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ANC.h.o.R FINANCIAL WELLBEING INSIGHTS · 2026

What 1,550+ employee journeys taught us about financial wellbeing.

Aggregated, anonymised observations from ANC.h.o.R programmes across 15 employers in France, Germany and the UK. Different measures use different participant subsets. Findings are observational and are not guarantees of individual outcomes.

~1,550employees through ANC.h.o.R pilots
15participating employers across 3 countries
84%completion among employees who opted in
83%of ~1,200 respondents reporting a positive day-to-day impact
PROGRAMME OUTCOMES

The strongest signals in the current dataset.

These figures describe measured programme observations. Where a before/after change is shown, it should be read as an association within the observed cohort—not proof that the programme alone caused the change.

85% / 96%

Employee / employer satisfaction

Post-programme satisfaction reported by employees and participating employers.

73%

Employers requesting continuation

Share of participating employers requesting an ongoing programme after the initial pilot.

+13.4 pts

Five-year retention intent

Positive responses rose from 59.4% before the pilot to 72.8% at six-month follow-up.

−54%

Observed employee departures

In a subgroup of 8 employers of roughly 250 employees, mean departures moved from 10 to 4.6 over comparable six-month periods.

+42%

ANC.h.o.R Financial Quality Index

Average six-month improvement across 600+ PWO clients. The proprietary index covers dimensions including purchasing power, savings capacity and financial buffer.

€175/mo

Average capacity identified

Across analysed participants earning €2,500+ per month. About €150/month was actually set aside on average; some remaining capacity was redirected to quality-of-life spending.

Higher-income/freelance subgroup: €271/month mean capacity identified among the relevant participants. These subgroup figures use different denominators from the full employee survey pool.
FINANCIAL FRICTIONS

Small recurring inefficiencies show up again and again.

ANC.h.o.R defines a financial friction as a recurring cost or structural feature that creates avoidable cost, complexity or inefficiency.

42%

Unused or redundant subscriptions/services

At least one unused or redundant recurring item identified.

34%

Reducible banking fees

Cases where banking costs with realistic reduction potential were identified.

22%

Overlapping insurance

Cases with duplicated or overlapping coverage identified.

Median: 10 financial frictions identified per client. Average: about 3 accounts per participant. Duplicate subscriptions are the most common friction in the current dataset.
SELECTED ANONYMISED CASES

What the numbers look like in real financial systems.

These ten selected cases illustrate the type of work performed and are not a statistical sample. Results depend on income, existing costs, implementation and personal priorities.

ANONYMISED CASE

Camille — Marketing Manager

France
€45k–€55k/year
6financial frictions
€410/mocapacity identified
€350/moactually set aside

Implemented in 3 weeks. Cancelled unused subscriptions, renegotiated mobile and insurance contracts, changed bank package and automated monthly savings.

“I expected to be told to spend less. Instead, I found money I was already losing without really noticing. I now save automatically every month without feeling restricted.”
ANONYMISED CASE

James — Freelance Graphic Designer

UK
£35k–£45k/year
8financial frictions
£520/mocapacity identified
£400/moactually set aside

Implemented in 1 month. Consolidated software, separated business and personal accounts, automated tax and savings allocations, and changed broadband provider.

“The biggest change wasn’t earning more. It was finally knowing what my money needed to do every month. My finances feel much more predictable now.”
ANONYMISED CASE

Lukas — Software Engineer

Germany
€70k–€85k/year
5financial frictions
€780/mocapacity identified
€700/moactually set aside

Implemented in 2 weeks. Reduced fixed costs, reviewed overlapping insurance, structured excess cash and automated monthly transfers.

“I was earning well but had never built a proper system around it. Once everything was structured, saving became something that happened automatically rather than something I had to remember.”
ANONYMISED CASE

Sophie — HR Specialist

France
€30k–€38k/year
7financial frictions
€290/mocapacity identified
€250/moactually set aside

Implemented in 4 weeks. Cancelled low-use subscriptions, reviewed energy and insurance, downgraded banking package and automated an emergency-fund transfer.

“€250 a month felt impossible before. The surprising part was that most of it came from fixing things I barely thought about, not from giving up the things I enjoy.”
ANONYMISED CASE

Oliver — Senior Sales Executive

UK
£80k–£100k/year
9financial frictions
£1,250/mocapacity identified
£1,000/moactually set aside

Implemented in 5 weeks. Automated savings after payday, reviewed insurance and banking products, removed recurring costs and created fixed bonus-allocation rules.

“My income had increased, but somehow my savings hadn’t. Putting a structure around the money made a much bigger difference than I expected.”
ANONYMISED CASE

Anna — Project Manager

Germany
€50k–€65k/year
6financial frictions
€460/mocapacity identified
€400/moactually set aside

Implemented in 3 weeks. Renegotiated recurring contracts, removed unnecessary subscriptions and created separate emergency and travel savings pots.

“Separating my savings by purpose completely changed how I manage money. Bigger expenses no longer feel like they are undoing months of progress.”
ANONYMISED CASE

Thomas — Independent Management Consultant

France
€90k–€120k/year
11financial frictions
€1,650/mocapacity identified
€1,300/moactually set aside

Implemented in 6 weeks. Separated business and personal cash flows, automated tax provisioning, streamlined tools and created a fixed personal savings allocation.

“My finances were profitable but messy. Once the business and personal sides were properly separated, I could finally see how much I could comfortably put aside.”
ANONYMISED CASE

Emily — Operations Coordinator

UK
£28k–£35k/year
5financial frictions
£230/mocapacity identified
£200/moactually set aside

Implemented in 2 weeks. Changed mobile plan, removed unused memberships and duplicate subscriptions, and automated savings immediately after payday.

“Moving my savings to payday instead of month-end was such a simple change, but it made saving £200 feel surprisingly manageable.”
ANONYMISED CASE

Felix — Product Director

Germany
€100k–€130k/year
8financial frictions
€2,100/mocapacity identified
€1,750/moactually set aside

Implemented in 1 month. Consolidated savings accounts, reduced recurring fees, reviewed insurance and created fixed salary and bonus allocation rules.

“I didn’t have a spending problem; I had an allocation problem. Once every euro had a purpose, the amount I could put toward my goals became much clearer.”
ANONYMISED CASE

Claire — Freelance Copywriter

France
€35k–€45k/year
7financial frictions
€370/mocapacity identified
€300/moactually set aside

Implemented in 5 weeks. Separated professional and personal spending, reduced software subscriptions and introduced percentage-based tax and savings allocations on every invoice.

“Freelance income will always fluctuate, but my savings don’t feel random anymore. Having percentages automatically allocated whenever I get paid has made a huge difference.”
METHODOLOGY & LIMITS

Useful data, with the limits visible.

Population
Approximately 1,550 employees participated in ANC.h.o.R pilots across 15 employers.
Employer mix
7 employers with 50–200 employees, 3 with 200–500 and 5 with 500–1,000. 9 in France, 3 in Germany and 3 in the UK.
Main survey pool
Approximately 1,200 employees. Some measures use smaller subgroups or six-month follow-up cohorts.
Financial Quality Index
Based on 600+ PWO clients followed for six months. The index is proprietary; its published description covers purchasing power, ability to save and ability to build a financial buffer, among other dimensions.
Departure observation
8 employers of roughly 250 employees in the tracked subgroup; mean departures moved from 10 to 4.6 over comparable six-month periods.
Confidentiality
Participating employers are not named. Published findings are aggregated, and the cases on this page are anonymised.
Interpretation
These are observational programme findings. They do not by themselves establish causality and should not be interpreted as guaranteed outcomes.