奥利弗Baudoux
Mitchell, An Enlyte Company全球产品战略和人工智能高级副总裁
声称自动化. 无触觉的估计. 直通处理(STP). 对于希望提高效率的汽车亚博真人官方版APP来说，这些话题是他们最关心的, reduce settlement time and enhance customer satisfaction by leveraging artificial intelligence (AI) in the claims process. 然而，尽管他们的兴趣只有10% 受访者 97%的人承认非接触式技术的价值，他们是否大量使用非接触式技术.
那么为什么会有这种差异呢?? Although the pandemic has accelerated advancements in virtual claims handling and opened the door to STP, 要兑现“无触碰”的承诺，还有很多工作要做. 作为一个行业, we are just beginning to reconcile initial expectations with the current state of the technology. 所以说到STP，还有什么更好的时机来区分事实和虚构呢?
摆动的情绪
就在几年前, 人工智能在技术趋势列表中名列前茅, 对汽车保险行业自动化索赔流程的能力寄予厚望. 那时， LexisNexis风险亚博真人官方版APP 报告称，79%的汽车亚博真人官方版APP对, 或考虑, 非接触式索赔的概念.
人工智能支持的自动化正在成为现实. Machines could recognize the extent of the damage and whether a part should be repaired or replaced. 虚拟估计——考虑到 第一级自动化-产生效率和一致性收益. 从图片上看，评估师完成了多达 每天15次估计 而只有三到四个人在战场上.
然后情绪发生了变化. 完全自动化并不像业界曾经认为的那样接近完成. 事实上，是2020年 《亚博真人官方版APP》文章 表示，大多数开始进行人工智能主导转型的公司都感到失望. 虽然自动化的设计是为了使理赔更容易, 它显然无法取代人类评估师.
此外，缺乏建立准确估算的基本要素. 例如, if you cannot decode a 车辆 identification number (VIN) and uniquely identify the model’s options, 你怎样才能准确地预测哪些部件需要修理或更换? 你要在保险杠上装传感器吗? 头灯呢?? And if the part is made of a special material like aluminum, how should the repair plan differ? 很明显，尽管人工智能可以识别最重要的汽车部件, 它需要学习数百甚至数千种.
人的因素
Another obstacle in using AI to do the work of human appraisers was the realization that humans do not process one image at a time or make decisions in isolation. 而不是, they contextually review all available photos to understand the situation and the impacts on the 车辆 before reaching a conclusion. AI, on the other hand, was not able to analyze multiple photos to determine unrelated prior damage. 更大的挑战, human appraisers who had always completed estimates on their own were now asked to review and approve a pre-written estimate generated by AI—something they were not ready to embrace.
结果是:主张自动化的情绪从希望变成了绝望. 许多组织缩减了规模。, 将STP投资从运营目标转移到研究和开发项目. 他们对非接触式估算失去了信心, 而不是, began to focus on more straightforward and realistic use cases for AI—such as triaging a claim or simply reviewing an already-written estimate (including for subrogation). 出版物等 《亚博真人官方版APP》 还指出，尽管87%的数据科学项目进入了生产阶段, “不到25%的全球组织制定了企业范围的人工智能战略”.
宣传和. 商业可行性
虽然这可能令人担忧，但转变情绪是新技术的典型特征. 为了解释这一点，Gartner将技术生命周期定义为五个阶段. 被称为 Gartner炒作周期, 阶段从膨胀的期望开始(阶段1), 基于技术早期成功的高峰(阶段2), and experience waning interest as well as disillusionment when implementations fail (Phase 3). 也就是说, 随着这项技术得到更广泛的理解，其好处得到明确界定(第4阶段), 主流采用(阶段5).
今天的现实
Although sentiment and hype surrounding claims automation have changed dramatically in just a few years, 这项技术从未停止过进步. 此外，以前的缺点也得到了解决. 例如，先进的人工智能亚博真人官方版APP，如 米切尔智能损伤分析 can predict more than 300 internal and external parts as well as provide recommendations for operations including repair and replace, 拆卸和安装, 抛光和混合.
此外, 完成了识别码的解码和正确零件的选择, 在很大程度上, by 将人工智能与车辆信息相结合. 用于非接触式评估，以产生准确的评估, 车辆, 维修和历史索赔数据至关重要.
