5 Finance Jobs Already Being Replaced by Robots

Finance has always been a lucrative industry to work in. From the time of the first banks and insurance companies, it always paid off to manage other people’s money. Offering an annual average wage of $ 100,000, finance allowed millions to study a respected profession and find an attractive job, depositing cash, transferring money, authorizing a loan, underwriting insurance, investing in securities, equity or commodities or just managing all of the above.

But with the age of big data and AI a significant portion of these jobs can become obsolete, or at least transformed. As predictive analytics, computing power and granular personalized data are converging robots can achieve more and more tasks, challenging their human counterparts. After all, finance is all about taking hundreds or thousands of factors into account and then predicting the chance a customer will pay a loan back or the return a stock will create in exchange for investment – and what can be a better task for a robot than that?

That is why Opimas, a consulting firm, predicts that 230,000 jobs in the finance sector could disappear by 2025, and Oxford academics claim that 54% of total lost jobs will be in American finance industry.

Market Research Analyst

Market and company researchers and analysts can be found in most of the consulting branches in banks, or in firms such as Mackenzie, Gartner and Forrester. Their work is rather manual, going over detailed research papers, interviewing key executives, and writing dozens of pages per report. However, their service is considered to be expensive, ranging from tens of thousands of dollars for a simple task to an average of a few million for an annual subscription.

Company analysis may be the last kind of job you’d imagine would be automated. Yet, it can be done by harnessing NLP and AI algorithms that crawl over dozens of structured or unstructured data sources. Digital analysis startup Zirra had built an automatic process that delivers insightful outputs on private companies, including a list of possible competitors, level of competition, web traffic, a map of meaningful events during a company’s life, and an automated list of risk and success criteria. Its proprietary technology allows it to create high-level analysis insights within seconds.

Zirra collects and aggregates data from a myriad of public and private information sources, including structured directories, semi-structured databases, and completely unstructured text. It then utilizes Natural Language Processing (NLP) techniques to process large volumes of unstructured text, to detect companies and their semantic context, to model their interrelationships, and to derive dynamic indicators.

Zirra recently released a first of a kind AI-powered analysis bot called Emmet. By using simple English, Emmet answers company analysis with outputs within seconds. Take for examples this output when asked about the risk and success criteria for ride-hailing app Lyft:

**Try Emmet here and invest in Zirra via SeedInvest to make private companies accessible**

Stock, Commodity, and Equity Analysts

Since robots are great at aggregating large amounts of information from various data sources, as well as at employing predictive analytics techniques from an even simpler data set, it is only natural that they can compete with a flesh-and-blood stock and equity analyst. What highly paid analysts to take hours to prepare, robots can do within minutes, even when talking about sophisticated predictions.

Serving hedge fund and bank traders, Kensho looks at real-world events and analyzes their effect on financial markets, and particularly on asset prices. For instance, Kensho can answer questions such as “what will happen to cement stocks when a Category 3 hurricane hits Florida?” Or “what happens to the currencies of oil-producing countries when oil trades below $45?” Following the iPhone 8 and iPhone X launch earlier this month, a Kensho study for CNBC found a pattern behind Apple’s shares after each iPhone announcement: the stock is flat on the day of the event, and then up 1.2% one week after the announcement, and up 2.6% three months later.

Kensho’s systems crawl through 90,000 financial and governmental reports and sources, searching for correlations between geopolitical and natural world event and financial assets. Backed by Goldman Sachs, JPMorgan Chase, Bank of America, Merrill Lynch, Morgan Stanley, Citigroup and Wells Fargo, the company serves trading desks at S&P and some of its investors.

Insurance Underwriters

The insurance industry is also facing a challenge from robots that are evaluating risks and compute actuarities. Insurance brokers are now being replaced by AI-based apps that sell insurance using chatbots. Startups such as Lemonade in the US, ZhongAn in China, and hibob and Gryphon in the UK have raised hundreds of millions of dollars each.

ZhongAn, backed by Ant Financial, Tencent and Ping An Insurance, partnered with the largest e-commerce, mobile, travel and insurance company of China to offer personalized insurance for their customers. ZhongAn sells insurance for web-based actions, such as shipping return policy to Alibaba’s shoppers, flight delay insurance to Ctrip’s customers, and cracked screen insurance to Xiaomi’s customers.

