【独家】七个2017年金融界最关注的数据趋势

36大数据 · 公众号 · 大数据 · 2017-05-28 10:58

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Big data has already heralded some massive changes in the world of finance, but new tech is pushing new trends for the industry. Anyone in the financial sector—and even common consumers—can benefit from recognizing them.

大数据已经预示着金融界某些领域的将发生巨大变化，但新技术正在推动这个行业朝着更新的趋势发展。任何金融界人士(甚至是普通消费者)，都可以从了解这些新技术中受益。

Data Trends for Finance in 2017

Use these trends to direct your investments, your choices as a consumer, and your direction within the finance industry overall:

2017金融界数据趋势

这些数据趋势可以用来指导您的投资、您作为消费者的选择以及您在整个金融行业的方向：

1.Real-time financial data.

Stock prices have been streaming for a while, but real-time capturing and analysis of financial data could start affecting more niches. For example, financial institutions could start making decisions based on micro-changes in prices, and consumers could expect to be evaluated for loans differently based on temporary fluctuations.

1.实时财务数据。

虽然股价是连续的一段时间，但用实时捕获和分析金融数据开始影响更多的商机。例如，金融机构可以根据价格的细微变化来做出决策，消费者贷款时可能会由于短时波动被进行不同的评估。

2. Improved risk analysis.

The improved capabilities of banks to assess risk could be beneficial to consumers and help banks improve profitability at the same time. For example, advanced AI-driven algorithms could calculate the probability of an individual defaulting on a mortgage using more data points than just a credit score or initial down payment. It could help new entrepreneurs get unsecured loans, rather than secured loans, and drive more home ownership and more economic momentum as capital becomes more available.

2.改进的风险分析

银行提高风险评估能力有利于消费者，同时也能提高自身盈利能力。例如，高级AI驱动算法可以使用更多数据点而不仅仅是信用评分或初始首付款来评估个人违约概率。它可以帮助创业者获得无担保的贷款而不是担保贷款，并且能推动更多的房产和经济动力作为资本。

3. Open source models.

With the abundance of data-related tools and strategies available to financial institutions, more companies and organizations are pushing for open source datasets. The advantage here is that more companies and organizations contributing to the common pool will result in greater collective knowledge and insight, which in turn, can help everyone make decisions that better affect the economy, and secure higher profitability. As predictive analytics becomes more popular, the volume offered by open source models is going to become even more important.

3.开源模型。

随着金融机构数据处理工具和策略的丰富，更多的公司和组织正在推动开源数据集。开源的优势在于更多的公司和组织出谋划策将会带来更多的集体知识和洞察力，这反过来又可以帮助每个人更好地做出促进经济发展的决策，并确保更高的盈利。随着预测分析越来越普遍，开源模型的提供将变得越来越重要。

4. Public and/or hybrid cloud investments.

Private cloud models sound safer, but public and hybrid cloud models could be viable investments for the financial sector. Public clouds offer the advantages of lower costs, fewer contracts, shared hardware, and less need for ongoing management. It still has a few kinks to work out, but it could change how banks store, provide, and access data in the future.

4.公共和混合云投资。

私有云模型听起来更安全，但公共和混合云模型可能在金融投资中更加可行。公共云可以降低成本、减少合同数量、共享硬件并且减少持续的需求。尽管它还有一些缺点，但它在未来将会改变银行存储、提供和访问数据的方式。

5. The Internet of Things (IoT).

We’ve been promised a revolution from the IoT for several years now, but analysts are predicting we’re finally ready to see mass integration. Within a few years, there could be up to 25 billion IoT devices in circulation, and you can bet banks will be first in line to take advantage of them. IoT could allow customers to make payments more conveniently, and in more ways. In turn, financial institutions would be able to collect more data on its customers than ever before.

5.物联网（IoT）。

几年前我们就已经承诺了要进行IoT革命，分析师预测，我们终于准备好去见证大规模整合了。在几年内，流通中可能会有高达250亿个物联网设备，并且可以打赌银行必定是第一个利用这些设备的行业。IoT可以让客户更方便地、以更多方式的进行付款。反过来，金融机构就能比以往任何时候更多的收集客户数据。

6. The Blockchain.

Ever since Bitcoin became popular, people have been excited about Blockchain—a system of publicly recording peer-to-peer transactions in a safe, encrypted way that protects users from fraud (while simultaneously keeping them anonymous). Again, the Blockchain isn’t a foolproof system, and it relies on high volumes of participation to work most efficiently, but it’s being developed as one of the biggest leaps forward in financial technology, and could revolutionize how we make and receive payments.

6.区块链

自从区块链流行以来，人们一直它感兴趣--一种公开记录对等交易的系统（以安全、加密、同时保持匿名的方式保护用户免受欺诈）。同样的，区块链不是一个简单的系统，它依赖于大量的技术参与来最有效地工作。但它正在发展成为金融技术领域最大的飞跃之一，并且可能彻底改变我们的付款和付款方式。

7. Talent shortages.

Though not a technological trend, per se, it is a repercussion of these growing technological trends. Our wealth of data requires human data analysts and predictive analytics specialists to make more informed, profitable decisions on behalf of businesses. Demand is rising, but availability isn’t—leading to severe talent shortages in this area.

7.人才短缺。

虽然人才短缺不是一个技术趋势，但这也是不断增长的技术趋势的一个反映。丰富的数据需要人力资源分析师和预测分析专家去代表企业做出更明智，更有利可图的决策。该领域需求正在上升但可用人才并不多，这也导致这一领域严重的人才短缺。

8.Stay Plugged In

Data trends can escalate or shift rapidly based on the introduction of new technology, or the discovery of game-changing factors, such as security flaws. In an industry as sensitive and as exposed to public scrutiny as the financial sector, this is even truer. Stay tuned to your favorite tech and financial blogs in the coming year, and be prepared for some surprising changes as we learn more about these trends.

8.保持持续关注

数据趋势可能会因新技术的引入或新的游戏转变因素的发现（比如安全漏洞）而迅速升级或转移。像金融部门这样一个敏感的行业并受到公众监督的行业，这些变化甚至更快。在未来，请持续关注您最喜欢的科技和金融博客，并准备好见证这些趋势的巨大变化。

本文为36大数据独家授权编译，未经允许不得转载

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