A discussion with Nadia Abouayoub, founder of AIFINAI and digital member of the World Economic Forum

与讨论 纳迪亚Abouayoub ，创始人 AIFINAI 和数字成员 的世界经济论坛

Artificial Intelligence (AI)is set to impact a multitude of sectors and industries. The finance sector has proven itself an early adopter of AI in comparison to other industries. Therefore, the applications of AI and machine learning in finance are myriad. Traders, wealth managers, insurers, and bankers are likely well aware of this in some form.

一个 rtificial智能(AI)设置为影响行业和产业的众多。 与其他行业相比，金融业已证明自己是人工智能的早期采用者。 因此，人工智能和机器学习在金融中的应用繁多。 交易员，财富管理公司，保险公司和银行家很可能以某种形式意识到这一点。

Since the very basis of AI is learning from data, it is a natural fit for the financial sector where records are imperative to the business. It has also established automation in the areas which require intelligent, analytical and clear-thinking. Applications like financial services chatbots have indeed proven themselves to be a powerful tool to customer satisfaction, and an unmatched resource for the enterprises, helping them save a lot of time and money.

由于AI的基础是从数据中学习，因此它自然适用于对业务至关重要的金融部门。 它还在需要智能，分析和思路清晰的领域建立了自动化。 金融服务聊天机器人等应用程序确实已证明自己是提高客户满意度的强大工具，并且是企业无法匹敌的资源，可帮助他们节省大量时间和金钱。

According to a study done by the World Economic Forum, AI is changing how financial institutions generate and use insights from data. In turn, this propels new forms of business model innovation, reshapes competitive environments and the workforce, engenders new risk dynamics, and poses novel challenges to firms and policy-makers alike.

根据世界经济论坛所做的一项研究 ，人工智能正在改变金融机构生成和使用数据见解的方式。 反过来，这推动了新形式的商业模式创新，重塑了竞争环境和劳动力，带来了新的风险动态，并给公司和决策者带来了新的挑战。

Our digital member, Nadia Abouayoub is a leading expert in the AI and finance space, and is currently developing an educational platform to elaborate on how AI can be integrated into the financial sector. I talked to her about how the field is evolving, as well as some misconceptions and limitations we need to keep in mind.

我们的数字会员Nadia Abouayoub是AI和金融领域的领先专家，目前正在开发一个教育平台，以详细说明如何将AI集成到金融领域。 我和她谈了这个领域的发展情况，以及我们需要记住的一些误解和限制。

1.人工智能将成为金融未来的关键部分。 (1. AI will be a pivotal part of the future of finance.)

In the Fourth Industrial Revolution, AI is one of the key technologies which will disrupt and shape our industries and society. Our society is facing unprecedented challenges which affect our economy, environment, and our welfare. To resolve these issues, we need to process and analyse the data related to them. Turning towards new technologies to understand the data, identify patterns, and predict potential outcomes can equip us to face difficult challenges.

在第四次工业革命中，人工智能是将破坏并塑造我们的行业和社会的关键技术之一。 我们的社会面临着前所未有的挑战，这些挑战影响着我们的经济，环境和福利。 为了解决这些问题，我们需要处理和分析与它们相关的数据。 转向使用新技术来理解数据，识别模式并预测潜在结果可以使我们面对困难的挑战。

The financial and monetary ecosystem, like other industries, is adopting new technologies. The regulatory bodies have recognized the impact of such disruption and have published their recommendations for financial institutions, specifically regarding how AI and other new technologies will affect the governance in our industry. We see many initiatives in established banks about the usage of AI to help them analyse and understand the markets, make decisions, and extract information from a constantly increasing volume of data. Another phenomenon is the increasing numbers of startups in financial services where AI is part of their business models.

与其他行业一样，金融和货币生态系统也在采用新技术。 监管机构已经意识到这种破坏的影响，并已针对金融机构发布了他们的建议，特别是关于AI和其他新技术将如何影响我们行业治理的建议。 在成熟的银行中，我们看到了许多有关使用AI的举措，以帮助他们分析和了解市场，做出决策并从不断增长的数据量中提取信息。 另一个现象是金融服务初创企业的数量不断增加，而人工智能是其商业模式的一部分。

2.我们需要为将要造成的破坏做好准备。 (2. We need to be prepared for the disruption this will cause.)

