AI风控模型

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长护险基金如何避免变成第二个“医保黑洞”?
Sou Hu Cai Jing· 2025-07-15 06:03
Core Insights - The article discusses the transformation of long-term care insurance (LTCI) management from traditional manual auditing to advanced algorithmic calculations, highlighting the use of AI and real-time data analysis to prevent fraud and improve service delivery [1][4]. Group 1: Fraud Prevention and Management - The new LTCI management system utilizes AI to detect anomalies, such as a "severely disabled" elderly person who is physically active, triggering alerts for potential fraud [1][4]. - The system has shifted from traditional sampling audits to real-time data processing, allowing for immediate identification of irregularities in care service claims [4]. - After implementing the system, a province saw the growth rate of fund expenditures drop from an annual average of 19% to 6%, while the satisfaction rate among genuinely disabled elderly individuals rose to 92% [4]. Group 2: Dynamic Fund Management - The system generates quarterly "fund stress test reports" based on 72 factors, including aging rates and healthcare costs, allowing for proactive adjustments in budget allocations [4]. - The introduction of a "dynamic rate adjustment valve" helps to balance funding across regions, ensuring that areas with increasing needs receive appropriate financial support [4]. Group 3: Transparency and Community Involvement - The "social co-governance" module allows family members to track expenditures through a mobile app, providing transparency with video evidence of care activities and electronic invoices [4]. - This level of transparency empowers families to monitor care services closely, reducing opportunities for fraudulent claims [4]. Group 4: Ethical Considerations in Care - The system includes a "terminal care fund pool" that allocates resources for pain management and psychological support for families when an elderly person is predicted to enter the end-of-life stage [5]. - The focus is not only on preventing fraud but also on ensuring dignity in care, emphasizing the ethical responsibility of the fund management [5].
被“误伤”后,他们期待:AI能否让反诈更精准?
3 6 Ke· 2025-07-15 00:34
数字化浪潮下,电信网络诈骗也如影随形,成了啃噬老百姓"钱袋子"的"隐形毒瘤"。全民参与反诈既不能停歇,也不能懈怠。 一组数据显示,2023年,国家反诈中心累计向各地下发资金预警指令940万条,公安机关累计见面劝阻1389万人次,会同相关部门拦截诈骗电话27.5亿 次、短信22.8亿条,处置涉诈域名网址836.4万个,紧急拦截涉案资金3288亿元。 然而,在反诈系统风控的过程中,偶尔也会"误伤"部分普通用户。 从买卡到突然被封,仅仅不到十天,"这次解封了,下次会不会又突然被封?"讲起手机卡被封的经历,用户大白颇为困惑。 事实上,类似的案例还较为普遍。那么,手机卡突然被封,是卡本身就有问题,还是被"误伤"?对于"误伤"的用户,是否有更快速的解决路径?《IT时 报》记者从数位行业资深人士处试图找寻答案。 用户吐槽,8天新卡被"封停" 从大白办新卡到被封号,仅过了一周。 今年5月下旬,大白在某运营商南京西路营业厅办理了一张副卡,但实际使用的次数屈指可数。6月初,大白突然收到一则短信,称其"近期号码通信异 常,存在被不法分子盗用的可能,根据《中华人民共和国反电信网络诈骗法》相关规定以及用户服务协议相关条款,限制了号码的 ...