Lemonade has sold dozens of thousands renters insurance so far, claiming to be the fastest growing insurance company among New York millennials. Lemonade built a chatbot called AI Jim to provide insurance policies handle claims, thus replacing brokers. The chatbot can check the claim, validate it with the policy, approve the claim (or deny it), and detect fraud. Among others, it uses the location of residence and a video of the customer via its app as criteria in the process of authorization.  

**Try Emmet here and invest in Zirra via SeedInvest to make private companies accessible**

Loan officers,  Credit Analysts, and Risk Managers

Let’s face it: risk is already calculated by robots. Whether it is the potential risk of not returning a loan or the risk entailed in making a fraudulent e-commerce transaction, robots are doing the jobs at the expense of banks and credit card companies.

Startups such as Riskified, Forter and Signifyd use machine learning to review credit card orders in e-commerce, evaluating the risk behind the orders and guaranteeing them so that any fraudulent orders that do pass through are reimbursed by them. Other startups, such as Fundbox, C2FO, Behalf, and BlueVine, are offering invoice financing for businesses, allowing them to expand and pay their payroll while waiting for third-party payments.  In addition, Funding Circle, Lufax, Zopa, EZbob, and Blender operate peer to peer lending platforms, allowing individuals and businesses lend money from their peers.

Most of these platforms belong to small startups that have not shown any profitability yet, one has to admit. Further, they serve mainly small or medium businesses and haven’t yet penetrated into the 500 Fortune club to make a more significant change in the industry.

Personal Financial Adviser

The age of robo-advisers has begun. Financial advisers and planners are already being replaced by programs and chatbots that automatically manage money and wealth for individuals, mostly millennials and those with average wealth and investment needs. Robo-advisers bring an empirical methodology to financial advisory, and also offer cheaper fees than human advisors. Companies such as SigFig, Betterment, Hedgeable, WiseBanyan, Wealthfront, Futureadvisor, and Personal Capital manage together almost trillion dollars, according to Business Insider.

SigFig, for instance, uses algorithms to track several metrics in the portfolio and provides investment recommendations based on this technology. It also takes into account the customer’s risk tolerance and automatically diversifies the investment accordingly.  An average investor could save up to $5,000 in fees each year, according to the company, or 4-5% of the average portfolio. The company has partnered with UBS and Wells Fargo to offer their customers the service.

Another startup, Personetics, is calling itself a “cognitive banking technology company” and uses predictive analytics and AI to provide timely insights to bank customers – or “nudges” as the company calls them. Customers will receive alerts about duplicate debits on their credit cards, that their cards have been used at new merchants, or that an important birthday is about to come so that automatic savings will temporarily stop. Other apps, such as Digit, Acrons, Chip or Qapital provide a similar service.

**Try Emmet here and invest in Zirra via SeedInvest to make private companies accessible**

AI Everywhere, Autonomous Buses, and fewer On-Demand Startups: 2017 In A Nutshell

A.I will be present in every startup’s toolbox, Apple will launch a VR product, mid-size autonomous vehicles (20-30 passengers) are going to become a focus area, and the on-demand crunch will deepen in 2017. Zirra asked nine VC investors to predict how 2017 is going to look in their field of expertise: A.I, AR/VR, automotive, drones, on-demand, voice-based assistance, FinTech, cyber-security, and marketing tech. After reading them, you will be surprised to learn that future has never seemed so close.


A.I in 2017 

Amit Karp, Vice President at Bessemer Venture Partners

There is not doubt 2016 was the year of AI, and more specifically, Deep Learning. Google’s DeepMind win against legendary Go player, Lee Sedol, was a defining moment for the industry and created a lot of buzz around AI. However, I believe we are still just at the early beginning of a large AI revolution that is going to impact almost any business out there. We are going to continue to see AI further progress in 2017 and the years to come. The building blocks of AI are still rough today and it’s too difficult to use. Many companies are trying to solve this by building anything from dedicated GPUs, accelerators, and cloud computing infrastructure for deep learning, to new and enhanced software libraries and tools for AI. In some ways, AI is following a course similar to that of big data in its early days. At the time, being a “big data” company was perceived as an advantage. But in the long run, it turned out that every good company needs to leverage “big data” to stay competitive. Similarly, we are seeing many new startups that claim their advantage is in deep learning. But over time, I believe every company will leverage AI in some shape or form.