From a macro-level, the first advancement to focus on is the disruption in companies and integrating new digital technologies. As mentioned previously, companies must adapt, and many of them are going through a digital transformation. The success of the transformation will depend on how companies are incorporating AI and new technologies within their business strategy and business model.

从宏观层面来看，首先要关注的进步是公司的颠覆和整合新的数字技术。 如前所述，公司必须适应，许多公司正在经历数字化转型。 转型的成功将取决于公司如何将AI和新技术纳入其业务战略和业务模型。

Companies have a different level of technical maturity, and each adaptation should be in line with the company business model. Apart from the adaptation, we need to look at preparing the workforce for current and upcoming developments.

公司具有不同的技术成熟度，每次调整都应符合公司的业务模式。 除了适应之外，我们还需要考虑为当前和即将到来的发展做好准备。

On a micro-level, Natural Language Processing and algorithmic computation will be key in data management. The validity and accuracy of data can not be overlooked, and valid processes need to be put in place to ensure efficiency in the procurement and maintenance of data sets, while optimizing the quality of data. Additionally, the impact of new scenarios on an algorithm, causality of an event and its efforts on predictive models will have a huge impact on the financial sector.

在微观层面上，自然语言处理和算法计算将是数据管理的关键。 数据的有效性和准确性不容忽视，需要采取有效的流程来确保数据集的采购和维护效率，同时优化数据质量。 此外，新方案对算法的影响，事件的因果关系及其对预测模型的努力将对金融部门产生巨大影响。

3.技术和伦理方面的局限性将决定该领域的发展速度。 (3. Limitation, both technical and ethical, will dictate how fast the field evolves.)

Most misconceptions around AI stem from a lack of education and awareness. By understanding AI and its limitations, organizations will be able to design a more realistic implementation plan and ensure the success of their projects. Unfortunately, at the moment, many statistics show that AI projects have a high rate of failure. These not only have a significant financial impact on companies, but also have a negative impact on future potential implementations.

关于AI的大多数误解都源于缺乏教育和意识。 通过了解AI及其局限性，组织将能够设计出更切合实际的实施计划并确保其项目成功。 不幸的是，目前，许多统计数据表明，人工智能项目的失败率很高。 这些不仅对公司产生重大的财务影响，而且对未来的潜在实施也具有负面影响。

Additionally, incorporating AI models relies on a high volume of data. To ensure accuracy of the results, the models must address the limitation on volume, velocity, and variety. Data Limitation is a key concern. Missing data, poor data quality, and lack of data will limit machine learning development standard, as specified by the Bank of England.

此外，合并AI模型还依赖大量数据。 为了确保结果的准确性，模型必须解决体积，速度和种类上的限制。 数据限制是关键问题。 数据丢失，数据质量差和数据不足将限制机器学习开发标准，这是英格兰银行规定的。

Alongside the technical limitation, there are other potential issues that need to be considered. There are a variety of principles that have been established, to aid in the usage of AI. Companies could either create their own set of rules or reference some pre-defined rules by organizations such as the OECD, the EU, or other bodies. Within the internal governance, it is crucial to ensure that AI projects are ethically implemented.

除技术限制外，还需要考虑其他潜在问题。 已经建立了各种原则来帮助使用AI。 公司可以创建自己的规则集，也可以参考OECD，欧盟或其他机构等组织的一些预定义规则。 在内部治理中，至关重要的是确保以合理的方式实施AI项目。

4.模型的信誉必不可少。 (4. Credibility of models is imperative.)

One issue of importance in relation to AI and finance is the robustness of AI models. This needs to apply to the the nature of the algorithms used, as well as the deep understanding of the data. It is also important to ensure a safe and explainable implementation, especially in relation to the financial sector, in order to ensure transparency.

