 1, 25.7 | < 0.001 | 0.002 | 0.267 | 0.087 to 0.468 |
| KPO | 26 | 20.14 | 1, 21.7 | < 0.001 | < 0.001 | 0.424 | † |
| Institution type | | | | | | | |
| Asset management | 22 | a | | | | | |
| Wealth management and private banking | 22 | 10.90 | 1, 19.9 | 0.004 | 0.004 | 0.298 | † |
| Investment banking (advisory and capital-markets origination) | 17 | a | | | | | |
| Insurance (life, property and casualty, health) | 12 | a | | | | | |
| Commercial and business banking | 11 | a | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 11 | a | | | | | |
| Credit card and payments issuing | 11 | a | | | | | |
| Retail and consumer banking | 10 | a | | | | | |
| Markets and trading (sales and trading, global markets) | 10 | a | | | | | |
| Private equity and private capital | 9 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 43 | 26.67 | 1, 23.4 | < 0.001 | < 0.001 | 0.393 | 0.215 to 0.550 |
| Technology engineering and operations | 34 | 26.59 | 1, 30.4 | < 0.001 | < 0.001 | 0.433 | 0.231 to 0.598 |
| Client servicing and communications | 14 | a | | | | | |
| Trade, settlement and reconciliation | 13 | a | | | | | |
| Payments, cards and disputes | 10 | a | | | | | |
| Credit, underwriting and suitability | 7 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 7 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 68 | 45.53 | 1, 57.3 | < 0.001 | < 0.001 | 0.404 | 0.263 to 0.530 |
| Corporate Functional | 67 | 50.28 | 1, 58.5 | < 0.001 | < 0.001 | 0.417 | 0.275 to 0.542 |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 26 | a | | | | | |
| Active, Transition/Cut-Over | 38 | 17.07 | 1, 23.4 | < 0.001 | 0.001 | 0.304 | 0.125 to 0.487 |
| Active, Production | 18 | a | | | | | |
| Canceled | 53 | a | | | | | |

Note: † Base under 30. No interval is reported. ‡ Base under 10. No statistic is reported. a Not tested: fewer than two levels of 10 or more engagements.

The engagement indicator mean was 3.1 (n = 76 engagements) on engagements whose respondents most often answered True and 5.1 (n = 59 engagements) on those whose respondents most often answered False (Welch F 93.60, p < 0.001, omega squared 0.415, n = 135 engagements). The difference reached significance and held after Holm correction in 10 of the 10 segment levels tested.

## Association with Intent to Leave

Intent to leave is the answer to C019, “How likely are you to leave your current job in the next 12 months?”, rated 1 to 10 by up to 798 respondents. For the indicator, the comparison uses the mean intent to leave of each engagement.

Table 15. Association with intent to leave by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Yes | 76 | 8.0 | 1.9 |
| No | 59 | 5.4 | 2.1 |
| I do not know | 0 | No engagements | |
| I prefer to not answer | 0 | No engagements | |

Table 16. Association with intent to leave, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 135 | 55.34 | 1, 116.7 | < 0.001 | < 0.001 | 0.293 | 0.196 to 0.393 |
| Outsourcing model | | | | | | | |
| CXM | 37 | 40.97 | 1, 33.1 | < 0.001 | < 0.001 | 0.485 | 0.295 to 0.632 |
| ITO | 39 | 14.41 | 1, 29.9 | < 0.001 | 0.003 | 0.250 | 0.087 to 0.438 |
| BPO | 33 | 9.27 | 1, 22.5 | 0.006 | 0.023 | 0.203 | 0.047 to 0.412 |
| KPO | 26 | 7.58 | 1, 24.0 | 0.011 | 0.032 | 0.202 | † |
| Institution type | | | | | | | |
| Asset management | 22 | a | | | | | |
| Wealth management and private banking | 22 | 3.91 | 1, 18.7 | 0.063 | 0.063 | 0.105 | † |
| Investment banking (advisory and capital-markets origination) | 17 | a | | | | | |
| Insurance (life, property and casualty, health) | 12 | a | | | | | |
| Commercial and business banking | 11 | a | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 11 | a | | | | | |
| Credit card and payments issuing | 11 | a | | | | | |
| Retail and consumer banking | 10 | a | | | | | |
| Markets and trading (sales and trading, global markets) | 10 | a | | | | | |
| Private equity and private capital | 9 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 43 | 19.48 | 1, 28.4 | < 0.001 | < 0.001 | 0.284 | 0.119 to 0.459 |
| Technology engineering and operations | 34 | 30.05 | 1, 31.3 | < 0.001 | < 0.001 | 0.452 | 0.251 to 0.613 |
| Client servicing and communications | 14 | a | | | | | |
| Trade, settlement and reconciliation | 13 | a | | | | | |
| Payments, cards and disputes | 10 | a | | | | | |
| Credit, underwriting and suitability | 7 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 7 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 68 | 17.78 | 1, 58.4 | < 0.001 | < 0.001 | 0.203 | 0.085 to 0.348 |
| Corporate Functional | 67 | 48.14 | 1, 61.1 | < 0.001 | < 0.001 | 0.399 | 0.257 to 0.526 |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 26 | a | | | | | |
| Active, Transition/Cut-Over | 38 | 7.87 | 1, 21.2 | 0.011 | 0.032 | 0.169 | 0.036 to 0.366 |
| Active, Production | 18 | a | | | | | |
| Canceled | 53 | a | | | | | |

