FINNBARR: Financial Networks Background, Audit, Recon, and Reporting

FINNBARR：金融网络背景、审计、侦察和报告

• 批准号: 59258
• 金额: $ 6.35万
• 依托单位: ANALYTICS ENGINES LIMITED
• 依托单位国家: 英国
• 项目类别: Responsive Strategy and Planning
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=59258
• 关键词: FINNBARR; Financial; Networks; Background; Audit

The current Covid-19 Pandemic has put increased pressure on the Financial Services industry in terms of supporting remote working, dealing with sickness, and seeing unprecedented demand for government backed schemes. This provides the opportunity, as highlighted in the Industrial Strategy Challenge Fund -- Next Generation Services, for AI and data analytics to assist humans in their work.This project employs natural language processing, machine learning, and knowledge-graph technologies to build up a comprehensive picture of UK companies through their connections through people, places, events, and documents. By creating a user-friendly interface for querying and exploring this data, productivity of staff within the Financial Services sector can be improved, as well as reducing risk through having a better visibility of the network of connections surrounding a company and proactive monitoring of this data for changes. Using a semantic layer on top of the data allows users to query meaning in the data, as well as creating connections based on these results. Overall, this project aims to provide next generation software into the Financial Services sector which can help to improve its response time during the next crisis through the intelligent usage of technology.

当前的 Covid-19 大流行给金融服务业带来了越来越大的压力，包括支持远程工作、处理疾病以及对政府支持计划的前所未有的需求。正如工业战略挑战基金——下一代服务所强调的那样，这为人工智能和数据分析提供了协助人类工作的机会。该项目采用自然语言处理、机器学习和知识图谱技术，通过人员、地点、事件和文档之间的联系来构建英国公司的全面概况。通过创建一个用户友好的界面来查询和探索这些数据，可以提高金融服务部门员工的工作效率，并通过更好地了解公司周围的连接网络并主动监控这些数据的变化来降低风险。在数据之上使用语义层允许用户查询数据中的含义，并根据这些结果创建连接。总体而言，该项目旨在为金融服务行业提供下一代软件，通过智能技术的使用，帮助提高其在下一次危机中的响应时间。