Going beyond OEM parts and incorporating recycled or aftermarket parts has also become a reality. 这使组织可以选择部分提供者. Finally, AI can now correctly identify the primary point of impact as well as unrelated prior damage.
启蒙的斜坡
那么，今天汽车保险行业在理赔自动化方面的立场是什么呢? Recent studies and customer feedback seem to indicate that we have successfully passed the third phase of the Gartner炒作周期 and are now entering Phase 4, 或者说启蒙的斜率. The key to this phase is realizing what is possible and how to put technology to use in situations that bring the most value. 评估的创建代表了支持ai的自动化的一个用例. 分诊和自动全损索赔也非常值得人工智能应用. By 2025, LexisNexis风险亚博真人官方版APP 预测远程信息处理数据和人工智能将导致60%的索赔通过自动化分类. STP仍然是愿景. 然而, 预计到2025年，只有一半的非伤害索赔将完全自动化, 现在这被认为是一个长期目标.
自动化的两条路径
考虑到这一点，我们应该如何考虑评估自动化? 我们应该跟踪哪些指标? 除了, 因为自动化是一种在不影响质量的情况下提高效率的方法, STP和自动化评估之间是否存在平行的路径?
直通式处理
STP involves pre-populating as much of the estimate as possible and auto writing the lines with a high degree of confidence. 包括所有的操作, parts selections and pricing generated by AI using 车辆 and claims data—with a focus on low-severity incidents. 一旦这些数据被捕获并分析了损坏的照片或视频, machine-learning algorithms translate the results into component-level estimate lines for appraiser review and approval.
衡量STP技术在过去几年中取得的进步, 首先必须就跟踪什么指标达成一致, 比如有多少人:
- 预测的估计线是正确的，基于什么被认为是真实的
- 零件已成功映射
- 估算行添加不正确，需要修改
- 估计线缺失或不正确，需要人工干预
Answering these questions will lead to a single, measurable indicator known as the North Star metric. For Mitchell, that metric is the efficiency gains delivered by automating the estimating process. 鉴于其总体目标, STP is ultimately a function of the percentage of estimate lines that correctly auto-populate—producing critical time savings and, 反过来, 更高的客户满意度.
而Mitchell的开放平台与 行业领先的人工智能, our own AI—MIDA—has demonstrated substantial gains over the last year with a 16% increase in the percentage of estimate lines correctly auto-populated. 继续微调MIDA的算法也是一个结果
在逐年的改进中:
- 26%正确识别的部件
- 12%正确识别的损坏部件
- 修理和更换人工操作占8%
These improvements demonstrate just how rapidly the technology is advancing and how much progress has occurred in a short period of time.
高效的人工估算
虽然STP是一个基本的目标，当然也是一个长期的愿景, it is just as important to realize that manual appraisals and human judgment remain key to the estimating process. 对于与最新车辆有关的严重事故或索赔, 评估师的参与仍然会产生切实的商业利益, 比如防止成本泄漏. 因此, optimizing the core estimating solution to enhance the user’s experience continues to be a priority. 这可能包括在正确的时间出现正确的照片, 当所选部分有歧义时请鉴定人, 甚至提示一个“真实”的人来确认机器可能不确定的事情.
前面的路
声称自动化 has demonstrated that it can deliver significant benefits to both auto insurers and collision repairers. 其中包括:提高评估师的生产力, 更高的估计一致性, 提高保单持有人满意度，加快结算速度.
随着技术的进步和行业利益相关者寻找利用其真正价值的方法, 重要的是要记住:
- STP是许多汽车保险索赔的一个长期但可实现的目标
- 人的判断对于确保适当的质量和决策仍然是必不可少的
- 定义和监视关键指标对于度量自动化进度至关重要
- 估计器的效率增益和人工智能的准确性应该在跟踪的指标中
- 推进人工智能技术将需要人机协作
- 评估写作不是一门精确的科学，即使有人类评估师
当涉及到技术提供商时，组织有很多选择, partnering with those that offer an open platform and integration with best-in-class AI will help future-proof any claims automation project—allowing businesses to easily scale when, 如果, 他们需要.