与AI和金融相关的重要问题之一是AI模型的鲁棒性。 这需要适用于所用算法的性质以及对数据的深刻理解。 确保安全，可解释的实施(尤其是在金融部门方面)也很重要，以确保透明度。

The lack of robustness on AI models limits the adaptability and scalability of the algorithms, being a parameter of project failures. To implement robust solutions, we should focus on successfully implementing resilient, scalable, and adaptable models. All these parameters combined will help us improve the credibility of models and develop trustworthy AI.

AI模型缺乏鲁棒性限制了算法的适应性和可扩展性，这是项目失败的一个参数。 为了实施健壮的解决方案，我们应集中精力成功地实施具有弹性，可扩展性和适应性强的模型。 所有这些参数的组合将帮助我们提高模型的可信度并开发可信赖的AI。

5.信息将提供竞争优势。 (5. Information will provide a competitive edge.)

In an era of information and data in which the volume of data is exponentially increasing, knowledge and insights are crucial for all industries. In financial services, information can help build an understanding of all the parameters influencing the industry, alongside with the capacity to manage, understand and process the data.

在信息和数据时代，数据量呈指数级增长，知识和见解对所有行业都至关重要。 在金融服务中，信息可以帮助您理解影响行业的所有参数，以及管理，理解和处理数据的能力。

To stay competitive and manage their risks efficiently, companies are looking at technologies which will help them build a deep understanding of the data by identifying patterns.

为了保持竞争力并有效管理风险，公司正在寻找可通过识别模式来帮助他们深入了解数据的技术。

AI models are being used to help data tell its story. Based on the information and AI solutions, the aim is to ensure that the decision process is fair and accurate. Extracting data from the information is not sufficient; we also need to ensure that we can guarantee the accuracy of the data, as well as transparency of models.

人工智能模型正在被用来帮助数据讲故事。 基于信息和人工智能解决方案，目的是确保决策过程公正，准确。 从信息中提取数据是不够的； 我们还需要确保我们能够保证数据的准确性以及模型的透明度。

战略情报等工具将是获得竞争优势的关键。 (Tools like Strategic Intelligence will be the key to gaining a competitive advantage.)

The Strategic platform helps reduce the time to insight by gathering key influencing parameters across industries and social phenomenon. Through bringing together the different elements into a transformation map, it helps us understand the relations between the parameters and their impact on our industry. For example, we can see how changes in governance, specific disruption in an industry, could affect the market.

战略平台通过收集跨行业和社会现象的关键影响参数来帮助缩短洞察时间。 通过将不同元素整合到一个转换图中，它可以帮助我们了解参数之间的关系及其对我们行业的影响。 例如，我们可以看到治理的变化，一个行业的特定破坏如何影响市场。

Another feature that Nadia found beneficial is the possibility to visualize the interaction between industries through transformation map. It allows us to analyse the risk and challenges which could disrupt an industry. Through the transformation map, the gathering of the information can facilitate decision-making.

纳迪亚发现另一个有益的功能是可以通过转型图可视化行业之间的互动。 它使我们能够分析可能破坏整个行业的风险和挑战。 通过转换图，信息的收集可以促进决策。

Strategic Intelligence is an online digital platform that helps individuals and organizations decipher the potential impacts of accelerating global complexity, while counteracting the misleading and unreliable information that is circulating. The Strategic Intelligence tool helps you understand the global forces at play and make more informed decisions.

战略情报是一个在线数字平台，可帮助个人和组织破译加速全球复杂性的潜在影响，同时消除正在传播的误导性和不可靠信息。 战略情报工具可帮助您了解正在发挥作用的全球力量并做出更明智的决策。

To explore Strategic Intelligence, visit intelligence.weforum.org or search Strategic IQ in the iOS, Play or Huawei stores.

要探索战略智商，请访问Intelligence.weforum.org或在iOS，Play或华为商店中搜索战略智商 。

Join the World Economic Forum’s Digital Membership community to monitor these issues and more here.

加入世界经济论坛的数字会员社区，以监视这些问题，并 在此处 更多 。

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