How well do you know the financial industry?

The mean rating was 4.8 and the median 5.0 (n = 796 respondents). Ratings of 3 or below, the distressed range, made up 27.26% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.61, 95% CI −0.70 to −0.50, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.77, 95% CI 0.68 to 0.84, p < 0.001, n = 94 engagements), a higher engagement indicator mean (r = 0.80, 95% CI 0.73 to 0.85, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.76, cluster bootstrap 95% CI −0.80 to −0.70, p < 0.001 with standard errors clustered by engagement, n = 750 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 34.66, Holm p < 0.001, omega squared 0.363), respondent role (Welch F 10.04, Holm p < 0.001, omega squared 0.019) and vendor type (Welch F 3.58, Holm p = 0.020, omega squared 0.015).

The 30 written responses came from C135, the comment field on the employer's capability (16), and C030, on what the respondent loves most about the job (14). Eighteen were positive and ten negative. The responses to C030 named knowledge of a financial domain gained on the engagement. Most of the responses to C135 described respondents who arrived without that knowledge, and several described days of generic training and a domain learned from colleagues on live work. No written outcome test reached significance.

Ratings of 3 or below, the distressed range, accounted for 217 of the 796 answers (27.26%). The engagement mean fell in the distressed range in 25 of 150 engagements.

All 30 responses were secondary. Each answered a question outside the indicator's survey section and addressed the indicator in its content. They came from 2 questions. That secondary share ranked 1st from the highest among the 11 Part 4 indicators with 30 or more written responses, tied with seven other indicators, against a median of 100.00%.

Each of the fourteen responses to C030 named knowledge of a financial domain gained on the engagement among the things the respondent loves most about the job: payments, underwriting, endorsements, financial planning and analysis, valuation, tax and supply-chain finance. Several listed it beside a hard engagement, one closing with relief that the work had ended.

Nine responses to C135 said the respondent arrived without knowledge of the domain: no idea what an APS, a capital call or a structuring pattern was, or how settlement, custody or a trading floor worked. Seven described training of days or of generic material before live work, such as a two-day induction, two e-learning modules and a recording, or a slide deck about banking. Seven said the respondent learned the domain from a seatmate, a senior or a colleague who was also new, and five said no one on the team, or few of its leads, came from the domain. One respondent learned what a side letter was from the questionnaire under review, and another said the team read a suitability rule for the first time when the tool flagged an adviser call.

Four responses said the domain training had worked, in fund accounting, payments, valuation and trading, and two of these placed the gap in training on the agent tools instead.

Of the 30 responses, 10 (33.33%, 95% CI 17.86% to 52.00%) were negative and 3 (10.00%) carried the strongest negative score of −10. Positive responses numbered 18 (60.00%), and 2 were neutral. The mean written score was 0.8 (95% CI −1.3 to 2.6, n = 30 responses), and the median was 5.0.

Of the 30 responses, 27 came from respondents who also rated the indicator. Among them, the written score did not track the rating (Spearman rho 0.12, 95% CI −0.29 to 0.55, p = 0.559, n = 27 responses). Of the 8 negative responses with a rating, 2 came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 27, with a mean rating of 4.4. The 769 respondents who rated the indicator without writing about it had a mean of 4.9. The difference, −0.4 (95% CI −1.4 to 0.6), included zero. Ratings in the distressed range made up 37.04% of the ratings from respondents who wrote (10 of 27) and 26.92% of the ratings from respondents who did not (207 of 769).

Every figure in the segment tables is at respondent level. Segments with fewer than 30 respondents carry no interval. Segments with fewer than 10 report counts only.

Segment families recorded at engagement level were tested on engagement means. Respondent role and vendor type were tested on respondents. Where an expected count fell below 5, the test of the distressed share used Fisher's exact test for a two-by-two table, marked exact, or a Monte Carlo test, marked simulated. After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 34.66, Holm p < 0.001, omega squared 0.363). Active engagements in Build-Out rated highest (mean 5.8, n = 163 respondents) and canceled engagements lowest (mean 3.5, n = 309 respondents). Ratings also differed by respondent role (Welch F 10.04, Holm p < 0.001, omega squared 0.019). Portfolio directors rated highest (mean 6.1, n = 28 respondents) and individual contributors lowest (mean 4.7, n = 617 respondents). Ratings also differed by vendor type (Welch F 3.58, Holm p = 0.020, omega squared 0.015). Pure-play agentic AI firms rated highest (mean 5.2, n = 68 respondents) and BPO specialists lowest (mean 4.5, n = 187 respondents). Outsourcing model, institution type, process family and class of work showed no difference.

Written sentiment did not differ by engagement status and lifecycle stage across the 21 engagements with a written response (Kruskal-Wallis H 0.81, df 2, p = 0.668). Of the groups with 10 or more responses, responses from active engagements in Transition/Cut-Over were the most negative (mean −0.5, 11 responses) and responses from canceled engagements the least negative (mean 1.4, 11 responses). Responses from active engagements in Build-Out (8) are reported as counts only.