Note: † Base under 30. No interval is reported. ‡ Base under 10. No statistic is reported. a Not tested: fewer than two levels of 10 or more engagements.

The engagement mean of intent to leave was 8.0 (n = 76 engagements) on engagements whose respondents most often answered True and 5.4 (n = 59 engagements) on those whose respondents most often answered False (Welch F 55.34, p < 0.001, omega squared 0.293, n = 135 engagements). The difference reached significance and held after Holm correction in 9 of the 10 segment levels tested.

## Association of Written Sentiment with the Study Measures

Table 17. Written sentiment and the study measuresTable

| Comparison | With a negative response | Without a negative response | Test | Statistic | n | p |
| --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate, engagements | 55 of 128 (42.97%) | 1 of 22 (4.55%) | Fisher exact | | 150 | < 0.001 |
| Customer satisfaction, active engagements | 61.89%, n = 73 | 71.76%, n = 21 | Welch t | −3.83 | 94 | < 0.001 |
| Engagement mean written score and cancellation, engagements | | | Point-biserial r | −0.20 | 128 | 0.024 |
| Respondent mean written score and intent to leave, respondents | | | Spearman rho | −0.18 | 346 | < 0.001 |

Two comparisons set the engagements with at least one negative response against all other engagements. Of the 22 other engagements, 22 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 128 engagements with a negative response, 55 (42.97%) were canceled, against 1 of the 22 other engagements (4.55%). The difference reached significance (Fisher exact p < 0.001). Customer satisfaction among active engagements differed between the two groups (mean 61.89% on 73 engagements against 71.76% on 21, Welch t −3.83, p < 0.001).

Two correlations test written sentiment directly. Across the 128 engagements with a written response, a more negative engagement mean written score came with cancellation (point-biserial r −0.20, p = 0.024). Across 346 respondents, a more negative respondent mean written score came with higher intent to leave (Spearman rho −0.18, p < 0.001). Of the four comparisons, all reached significance at 0.05.

## Comparison of Associations Across the Four Measures

Table 18. Associations across the four measuresTable

| Measure | Effect size | n | Value | p | Equivalent to zero | Rank among the four |
| --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate | Omega squared, 0 or 1 flag | 135 | 0.269 | < 0.001 | No | 3 |
| Customer satisfaction | Omega squared | 82 | 0.176 | < 0.001 | No | 4 |
| Engagement indicator mean | Omega squared | 135 | 0.415 | < 0.001 | No | 1 |
| Intent to leave | Omega squared | 135 | 0.293 | < 0.001 | No | 2 |

Steiger's z compares two correlations. A categorical indicator yields an effect size across its levels and not a correlation, so the pairs of measures were not compared by test. On omega squared, the association was strongest with the engagement indicator mean (0.415) and weakest with customer satisfaction (0.176).

## Clustering and Effective Sample Size

Table 19. Clustering and effective sample sizeTable

| Statistic | Value | Reading |
| --- | --- | --- |
| Clusters (engagements) | 150 | Engagements with one or more answers. |
| Mean respondents per engagement | 5.6 | Answers per engagement, among engagements with one or more answers. |
| ICC(1) | 0.20 | Share of the variance that lies between engagements. |
| Design effect | 1.95 | One plus the product of the ICC and the mean cluster size less one. |
| Nominal respondent n | 845 | Every answer, with “I do not know” and “I prefer to not answer” counted as levels, as in the plurality rule. |
| Effective n | 434 | Nominal n divided by the design effect. |
| Cluster bootstrap applied | Yes | Applied to every respondent-level interval where the ICC is 0.05 or above. |

Answers clustered within engagements (ICC 0.20). Clustering reduced the 845 respondent answers to the equivalent of about 434 independent answers. Respondent-level intervals therefore used the cluster bootstrap. Respondent-level tests used standard errors that allow for clustering by engagement.

