--- title: "MARKET ENGAGEMENT on behalf of NHS CFA- Advanced Analytical Data Science Capability to Counter Fraud in the NHS - Delivery Partner" ocid: "ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c" canonical_url: "https://d3tenders.com/contract/?ocid=ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c" markdown_url: "https://d3tenders.com/contract/ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c.md" json_url: "https://d3tenders.com/contract/ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c.json" source: "Contracts Finder" current_stage: "Planning" buyer: "NHS SHARED BUSINESS SERVICES" published: "2023-09-29" --- # MARKET ENGAGEMENT on behalf of NHS CFA- Advanced Analytical Data Science Capability to Counter Fraud in the NHS - Delivery Partner Buyer: NHS SHARED BUSINESS SERVICES Current stage: Planning OCID: ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c [View canonical contract page](https://d3tenders.com/contract/?ocid=ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c) [Download OCDS JSON](https://d3tenders.com/contract/ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c.json) ## Summary The NHS Shared Business Services is looking for a Delivery Partner for an advanced analytical data science capability project to counter fraud in the NHS. The procurement is currently in the planning stage with an engagement end date of 9th October 2023. The project is expected to start in October 2023 and deliver its objectives by the end of March 2025. The location of the project is in SALFORD, England, with a focus on data analysis services within the healthcare industry. This tender by the NHS presents an opportunity for businesses specializing in data analysis services, particularly those with expertise in advanced analytical techniques and fraud detection. SMEs with experience in innovative data analysis to counter fraud would be well-suited to compete for this project. The selected partner will help the NHS become a Centre of Excellence for analytical fraud detection and pattern identification, contributing to the protection of NHS funds from fraud by leveraging data science capabilities. ## Notice It is the NHSCFA's intention to use advanced analytical techniques underpinned by data science including machine learning, together with the integration of technology to not only help stop known frauds but predict and uncover those that have yet to occur or those that have yet to be reported or observed. By creating a data science technological capability and utilising the copious amount of data captured each day in the NHS. Harnessing the power of expertise, then actionable outcome through an evidence-based data science approach to fraud detection will not only identify novel patterns of concern but unlock the value of data meaning abuse can be detected earlier in turn protecting NHS funds from fraud. The inclusion of fraud detection techniques will also highlight patterns in data that will identify previously unseen fraud trends, therefore improving the time to action. The requirement is to secure a partner to build our advanced analytical capability and data environment. We require a partner who has supported organisations drive forward innovative data analysis to counter fraud. They will support NHSCFA to become a Centre of Excellence for analytical fraud detection and pattern identification. We are looking to start the project in October 2023 and deliver the objectives of the project by the end of March 25 Please refer to the full draft specification document for details. ## Key Details | Field | Value | | --- | --- | | Publication source | Contracts Finder | | Latest notice | https://www.contractsfinder.service.gov.uk/Notice/cee8d817-0665-46b8-8d6d-2a958762f716 | | Notice type | Market Engagement Notice | | Procurement type | Standard | | Procurement category | Not specified | | Procurement method | Not Specified | | Procurement method details | Not specified | | Tender suitability | SME | | Awardee scale | Not specified | | All stages | Planning | ## Dates | Field | Value | | --- | --- | | Publication date | 29 Sep 2023 | | Submission deadline | Not specified | | Future notice date | 9 Oct 2023 | | Award date | Not specified | | Contract period | Not specified | | Recurrence | Not specified | ## Values | Field | Value | | --- | --- | | Tender value | Not specified | | Lots value | Not specified | | Awards value | Not specified | | Contracts value | Not specified | ## Status | Field | Value | | --- | --- | | Tender status | Planning | | Lots status | Not specified | | Awards status | Not specified | | Contracts status | Not specified | ## Buyer | Field | Value | | --- | --- | | Main buyer | NHS SHARED BUSINESS SERVICES | | Locality | SALFORD | | Post town | Manchester | | Postcode | M50 2UW | | Country | England | | ITL 1 | TLD North West (England) | | ITL 2 | TLD3 Greater Manchester | | ITL 3 | TLD34 Greater Manchester South West | | Local authority | Salford | | Electoral ward | Quays | | Westminster constituency | Salford | | Delivery location | Not specified | ## CPV Codes ### Divisions - 72 - IT services: consulting, software development, Internet and support ### Codes - 72316000 - Data analysis services ## Release History - 29 Sep 2023 at 09:59 - Planning - Market Engagement Notice - https://www.contractsfinder.service.gov.uk/Notice/cee8d817-0665-46b8-8d6d-2a958762f716 - 28 Sep 2023 at 16:39 - Planning - Market Engagement Notice - https://www.contractsfinder.service.gov.uk/Notice/cee8d817-0665-46b8-8d6d-2a958762f716 ## Documents - https://www.contractsfinder.service.gov.uk/Notice/cee8d817-0665-46b8-8d6d-2a958762f716 29th September 2023 - Early engagement notice on Contracts Finder - https://discovery.ariba.com/rfx/17577460 Please access the procurement portal using the link https://discovery.ariba.com/rfx/17577460 to respond to the Market Engagement Questionnaire(MEQ) ## Provenance This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-b5fd17-5288f571-cb1d-40a7-a610-7698bd8f1e1c.json.