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 27 and engagement managers wrote 3 responses, reported as counts only.

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.

Across the study set, higher ratings came with less cancellation (r = −0.61, 95% CI −0.70 to −0.50, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in sixteen of the 20 segment levels tested.

Customer satisfaction is the percentage recorded against each engagement. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

Across the active engagements, higher ratings came with higher customer satisfaction (r = 0.77, 95% CI 0.68 to 0.84, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in fifteen of the 16 segment levels tested.

The engagement indicator mean is the mean of an engagement's ratings across the rated indicators, measured at engagement level (150 engagements). The indicator does not enter the mean.

Higher ratings came with a higher engagement indicator mean (r = 0.80, 95% CI 0.73 to 0.85, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in twenty-three of the 24 segment levels tested.

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. It is measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

Respondents who gave higher ratings reported lower intent to leave (r = −0.76, 95% CI −0.79 to −0.72, Holm p < 0.001, n = 750 respondents). The association held after Holm correction in thirty-seven of the 37 segment levels tested.

Two comparisons set the engagements with at least one negative response against all other engagements. Of the 140 other engagements, 129 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 10 engagements with a negative response, 3 (30.00%) were canceled, against 53 of the 140 other engagements (37.86%). The difference did not reach significance (Fisher exact p = 0.744). The comparison of customer satisfaction was not computed, because one of the two groups held too few active engagements.

Two correlations test written sentiment directly. Across the 21 engagements with a written response, the engagement mean written score was not associated with cancellation (point-biserial r −0.07, p = 0.760). Across 29 respondents, the respondent mean written score was not associated with intent to leave (Spearman rho −0.10, p = 0.597). Of the three comparisons, none reached significance at 0.05.

The four associations were compared in pairs on their engagement-level forms, each oriented so that a higher value is the better outcome, across the 150 engagements with all four measures. After Holm correction, five of the six pairs differed. The association with the engagement indicator mean was the strongest and the association with cancellation the weakest. The associations with customer satisfaction and the engagement indicator mean did not differ (Holm p = 0.113).

Answers clustered within engagements (ICC 0.61). Clustering reduced the 796 respondent answers to the equivalent of about 219 independent answers. Respondent-level intervals therefore used the cluster bootstrap. Respondent-level tests of intent to leave used standard errors that allow for clustering by engagement.

No association was equivalent to zero. Each of the four differed from zero. The detection floor shown is the study floor at 150 engagements. Intent to leave was tested on its effective sample size.

Each change was computed before rounding and may differ by 0.01 from the difference between the two printed values.

All 22 checks held. A check holds when its test falls on the same side of 0.05 as the primary test. Where the primary test falls below 0.05, the check must also keep the sign of the primary correlation. The thin-base check removes the engagements in any level of outsourcing model or process family with fewer than 30 engagements. Institution type is not used for that check, because every one of its levels has fewer than 30 engagements.

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.

Each deviation was computed before rounding and may differ by 0.01 from the difference between the two printed values.

The comparison covered 150 engagements. The indicator departed from the study's typical pattern on intent to leave. Its association was stronger than the norm on intent to leave.

Among the 11 Part 4 indicators with 30 or more written responses, the indicator's share of negative responses, 33.33%, ranked 6th from the highest, against a median of 33.33%. Its mean written score, 0.8, ranked 6th from the most negative, against a median of 0.8.

The indicator most often present in the same responses was C125, “Rate how well your employer's training programs build financial industry knowledge.”, in 11 of the 30 responses (36.67%). C123, “Rate the adequacy of your employer's investment in training its workforce.” (10 responses), C120, “Rate the depth of your employer's knowledge of the financial industry.” (5 responses), C084, “My manager cares about the larger team.” (4 responses) and C018, “How happy are you with your current job?” (3 responses) followed.

The most frequent theme was “Skills learned”, in 16 responses (53.33%). The second was “Team or colleagues”, in 9 responses.

Over a quarter of all ratings of how well respondents know the financial industry fell in the distressed range (217 of 796 answers, 27.26%). The rating was associated with all four study measures, and every association held under each of the 22 robustness checks. Its association with the engagement indicator mean was strong (r = 0.80, n = 150 engagements), although the self-assessment is not one of the rated indicators. Canceled engagements rated far below the three active stages (mean 3.5, n = 309 respondents).

The written evidence describes delivery teams placed on live financial work before they knew the domain and taught by their colleagues rather than by the vendor. The same knowledge, once gained, was what many respondents valued most in the job. No written outcome test reached significance.

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.

Tests by respondent role and by vendor type treated respondents as independent. The section on clustering reports how far clustering within engagements reduced the information in respondent-level figures.

Customer management executives gave 1 answers, a base of anecdote strength.

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 (30 responses on 21 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.

The rating is a self-assessment of the respondent's own knowledge and not a measure of it.