Data management issues have always presented challenges for the financial services industry. 在这里, 存探讨原因, 有了正确的技术, 纪律和结构到位, 现在我们有理由感到乐观.
相关:推动金融市场未来的四大大数据管理趋势
所有资本市场公司都面临着一个共同的挑战, 无论大小, 位置, their level of complexity or the collective experience of their IT teams: data management. 当涉及到数据管理时，不存在设置和遗忘或一劳永逸的主张. 这是一个连续体，公司沿着这个连续体向更高的质量水平发展, 透明度和标准化, 没有终点线. The challenge facing firms is further exacerbated by an industry riddled with legacy and proprietary platforms, 还有一系列的数据标准, 因为他们的存在, 这意味着整个行业几乎没有所有公司都认同的标准.
这就是存托信托的背景 & 结算公司(存)最近发布的白皮书， 数据策略 & 金融市场管理, 哪一个 outlines the challenges facing capital markets firms and proposes feasible strategies to address those problems. 本文主要关注当今行业普遍存在的四个关键挑战:
- 标准重叠影响企业数据交换活动的效率.
- Data fragmentation issues and limited business context of data impacting firms’ abilities to fully realize the latent value within their data.
- 复杂和遗留的IT基础设施导致不合格的数据管理实践.
- 整体数据质量差，影响公司的下游系统和流程.
动力
Kapil邦萨尔, 董事总经理, 业务架构主管, 存的数据策略和分析, 解释说,, 在2007-08年开始的全球金融危机之后, regulatory bodies introduced a set of regulations that either directly or indirectly required capital markets firms to focus on their data strategies as an organizational priority.
“That created the impetus for firms to start focusing more closely on their data,他说. “无论是交易后的过程, 流动性和风险管理, 或者监管报告, 它们都有潜在的数据可用性, 准确性和报告是关键的推动因素. 金融危机已经过去15年了, we still have regulations like the Central Securities Depositories Regulation and the UK’s Securities Financing Transactions Regulation, 哪些会对数据质量和管理产生巨大影响.”
遗留问题占上风
随着公司寻求通过新vnsr威尼斯城官网登入创造增量收入, or look to serve their clients better with increased transparency and business insights while simultaneously reducing their operational risk, 数据成为这些要求的核心. 然而, 从不同的系统(尤其是遗留系统)中获取数据, 哪一个 are still prevalent across the industry—is a challenge for even the most tech-savvy firms. 班萨尔解释说:“从遗留系统中获取数据确实存在摩擦成本. “Often the way the data is managed prevents organizations from leveraging that data to drive new business insights.”
不用说，资本市场的格局是复杂的. 它的基础是一个全对全的模型, 允许公司之间进行交易和交换信息. 有许多服务提供商, 每个人都有自己的专业领域, 买方公司有多个托管人, and there are large numbers of broker-dealers and clearing houses through 哪一个 firms clear trades across a variety of asset classes. This means data needs to flow between all the entities across the global markets involved in any form of market activity, 理想情况下，摩擦最小. “需要进行大量的数据交换, 虽然已经有了向通用数据标准的转变, 这些标准仍然是支离破碎的, 这在数据交换的有效性方面造成了障碍,班萨尔解释道. “也存在重叠或重复的标准, 哪一个 means firms spend quite a bit of money trying to exchange data with each other and then bringing that data into their own organizations and converting it into their preferred business context and format.”
然后是数据质量, 哪一个, 据班萨尔说, 需要成为公司在任何数据战略计划开始时的优先事项. “即便如此，这也不是一劳永逸的命题，”他解释道. “You have to invest in maintaining high data-quality standards across the value chain because, 如果数据不准确，没有正确维护, 那么它就不能驱动它想要实现的功能.”
数据作为资产
资本市场公司通常拥有大量数据, 哪一个 is invariably distributed across disparate systems and locked away within legacy platforms, 在整个企业中访问和共享它是一个挑战. 客户端s are increasingly looking for quality data in real time and in the format they can consume with least friction. Bansal suggests that approaches to data need to change—it must be considered an asset or product in its own right, 有自己的价值链, 他说，这是为了让公司从中获得真正的价值.
“Data is created, then it is transformed by, for example, adding additional insight to it. 然后进行分发、报道和维护。. “So, 这是一条价值链, 从数据中提取价值, 作为一个组织，你必须考虑你将要做的决定, the infrastructure you’re going to establish and the policies you are going to implement across the entire value chain. 如果你不关注价值链的任何部分, 作为一个组织，您将无法在数据中实现价值. 但首先, you have to establish a North Star of your data strategy at an enterprise level and strategically prioritize aspects of that North Star in alignment with business priorities.”
前进的道路
The infrastructure to 哪一个 Bansal refers is determined by the decisions individual firms take with respect to how they want to organize their data—for example, the extent to 哪一个 they choose to centralize their data and the type of data they centralize—哪一个 is as much a strategic and data governance issue as it is about pure infrastructure and enabling technology.
“Should firms set up their entire infrastructure/technology landscape so that it’s centralized or decentralized? 公司已经尝试了不同的方法. 当涉及到数据能力时，企业战略和最终状态是有意义的. 但是还有一些特定于业务的需求, 哪些需要通过足够灵活的去中心化功能来解决. 所以，答案介于两者之间.
“Firms should think about data strategy and data capabilities at the enterprise level to drive harmonization and efficiency in infrastructure costs. 在这种程度上，数据策略的集中视图是有意义的. 话虽如此, data should be made available to businesses in a flexible manner so respective business insights can be drawn on in a decentralized manner.”
api和云
Bansal 解释说, the answer to the question about the technologies firms can use to manage their data better from inception to final consumption and analysis should be prefaced by a clear understanding of the type of operating model they are looking to establish—centralized, 区域性的还是地方性的. 这个问题也应该得到回答, 他说, 在数据价值链的背景下, the first step of 哪一个 entails cataloging data with the business definitions at inception to ensure it is centrally located and discoverable to anyone across the business. Firms also need to use the right data standards to ensure standardization across the firm and their business units. 然后, vns6060威尼斯城官网分布, they need to establish a clear understanding of how they will send that data to the various market participants they interact with, 以及内部消费者甚至监管机构. 这就是应用程序编程接口(api)的用武之地, 但它并不是放之四海而皆准的,他说. “人们普遍认为api是传输数据最可行的方式, 但是没有通用数据标准的api是行不通的.”
班萨尔认为云基础设施在存储方面发挥着关键作用, 对数据进行编目和分发, 哪一个 他说 has the ability to allow firms to decouple themselves from their legacy platforms. 然而, 他警告说, 除非他们在数据质量和编目方面预先投资, 他们将无法充分发挥其数据的潜力, 不管它是否在云端. “有很多可用的技术致力于提高数据质量, 数据编目, 数据维护和数据报告, 然后是由api支持的云基础设施,他说.
“云计算的优势在于, when you have invested in your data and it’s been subject to the right quality checks and cataloging, 具有完全不同用例的多个用户可以从中获得价值, 非常迅速地.”
本文最初发表于 水技术 2023年4月24日.