MMC 通过智能自动化提高生产力并降低风险
技术
- 分析与建模 - 机器人过程自动化 (RPA)
- 应用基础设施与中间件 - 事件驱动型应用
适用行业
- 教育
- 生命科学
用例
- 自动化制造系统
- 虚拟培训
服务
- 系统集成
- 培训
关于客户
MMC 是一家总部位于新西兰的金融服务公司。他们每月处理数千名投资客户的入职事宜。他们之前的入职流程主要是手动的，涉及手写申请，效率低下并且带来了很大的风险。该公司需要一种解决方案，不仅可以简化入职流程，还可以减少风险和浪费，并提高整体可审核性。该公司与许多外部系统集成来检索数据，这导致了材料的双重处理并引入了风险和培训问题。
挑战
MMC 是一家总部位于新西兰的金融服务公司，其客户入职流程面临着重大挑战。该过程主要是手动的，涉及手写申请，这给他们每月加入的数千名客户造成了主要瓶颈。手动流程使得跟踪问题变得困难，带来了很大的风险，并且从用户的角度导致了材料的双重处理。这是因为需要从外部系统检索数据，由于 MMC 必须集成的系统数量较多，这也带来了风险和培训问题。 MMC 的首席信息官 Craig Richardson 认识到需要进行变革，以简化入职流程、减少风险和浪费并提高整体可审核性。
解决方案
MMC 使用 Nintex K2 Five 实施了全自动入职解决方案。该解决方案结合了自定义用户界面 (UI) 和面向任务的流程来加速客户入门。该流程是使用 K2 Software 构建的，并使用基于 Blue Prism 的机器人自动执行从 Salesforce 提取数据并将其集成到工作流程中的任务。此外，ABBYY 的 Content IQ 解决方案还用于提供文档抓取和分析功能。该解决方案最初被视为概念验证，但很快成为实现可扩展性的基础设施的关键部分。结果立竿见影，团队可以受理的申请数量显着增加，有时甚至提前清理了申请队列。
运营影响
数量效益
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