Award

Transaction Risking DataOps

DEPARTMENT FOR WORK AND PENSIONS

This public procurement record has 1 release in its history.

Award

08 Aug 2022 at 16:24

Award Notice
Summary of the contracting process

The Department for Work and Pensions has awarded a contract for the project titled "Transaction Risking DataOps" to Scott Logic. This contract falls under the IT services category and involves developing a cloud-based analytics platform to enhance fraud and error prevention in benefit payments. The procurement method used was selective, with a tender period that ended on 7th August 2022. The contract value is £1,624,184, and the contract period is from 10th August 2022 to 31st March 2023, with the procurement stage at the award phase.

This tender presents an opportunity for businesses providing IT services, consulting, and software development to compete by offering solutions for real-time fraud and error prevention in benefit systems. Companies with expertise in cloud-based analytics, machine learning, and data integration can find potential for growth in this project. The contract, issued by the Department for Work and Pensions, aims to improve fraud detection capabilities and streamline data workflows to reduce benefit overpayments and enhance decision-making processes.

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Notice Information

Notice Title

Transaction Risking DataOps

Notice Description

The Covid-19 pandemic has caused an unprecedented surge in demand on the welfare system, resulting in a hugely increased operational workload across DWP. To process benefit claims and pay customers their entitlement, there was an easement of controls that led to increasing levels of fraud and error. This is now at unprecedented levels, with PS8.4bn overpaid in 2020/21. The Integrated Risk and Intelligence Service (IRIS) provides a service to support identification of singleton and organised fraud and error. IRIS has been challenged to be more real time and adapt to changing fraud risks. To deliver a better service, IRIS needs to: - Accelerate fraud and error prevention at the point of application and in advance of payment to reduce benefit overpayment and lower the debt burden on claimants. - Enhance DWP's fraud and error decision making through consolidating sources of risk into a single view of risk to inform routing and intervention types. - Better target operational resource to focus on the highest risk cases associated with the largest financial impact, enabling resourcing to risk. This is being achieved through investment in a cloud-based analytics platform where new fraud and error identification capabilities will be developed including machine learning, and a risk engine that will act as a funnel for all the different risk types and provide a triage function. The project will deliver a core data integration capability that: - Implements event-driven ETL pipelines and self-serve tooling to provide re-useable and extensible data workflows by integrating data from currently available systems and lines of business as well as securely ingesting and integrating 3rd party data (e.g. through automated data pipelines or by setting up API's). Some of these systems may not yet have the ability to interface with Transaction Risking and the infrastructure to support integration may not yet be in place. The Department is driving towards real-time analytics and so data should be incorporated in near real time where that is possible. - Implements a data treatment service with obfuscation of personal data and security controls in place to ensure individuals and tools have appropriate data visibility, while retaining an appropriate level of detail so that the data can be linked and meaningful analysis of the data is still possible. - Implements a data matching capability to resolve common entities across all data sets to enable claimants (and other entities of interest) to be tracked across multiple data sources. This will include creating the ability to link personal data securely in a cloud environment. - Conforms to a consistent data model so data sets from multiple source systems are interoperable, making analytics development and insight generation more efficient. - Is extensible to enable further integration of other event data sources in future e.g. other lines of business or data sources.

Notice Details

Publication & Lifecycle

Open Contracting ID
ocds-b5fd17-5ca501fa-e7b8-4347-95d3-2a3e419a5198
Publication Source
Contracts Finder
Latest Notice
https://www.contractsfinder.service.gov.uk/Notice/206f229d-9fa3-4d25-a750-9c5f20a99c24
Current Stage
Award
All Stages
Award

Procurement Classification

Notice Type
Award Notice
Procurement Type
Framework
Procurement Category
Services
Procurement Method
Selective
Procurement Method Details
Call-off from a framework agreement
Tender Suitability
Not specified
Awardee Scale
Large

Common Procurement Vocabulary (CPV)

CPV Divisions

72 - IT services: consulting, software development, Internet and support

CPV Codes

72000000 - IT services: consulting, software development, Internet and support

Notice Value(s)

Tender Value
£1,624,184 £1M-£10M
Lots Value
Not specified
Awards Value
£1,624,184 £1M-£10M
Contracts Value
Not specified

Notice Dates

Publication Date
8 Aug 20223 years ago
Submission Deadline
7 Aug 2022Expired
Future Notice Date
Not specified
Award Date
7 Aug 20223 years ago
Contract Period
9 Aug 2022 - 31 Mar 2023 6-12 months
Recurrence
Not specified

Notice Status

Tender Status
Complete
Lots Status
Not Specified
Awards Status
Active
Contracts Status
Not Specified

Buyer & Supplier

Contracting Authority (Buyer)

Main Buyer
DEPARTMENT FOR WORK AND PENSIONS
Contact Name
Not specified
Contact Email
mark.cranshaw@dwp.gov.uk
Contact Phone
Not specified

Buyer Location

Locality
BLACKPOOL
Postcode
FY4 5ES
Post Town
Blackpool
Country
England
Major Region (ITL 1)
TLD North West (England)
Basic Region (ITL 2)
TLD4 Lancashire
Small Region (ITL 3)
TLD42 Blackpool
Delivery Location
TLI London
Local Authority
Blackpool
Electoral Ward
Stanley
Westminster Constituency
Blackpool South

Supplier Information

Number of Suppliers
1
Supplier Name

SCOTT LOGIC

Further Information

Open Contracting Data Standard (OCDS)

View full OCDS Record for this contracting process

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The Open Contracting Data Standard (OCDS) is a framework designed to increase transparency and access to public procurement data in the public sector. It is widely used by governments and organisations worldwide to report on procurement processes and contracts. 

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