Lot 1
No lot description published.
Buyer: Futures Housing Group →
Income collection tool, to reduce rent arrears and maximise customer contact, by focusing resources. We are looking for a solution designed to enhance our arrears management processes. This tool will leverage advanced technologies to provide a comprehensive view of customer debt and tenancy types, while also utilising AI and machine learning to optimise caseload management. The solution will need to: 1. Engage customers most in need through risk-base prioritisation. 2.Provide a consolidated view of all debt and tenancy types, including CTA, FTA, Sub Accounts, Leasehold, etc. 3. Utilise AI and machine learning to learn from officer and customer behaviours, creating an accurate caseload of customers requiring support. 4. Deliver personalised messages via the preferred contact method, with the right message at the right time through intelligent automation. 5. Support officers with "Outcome Impact" to inform future decision-making based on previous successful interventions. 6. Consolidate all relevant information with notes, payments, and case history on a single screen, plus quick search functionality for officers' convenience. 7. Drive positive actions and outcomes through the use of behavioural science and nudge theory. 8. Empower officers on the go and enhance productivity with a mobile responsive solution.
UK, GB
No lot description published.
| Item | Category | Quantity |
|---|---|---|
| 1 | Software package and information systems | Not published |
Benchmarked against retained Find a Tender procedures with CPV division 48. The category anchor is Software package and information systems (48000000); this is a deliberately broad market comparator. The comparison is shown at several levels rather than pretending one company or region is always the best benchmark.
| Comparison set | Procedures | Reported bids per procedure | Named award suppliers | Price evidence |
|---|---|---|---|---|
| Market: CPV division 48 | 6,836 | 1 median · 9.6 average (2,488 of 6,836 with a bid count) | 1.7 average (2,927 of 6,836 with named award suppliers) | Not published |
| Same buyer | 1 | Not published | Not published | Not published |
| Delivery region: UK | 1,892 | 2 median · 22.6 average (612 of 1,892 with a bid count) | 3 average (732 of 1,892 with named award suppliers) | Not published |
“Reported bids” is an official aggregate, sometimes reported per lot; it is the closest available competition measure. “Named award suppliers” are winners, not all applicants.
Not enough comparable procedures currently publish both a GBP tender value and a usable lowest-valid-bid value to calculate a responsible price-reduction benchmark. Tenderline deliberately does not infer a saving from named award suppliers or from missing award values.
| Milestone | Type | Due | Status |
|---|---|---|---|
| We are looking to see what software is available in the market place specifically for the collection of rent arrears. Deadline:23.07.2025 Please contact procurementteam@futureshg.co.uk | engagement | 23 Jul 2025 | scheduled |
No linked framework, prior procurement or reprocurement published.
Diagnostic view. “Not published” means this current release does not provide a value.
| OCID | ocds-h6vhtk-0551e7 |
|---|---|
| Latest release ID | 034452-2025 |
| Latest release timestamp | Mon Jun 23 2025 14:19:17 GMT+0000 (Coordinated Universal Time) |
| Source | find-a-tender |
| Official notice URL | Not published |
| Tender status | planning |
| Procurement method | Not published |
| Procurement method details | Not published |
| Main procurement category | goods |
| Above threshold | No |
| Legal basis | 2023/54 |
| Tender period: start | Not published |
| Tender period: end | Not published |
| Expression of interest deadline | Not published |
| Enquiry deadline | Not published |
| Award period: start | Not published |
| Award period: end | Not published |
| Submission method details | Not published |
| Submission languages | Not published |
| Electronic catalogue policy | Not published |
| Total tender value | Not published |
| Tender lots in source | 1 |
| Tender items in source | 1 |
| Tender documents in source | 0 |
| Awards in latest release | 0 |
| Contracts in latest release | 0 |
| Parties in latest release | 1 |
| Date | Event | Reference |
|---|---|---|
| 23 Jun 2025 | planning | 034452-2025 |
Unmodified official OCDS data retained by Tenderline for this procurement process.
{
"id": "034452-2025",
"tag": [
"planning"
],
"date": "2025-06-23T15:19:17+01:00",
"ocid": "ocds-h6vhtk-0551e7",
"buyer": {
"id": "GB-COH-06293737",
"name": "FUTURES HOUSING GROUP LIMITED"
},
"tender": {
"id": "FHG_2025P053",
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],
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"description": "Income collection tool, to reduce rent arrears and maximise customer contact, by focusing resources.\nWe are looking for a solution designed to enhance our arrears management processes. This tool will leverage advanced technologies to provide a comprehensive view of customer debt and tenancy types, while also utilising AI and machine learning to optimise caseload management.\nThe solution will need to:\n1. Engage customers most in need through risk-base prioritisation.\n2.Provide a consolidated view of all debt and tenancy types, including CTA, FTA, Sub Accounts, Leasehold, etc.\n3. Utilise AI and machine learning to learn from officer and customer behaviours, creating an accurate caseload of customers requiring support.\n4. Deliver personalised messages via the preferred contact method, with the right message at the right time through intelligent automation.\n5. Support officers with \"Outcome Impact\" to inform future decision-making based on previous successful interventions.\n6. Consolidate all relevant information with notes, payments, and case history on a single screen, plus quick search functionality for officers' convenience.\n7. Drive positive actions and outcomes through the use of behavioural science and nudge theory.\n8. Empower officers on the go and enhance productivity with a mobile responsive solution.",
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],
"language": "en",
"planning": {
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}
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}{
"id": "034452-2025",
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"id": "2023/54",
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"scheme": "UKPGA"
},
"description": "Income collection tool, to reduce rent arrears and maximise customer contact, by focusing resources.\nWe are looking for a solution designed to enhance our arrears management processes. This tool will leverage advanced technologies to provide a comprehensive view of customer debt and tenancy types, while also utilising AI and machine learning to optimise caseload management.\nThe solution will need to:\n1. Engage customers most in need through risk-base prioritisation.\n2.Provide a consolidated view of all debt and tenancy types, including CTA, FTA, Sub Accounts, Leasehold, etc.\n3. Utilise AI and machine learning to learn from officer and customer behaviours, creating an accurate caseload of customers requiring support.\n4. Deliver personalised messages via the preferred contact method, with the right message at the right time through intelligent automation.\n5. Support officers with \"Outcome Impact\" to inform future decision-making based on previous successful interventions.\n6. Consolidate all relevant information with notes, payments, and case history on a single screen, plus quick search functionality for officers' convenience.\n7. Drive positive actions and outcomes through the use of behavioural science and nudge theory.\n8. Empower officers on the go and enhance productivity with a mobile responsive solution.",
"aboveThreshold": false,
"mainProcurementCategory": "goods"
},
"parties": [
{
"id": "GB-COH-06293737",
"name": "FUTURES HOUSING GROUP LIMITED",
"roles": [
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],
"address": {
"region": "UKF22",
"country": "GB",
"locality": "Castle Donington",
"postalCode": "DE74 2SA",
"countryName": "United Kingdom",
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],
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{
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"dueDate": "2025-07-23T23:59:59+01:00",
"description": "We are looking to see what software is available in the market place specifically for the collection of rent arrears.\nDeadline:23.07.2025\nPlease contact procurementteam@futureshg.co.uk"
}
]
},
"initiationType": "tender"
}