AV/VR in 2017

Guy Horowitz, Investment Partner at Deutsche Telekom Capital Partners

In 2017, a clearer distinction will be drawn between AR and VR. While some underlying technologies are shared between the two types of experiences, the use-cases, hardware, and content are completely different. AR will continue to revolve and evolve around productivity and gaming, while VR is driven by the content. Quality content will drive more users to VR experiences, such as games and short-form.

There’s nothing virtual about VR in 2017. For those attending CES this year, either in person or virtually, VR was very real and immersive. Not all pieces are in place. The main challenges of VR remain the availability (and discoverability) of content, the wide performance gap between high-end devices and low-end gear, and the price of the top-quality experiences – especially as VR peripherals get into the mix. 2017 will mark the entry of Apple into the arena, focused on content creation after acquiring and integrating PrimeSense and Metaio. Facebook will double-down on content distribution, no longer through the Oculus brand. 2nd generation of standalone devices by HTC, Sony, and Oculus will be connected (rather than tethered), new entrants will enable both consumption and acquisition, and in general the 2017 VR gear should be more appealing to the masses.

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2017 will not be a year of mass adoption, but VR will become part of more and more people’s life, especially with WebVR and Mozilla A-Frame adoption. Hand-tracking technologies will take a while longer to get integrated into the head-gear, so regardless of autonomous driving, 2017 will be predominantly “hands-free.”


Automotive in 2017

Ran Achituv, General Partner at Magma Venture Partners

Connectivity and electric vehicles (EV) are going to emerge as the strongest innovative trends in 2017-8 and they are a pre-condition for any self-driving car model; connectivity is a more immediate trend while EV a longer term one. Among car manufacturers, Tesla has an advantage due to its achievements in connectivity and EV, so it can learn and adapt faster.

In the meantime, a war is going on between various sensor types, with radar vs. lidar (a laser based radar) war intensifying as selections for 2020-21 models for all OEMs are all going to be done during already this year. Also in 2017 the fate of V2X (Vehicle To Everything communication) is going to be determined either as a must component in every vehicle or vanish like the WiMax did.

Public transportation solutions based on mid-size (20-30 passengers) autonomous vehicles are going to become a focus area in 2017 due to the economic benefits. From a technical point of view, they have already purchased knowledge of fixed routes. Five or Six OEMs are going to run live trials in that newborn technology and they are about to learn it would take them another one or two years to perfect the technology.

Specifically, for Israel in 2017 we will see one or two mid-size acquisitions and more OEMs and first tier technology players opening offices here.

Drones in 2017

Shuly Galili, Founding Partner at UpWest Labs

2017 will be a defining year for drones as the leading players in the industrial, consumer, and military sectors continue to crystallize market segment ownership.

While the rapidly expanding consumer market will be increasingly dominated by leading manufacturing giants, a growing trend of “drones for industry” will bring a new diversity into the marketplace.

In terms of applications, while photography is persistently the main application for drones, additional uses in agriculture, mining, and industrial inspection will move further from being a disruptive method and closer to being a common workplace tool.  Provision of commercial aerial data will continue to come from small “drone-as-a-service” providers while a select few enterprises will choose to establish in-house resources for drone operation.  Although drone delivery applications are creating a lot of buzz, there are still obstacles involving regulations that are not likely to be resolved in 2017.

Meanwhile, the now infant model of full-cycle drone automation, or “drone in box” model, will begin to scale as a permanent onsite tool for industrial use.  Some of the growing industries to adopt drone operations include: mining, oil and gas, seaports, power plants, and other energy companies.  The agile drone companies who can efficiently provide analyzed data to these industrial players will win.

As drone giants begin to integrate horizontally, prospects for nascent drone startups become increasingly slim, both with respect to investment, intellectual property, and competition. Therefore VC investments in the space will likely decline in 2017 while large enterprises and consumer brands will step in to dominate the investment in the space.  Equally, we will start to see more M&A activities in 2017.

Last but not least, regulation continues to serve as a major stepping stone on the way to infuse drones into industries. We predict 2017 will introduce some important milestones in terms of regulation of automated drone systems in the industrial space.

Cyber Security in 2017

Arik Kleinstein, Founding Manager Partner at Glilot Capital Partners

2016 was the year cyber-attacks dominated the headlines, exposing vulnerabilities in businesses and industries. The growing sophistication of cybercrime-as-a-service business models led to more data breaches, as well as botnet and malware distribution attacks. New types of threats emerged, such as ransomware and DDoS attacks leveraging IoT devices. We expect to see the following trends take center stage in 2017:

Ransomware will continue to be a common attack method and evolve to target enterprises, critical infrastructure, and cloud-based data centers. The attacks we’ve seen in 2016 will be more frequent in 2017 to abuse IoT devices, mobile devices (including iOS), and legacy critical infrastructure systems, while new cyber-security vulnerabilities will arise from smart cars.

