JFAC Minimum Viable Product Delivery

Tender description

Summary of the work Development and delivery of the Minimum Viable Product of an advanced analytics capability for financial crime intelligence. Expected Contract Length March 2018 Latest start date 15/05/2017 Why the Work is Being Done The Joint Financial Analysis Centre, staffed by members of FCA, HMRC, NCA, and SFO, was established to provide a world-class capability to create actionable intelligence on financial crime. Advanced analytics are central to JFAC’s capability and while existing capabilities meet today’s needs, they will not address future demands. Problem to Be Solved Following the initial exploratory work, the JFAC project is looking to select a supplier to deliver a Minimum Viable Product (MVP) that will be used by analysts to provide operational intelligence. It is expected that the MVP will support two distinct types of intelligence operations during this period, starting with an initial baseline capability that increases in functional richness as it develops. The two intelligence operations will be supported by three analytic types: Index and search, including self-service batch capability Entity extraction, matching and visualisation from structured and unstructured data Graph analysis techniques and automation to identify potentially interesting phenomena. Who Are the Users The Joint Financial Analysis Centre, staffed by members of FCA, HMRC, NCA, and SFO who need to develop financial crime intelligence, using an advanced analytics capability. Early Market Engagement As part of assessing achievability, a survey has been undertaken to identify technologies, products and designs that can address the type and nature of challenge faced by JFAC. Engagements have been undertaken with Other Government Departments and industry. Work Already Done The initial requirements/design work developed outline architecture and identified candidate technologies. JFAC’s data covers structured, semi-structured and unstructured data in a variety of files format. Volume/variety of data is materially different to that processed by HMG analytical systems or commercial alternatives. Core approach is based around the Apache/Hadoop stack. Solution will be deployed in the infrastructure-as-a-service cloud environment, not using vendor specific services. Must holistically manage the data lifecycle and data access at a fine grain level. Ideally this will be with a single toolset that encompasses both the core Apache components and extended, where appropriate, to the wider architecture. Existing Team The existing team consists of intelligence officers and analysts from NCA, HRMC, SFO and FCA. They are supported by client-side professional services to deliver the programme. Current Phase Alpha Skills & Experience • Experience of developing ‘big data’ analytics solutions. • Experience in graph theory, management of graph complexity and graph embedding, demonstrated through past implementations of graph databases (e.g. Neo4J, Accumulo). • Experience of indexing of large, unstructured text sets (e.g. Solr or elasticsearch). • Experience in natural language processing, machine vision and OCR (e.g. Tesseract, Tikka and NLTK) • Experience of successfully delivering projects with similar scope using agile (e.g. scrum) methodology. • Experience working collaboratively with internal teams, who have limited agile development experience. The supplier is required to actively participate/lead some of the workshops followed by iterative development. • Ability to adopt a flexible and scalable resourcing and delivery model that assures the project is effectively resourced in a way that enables us to meet our timescales. • Relevant technical expertise (including accessibility standard 'W3C AA' and secure coding standards) and evidence of applicable technical qualifications/accreditations. • Experience of developing and delivering training to key users • Experience in legal, regulatory and security compliance. • Experience in successfully applying and extending fine-grained access control and data provenance in Hadoop (e.g. Apache Atlas, Ranger and Sentry). • It is anticipated that the supplier will need to extend the stock features in CDH / HDP. • Experience in Hadoop, including CDH / HDP. End-to-end expertise is required – from administration, provisioning, persistence to variety of processing engines • (principal focus on Spark, however experience with other engines are also desirable). Nice to Haves • Experience of finance, law enforcement and intelligence sectors is desirable. • Experience deploying onto Microsoft Azure • Academic qualifications (e.g. MSc, PhD) in natural language processing, machine vision and OCR Work Location National Crime Agency ( NCA ) (Tinworth Street, London SE11 5EF) and supplier’s own premises. Working Arrangments The user team are located at Tinworth Street. Suppliers will need to accommodate working at OFFICIAL SENSITIVE from their own premises. Security Clearance Minimum of SC Additional T&Cs Freedom of Information Act Clause will be amended, details will be provided on request. No. of Suppliers to Evaluate 5 Proposal Criteria • Written proposal, no longer than 20 pages, excluding appendices, that covers: • a. An overview of the supplier’s organisation • b. The supplier’s understanding of the task and key challenges in undertaking it, specifically the: • i. Approach, including mobilising the team • ii. Team to deliver the Minimum Viable Product including SFIA grades, roles and skills • iii. Supplier’s ability to operate at OFFICIAL SENSITIVE • iv. Approach to aligning with the JFAC culture and ways of working • v. Proposal for working at their own premises, with an operational JFAC team based in central London • c. Relevant Track Record • d. Total price presented on a monthly basis, by individual and with expenses clearly identified where relevant. Cultural Fit Criteria JFAC is a dynamic team that is evolving and responding to emerging demands. Alignment with the culture is an essential component of any suppliers. Payment Approach Time and materials Evaluation Weighting Technical competence 50% Cultural fit 20% Price 30% Questions from Suppliers No questions have been answered yet.