Acuity: Transforming insurance management and understanding for consumers
敏锐度:改变保险管理和消费者的理解
基本信息
- 批准号:10031668
- 负责人:
- 金额:$ 44.51万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Collaborative R&D
- 财政年份:2022
- 资助国家:英国
- 起止时间:2022 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The insurance sector has the lowest levels of consumer trust among financial services, with 30% of consumers reporting mistrust (FCA, 2020). Mistrust is driven primarily by misleading terms and conditions (53%) and unclear content (34%; FCA, 2020). Indeed, a UK study found that consumers must be educated to at least A-level, but in the majority of cases graduate or even postgraduate level, in order to meaningfully understand their insurance policies (BrowneJacobson, 2018). Consequently, when choosing either motor or home insurance, most consumers (76%+) select a policy based on price rather than features (FCA, 2020). Feature differences between policies are difficult to identify and assess, yet vital to ensuring the right cover is in place. For example, if a user misses a flight home, does their travel insurance cover accommodation until the next flight? It is also commonplace for consumers to forget their policy renewal date and even their insurance provider.Founded in Cambridge in 2019, Rnwl's mission is to make it easier for consumers to manage their insurance policies, find the best possible coverage for the best price, and avoid spending hours renegotiating and renewing every year. Starting with motor insurance, we have built a consumer app (available to download on Apple and Android). Our app keeps track of the renewal dates of a user's car insurance, MOT, tax, and breakdown cover, as well as recording vital policy details such as provider, policy number, and contact details, which could be needed urgently in the event of an accident. When it comes to insurance renewal, we provide the user with quotes at the optimum time to purchase a new policy.With support from Innovate UK, we have developed an analytical engine that uses natural language processing (NLP) and machine learning (ML) algorithms to extract key policy features at scale, using this data to help consumers manage their motor insurance policies. Here, we will extend our cutting-edge NLP and ML algorithms to improve user readability and comprehension. Our technology will effectively reduce the required insurance policy reading age from up to postgraduate level to that of a 12-13 year old i.e. from the level of a scientific journal to the level of the BBC website (BrowneJacobson, 2018). By developing a solution that works for consumers at scale, spanning unstandardised insurance policies from multiple insurance providers, we will disrupt the insurance industry, and ensure maximum value and peace of mind for UK consumers.
在金融服务业中,保险业的消费者信任度最低,30% 的消费者表示不信任(FCA,2020)。不信任主要是由误导性条款和条件 (53%) 以及内容不明确 (34%;FCA,2020) 造成的。事实上,英国的一项研究发现,消费者必须至少接受过 A 级教育,但在大多数情况下是研究生甚至研究生水平,才能有意义地理解他们的保险政策(BrowneJacobson,2018)。因此,在选择汽车保险或家庭保险时,大多数消费者 (76%+) 根据价格而不是功能来选择保单(FCA,2020)。保单之间的特征差异很难识别和评估,但对于确保提供正确的保障至关重要。例如,如果用户错过了回家的航班,他们的旅行保险是否涵盖下一航班之前的住宿?消费者忘记保单续保日期甚至保险提供商的情况也很常见。Rnwl 于 2019 年在剑桥成立,其使命是让消费者更轻松地管理他们的保单,以最优惠的价格找到最佳的保险范围,并避免每年花费大量时间重新谈判和续保。从汽车保险开始,我们构建了一个消费者应用程序(可在 Apple 和 Android 上下载)。我们的应用程序会跟踪用户的汽车保险、MOT、税收和故障保险的续订日期,并记录重要的保单详细信息,例如提供商、保单编号和联系方式,这些信息在发生事故时可能会紧急需要。在保险续保方面,我们在最佳时间为用户提供购买新保单的报价。在 Innovate UK 的支持下,我们开发了一个分析引擎,使用自然语言处理 (NLP) 和机器学习 (ML) 算法大规模提取关键保单特征,利用这些数据帮助消费者管理他们的汽车保险保单。在这里,我们将扩展我们最先进的 NLP 和 ML 算法,以提高用户的可读性和理解性。我们的技术将有效地将所需的保单阅读年龄从研究生水平降低到12-13岁,即从科学期刊水平降低到BBC网站水平(BrowneJacobson,2018)。通过开发适合大规模消费者的解决方案,涵盖多家保险公司提供的非标准化保险单,我们将颠覆保险业,并确保英国消费者获得最大价值和安心。
项目成果
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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其他文献
Internet-administered, low-intensity cognitive behavioral therapy for parents of children treated for cancer: A feasibility trial (ENGAGE).
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- DOI:
10.1002/cam4.5377 - 发表时间:
2023-03 - 期刊:
- 影响因子:4
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Differences in child and adolescent exposure to unhealthy food and beverage advertising on television in a self-regulatory environment.
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- DOI:
10.1186/s12889-023-15027-w - 发表时间:
2023-03-23 - 期刊:
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The association between rheumatoid arthritis and reduced estimated cardiorespiratory fitness is mediated by physical symptoms and negative emotions: a cross-sectional study.
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- DOI:
10.1007/s10067-023-06584-x - 发表时间:
2023-07 - 期刊:
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10.1186/s12859-023-05245-9 - 发表时间:
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Amplified EQCM-D detection of extracellular vesicles using 2D gold nanostructured arrays fabricated by block copolymer self-assembly.
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- DOI:
10.1039/d2nh00424k - 发表时间:
2023-03-27 - 期刊:
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的其他文献
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