## Equivalence Tests of Null Results

Table 20. Equivalence tests of null resultsTable

| Measure | n | Omega squared | Equivalence bound | Equivalence p | Equivalent to zero | Achieved power | MDE at power 0.80 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate | 135 | 0.269 | Omega squared < 0.090 | 0.999 | No | 0.95 | 0.056 |
| Customer satisfaction | 82 | 0.176 | Omega squared < 0.090 | 0.913 | No | 0.80 | 0.089 |
| Engagement indicator mean | 135 | 0.415 | Omega squared < 0.090 | 1.000 | No | 0.95 | 0.056 |
| Intent to leave | 135 | 0.293 | Omega squared < 0.090 | 1.000 | No | 0.95 | 0.056 |

No association was equivalent to zero. Each of the four differed from zero. The equivalence bound is an omega squared of 0.090, the study's threshold for a negligible association expressed as variance explained.

## Robustness Checks

Table 21. Robustness checksTable

| Check | Measure | Primary p | Check p | Check statistic | Conclusion holds |
| --- | --- | --- | --- | --- | --- |
| Kruskal-Wallis in place of Welch F | Customer satisfaction | < 0.001 | < 0.001 | 15.03 | Yes |
| Kruskal-Wallis in place of Welch F | Engagement indicator mean | < 0.001 | < 0.001 | 57.41 | Yes |
| Kruskal-Wallis in place of Welch F | Intent to leave | < 0.001 | < 0.001 | 36.94 | Yes |
| Active engagements only | Engagement indicator mean | < 0.001 | < 0.001 | 26.78 | Yes |
| Active engagements only | Intent to leave | < 0.001 | 0.006 | 8.21 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Cancellation rate | < 0.001 | < 0.001 | 59.49 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Customer satisfaction | < 0.001 | < 0.001 | 75.04 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Engagement indicator mean | < 0.001 | < 0.001 | 204.26 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Intent to leave | < 0.001 | < 0.001 | 87.34 | Yes |

All nine checks held. A check holds when its test falls on the same side of 0.05 as the primary test. The checks replace Welch's F with a Kruskal-Wallis test, repeat the tests on active engagements alone, and repeat them at respondent level with a Wald F clustered by engagement.

## Measure Independence and Part-Whole Correction

Each of the four measures was computed from data the indicator does not contain. Each result is therefore a finding and not an arithmetic consequence.

## Comparison with the Study Norm

A categorical indicator has no signed correlation with the study measures and therefore no profile against the study norm. The comparison by answer appears in the four association sections.

## Comparison of Written Sentiment with Other Part 5 Indicators

Figure 4. Share of negative written responses, Part 5 indicators with 30 or more written responses (n = 13 indicators)ExhibitNote: Each column is one indicator, ordered from the highest share of negative responses. The indicator is the amber column. The dashed line marks the median share, 98.03%.

Among the 13 Part 5 indicators with 30 or more written responses, the indicator's share of negative responses, 98.79%, ranked 6th from the highest, against a median of 98.03%. Its mean written score, −7.0, ranked 5th from the most negative, against a median of −6.3.

## Co-Occurring Indicators and Themes

Figure 5. Other indicators and themes in the same written responses (n = 578 responses)ExhibitNote: Themes carry no score. Labels give the count and the share of the 578 responses. The figure shows each indicator and each theme among the five most frequent of its kind, with every tie at the cut. C094: “Rate the quality of the customer's data across the systems this engagement depends on.” C200: “I discussed the data alteration with internal management” C108: “Rate the customer's ability to provision the system access and identities that AI agents require.” C096: “Rate how well the customer's data is normalized, with consistent formats and definitions across source systems.” C201: “I or my management discussed data alteration with the client” C203: “My greater team regularly alters client provided data.” Emotional states in the same responses, as counts: resigned 51, frustrated 37, tired 30, calm or fine 21, stressed 9, angry 1, proud 1.

The indicator most often present in the same responses was C094, “Rate the quality of the customer's data across the systems this engagement depends on.”, in 341 of the 578 responses (59.00%). C200, “I discussed the data alteration with internal management” (128 responses), C108, “Rate the customer's ability to provision the system access and identities that AI agents require.” (92 responses), C096, “Rate how well the customer's data is normalized, with consistent formats and definitions across source systems.” (88 responses) and C201, “I or my management discussed data alteration with the client” (74 responses) followed.

