As a necessary matter of compliance, 银行通常会对客户进行风险评分，以确保他们符合预先设定的风险偏好. 无论是在入职期间还是通过监控客户和交易, every entity is screened by the major financial crime divisions, usually broken down into: Know Your Customer (KYC), Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF), Sanctions, Fraud, and Transaction and Customer Monitoring.
However, most of these entity reviews operate in business silos, with each assessment generally taking place across different systems, executed by disparate policies and processes, 由于缺乏集中的客户数据，无法提供客户的整体视图.
By being assessed separately, 同一实体的不同风险评分或版本可能存在，并给银行带来并发症. For example, 拥有商业贷款的客户可能被认定为政治暴露者(PEP)，但他们的商业账户将其列为低风险客户.
这可能导致客户碎片化、数据重复或单个实体的多个记录. As a result, 许多银行的金融犯罪部门缺乏效率，没有利用技术潜力来创建一个企业范围的系统, single customer view.
Entity Resolution / Single Customer View
Entity resolution (ER) is the white knight of financial crime risk management. ER可以解开复杂的客户数据的数字网络，创建一个整体, 实时查看他们的客户和与他们互动的网络. 将来自不同内部系统的数据拼接在一起，并辅以外部数据，将使银行打击金融犯罪的能力现代化. 人工智能可以进一步用于改进对客户风险的分析, 能够更好地解释隐藏在数据中的某些行为或关系.
ER还通过组合脱节的数据系统带来了增强分析能力的希望. 统一的客户档案将意味着更好的监控能力, more robust customer due diligence, automated reporting, streamlined processes, increased traceability and better data lineage. Perhaps most significantly, the ability to perform enterprise-wide case management 在开展金融犯罪调查方面是否会有一个巨大的飞跃. 其好处不仅限于操作层面，而且使用数据创建单一客户视图可以帮助提高银行在安全性方面的声誉, improve customer retention and, crucially, transform a bank’s ability to fight financial crime.
Implementing the Technology
Banks often have the right intentions, driven by motivated people, but, as soon as the costs and complexities start adding up, they can choose an easier path. Implementation of entity resolution will require heavy investment in technology and security; uplifting of policy, procedures and governance; and most likely a structural re-organization to integrate all financial crime risk management portfolios under a synthesized framework. Yes, this is a lot to chew, 但红利是可观的，这将是一家银行未来为客户和机构提供安全保障的最佳选择. To borrow shamelessly from Nelson Mandela, it always seems impossible until it is done.
幸运的是，在许多情况下，完成单个客户视图所需的数据已经存在. The challenge, however, 关键在于连接海量和快速的数据，并将其转换成一种可以跨不同系统读取的格式. There are 银行可以采取三个主要的数据举措来实现实体解决:
- Removing duplicates of repeated data
- 查找在不同系统中引用相同客户或实体的记录并将它们链接起来
- 标准化以前以多种形式表示的数据的形式, also known as “canonicalization”
Other global players are already further ahead than the UK in this regard. 美国的社会保障制度为每个公民提供一个唯一的身份证号，记录个人的收入或工资, 金融机构可以使用哪些工具来检查其信用评分或其他有关实体的要求信息. Across Europe, 挪威的BankID和冰岛的Kennitala系统为公民提供了一个单一的数字标识符，使每个人都可以访问每家银行和公共机构, 并与相关管理部门建立了客户记录的集中存储库. In China the large technology and financial services players, such as Ant Financial, 是否在他们的指尖上整合大量的客户数据，以创建一个可视化的网络视图，显示客户的所有互动——包括财务和社交.
UK institutions still have a lot of room to grow. According to a poll of 90 FIs by NICE Actimize, a leading provider of unified customer views, 资产在600亿美元以上的银行中，超过50%的银行拥有10个以上的检测系统, and a further 31% have over 20.
有更有效的方法来执行必要的反金融犯罪检查. 为网络中与一个实体相关的所有数据分配一个数字或唯一标识符是一个很好的起点. Moreover, 值得注意的是，世界银行主张，通过民事登记系统拥有一个唯一识别号码(UIN)对于实现这一目标至关重要 UN Sustainable Development Goals (Target 16.9).
The Multiple Uses of a Single Customer View
除了金融犯罪，实体解析的用例也非常多. From optimized marketing, to resource management, to specialized services, 了解客户的背景只会有助于改进您的个性化业务产品. 通过更好地了解个性化的客户需求，预测分析可以更有针对性.
通过单一客户视图进行整体客户风险评级可能还不是标准, but as the culture of compliance develops and deepens in banks, this is undoubtedly a necessary goal.