The most frequent theme was “Occurs every cycle or most days”, in 215 responses (37.20%). The second was “Told vendor-side management”, in 102 responses.

## Interpretation of the Data

Half of the respondents who answered said they had altered data provided by the financial institution. Engagements whose respondents most often said so were canceled more often, recorded lower customer satisfaction and a lower engagement indicator mean, and their respondents reported higher intent to leave. Every association held under each of the robustness checks. The answer was given more often by individual contributors and on canceled engagements.

The written evidence describes alteration as routine work forced by the state of the data and the lack of access to its source, done every cycle and mostly kept within the team. Respondents rarely said the financial institution had been told. The associations do not establish that alteration produced the outcomes. The written responses describe alteration as one response to the same data and access problems that the other Part 5 indicators record.

## Limitations

The evidence is the reported experience of the vendor's delivery teams, collected in a single cross-section. The associations reported here are not causal. The answer is the respondent's own report of an alteration and not a record of it.

Each engagement carries the answer given by the largest number of its respondents, and tied engagements are excluded from the engagement-level tests.

Shares of written sentiment are shares of responses and not of the study set of respondents. The written score takes five fixed values, so its mean and median are coarse. Responses clustered within engagements (578 responses on 128 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.

The written responses are counted by sets of words stated in each rule. A response that described a reason in other words is not counted, so each count is a floor.

## Definitions

Table 22. DefinitionsTable

| Term | Definition |
| --- | --- |
| Response scale | The answer is True or False to the statement shown in the indicator specification. The indicator is not a rating. No distressed range applies. |
| Answering base | Respondents who answered True or False. |
| Non-answers | “I do not know” and “I prefer to not answer” are counted separately. They are excluded from the answering base and from the shares. |
| Indicator class | Respondent level: a report of the respondent's own action. Each engagement also carries the answer given by the largest number of its respondents, for the engagement-level tests. |
| Failure category | The five failure categories of the Study Taxonomy apply only to the rated indicators. The indicator carries none. |
| Engagement indicator mean | The mean of an engagement's ratings across the rated indicators. The indicator does not enter it. |
| Written response | A written answer about the respondent's own engagement that addresses the indicator. Non-answers and answers about another engagement are excluded. |
| Primary and secondary | A primary response answered the written-answer question of the indicator's survey section. A secondary response answered a question in another section and addressed the indicator in its content. |
| Written sentiment score | Each written response carries one of five scores: −10, −5, neutral, +5 or +10. The sign records whether the response described the state of the indicator as harmful or helpful to the engagement. The magnitude records its strength. A score of −10 marks a statement of totality, constancy or serious harm. |
| Cluster bootstrap | An interval computed by resampling engagements rather than responses, so that the responses from one engagement stay together. |

## Sources and Provenance

Table 23. Sources and provenanceTable

| Source | Value |
| --- | --- |
| Study data | Study Data.xlsx, Data sheet, column C199, sha256 219eba0457274d04 |
| Statistics engine | compute_statistics.py, sha256 738319eef764602b |
| Statistics record | Computed Statistics.json, record C199, sha256 1ae50a3637fc9370 |
| Computed | October 13, 2026, 04:57 UTC |
| Template | Indicator Template v2, version 2.0 of 10 October 2026 |
| Figures placed by script | 1,243 |
| Written responses | Quotes Master.jsonl, sha256 27da38085e2b13fd |
| Written sentiment scores | Quote Coding Rulebook, version 0.6, with section 21 |
| Written-response computation | qa_stats.py, sha256 74a61f3a96169da9. wfacts.py, sha256 b85fae20adf812a1. build_indicator.py, sha256 a97ad6e74627e11e |
| Written-response records | C199.qa.json, sha256 b0720089bdf8d123. C199.wfacts.json, sha256 3dca51e8f990452c. Hand-written text handcraft/C199.json, sha256 9a38dc1c200a8acf |


## Links to related study evidence

- [Part 5](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/part-5-manual-alteration/)
- [Customer satisfaction](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-1-measure-customer-satisfaction/)
- [Engagement indicator mean](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-1-measure-engagement-indicator-mean/)
- [Intent to leave](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-4-c019/)
- [third-party ecosystem](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/part-2-five-failure-categories/third-party-ecosystem/)
- [C019](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-4-c019/)
- [C094](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-2-c094/)
- [C200](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-5-c200/)
- [C108](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-2-c108/)
- [C096](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-2-c096/)
- [C201](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-5-c201/)
- [C203](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-5-c203/)