AI will be incorporated more broadly to accurately predict malicious behavior and attack vectors. More smart and comprehensive threat intelligence solutions will be used to remediate attacks, and isolation methods will be leveraged to create secure by design IT infrastructure.


On-Demand in 2017

Daniel Cohen, General Partner at Carmel Ventures

Many people talk about 2016 as a “tough” year, but it was possibly even worse for the on-demand category. If in 2014-15 we saw a surge in on-demand investing, 2016 became the time of disillusionment, as investors realized that not everything is right for on-demand. Heading into 2017, we are going to see this trend continue, as the real on-demand winners will start to emerge. Who will be those winners? It’s not enough to be the “uber of something,” as it’s all about unit economics, and the ability to show long-term sustainable profits. The 2017 winners will be determined based on 3 main criteria:

Ability to compete with the big boys – but mostly with Amazon. As Amazon enters the on-demand market, they are best positioned to win, leaving specific verticals and niches to competitors. Startups now have an option to improve unit economics with additional products and services. Uber does it with surge pricing, but it can be better if there are upsells at high profit-margins and if there is an increased life-time-value through high-switching-cost. What differentiates a service that requires users to stay and not move to a competitor?

2017 will truly separate the on-demand men from the boys. Those who will win with great unit economics will generate enormous value.

Voice Based Assistants in 2017

Yanai Oron, General Partner at Vertex Ventures

2017 is shaping out to be the year where voice based assistants make the leap from novelty to main stream phenomena and Amazon has the front seat to take advantage of it. Amazon has gotten to an early success and has momentum on its side. It has come out with the first, powered byAlexa – Echo and already sold over 5 million devices.

A key factor driving this success is the network effect for the adoption of Alexa created by Amazon opening access to third party applications, called Skills, and there are over 7,000 of those. Amazon also licensed Alexa to other hardware manufactures to build their own Alexa powered hardware. Walking around at CES last week, I encountered numerous Alexa-powered devices including TVs, speakers, lamps, cars, and others. Ben Thompson, in his blog “Stratechery” calls Alexa the operating system of the home.  He also noted that Amazon has an obvious business model for this (consumers ordering more stuff from Amazon) while Google might find it hard to monetize voice interface on this platform.

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With their early success, we’ve seen the competition heat up. Google has come out with the Google home which can compete based on their AI and knowledge graph prowess. It presented its API only this past December so there has been no network effect yet.

Google and Apple made the bet that the phone will be the center of the home but that is not happening so far. Apple has not come out with a Siri for the home yet but many expect them to do so. It will be great to see how this plays out in 2017.

A platform shifts creates an opportunity and voice first startups is already becoming a thing. The proverbial “Shovels and Picks Strategy” is already coming into play with a few startups building toolkits to create such voice application but the bigger opportunity in my mind is to come up with a delightful new experience that delights users similar to what Shazam did in the early days of the iPhone.

FinTech in 2017

Alon Lifshitz, Managing Director at Blumberg Capital

The financial services sector is bracing itself for an unprecedented period of disruption. The days of standing in line at a bank are long gone for many as technological innovations are forcing everyone from banks to small businesses to consumers to adapt. In 2016, our Blumberg Capital FinTech survey found that the majority of respondents believe traditional financial institutions are no longer meeting their needs and nearly 75 percent agree that FinTech provides everyone with more power over their finances. At Blumberg Capital we believe in the power of FinTech and that is why we partner with forward thinking banks and invest in the companies at the center of the FinTech revolution. These banks and companies are providing consumers and small businesses access to new financial products and services that are helping save money, make smarter decisions, and operate more efficiently.

In 2017, we expect to see continued mass adoption of FinTech and a focus on a security for financial institutions. Both startups and incumbents need to adopt new technologies to meet the demands of the consumers and business owners while providing adequate cybersecurity in an increasingly dangerous environment. We see the intersection between cybersecurity and FinTech becoming more prominent as cyber threats continue to become more complex.


Marketing Tech in 2017

Kobi Samboursky, Founder & Managing Partner at Glilot Capital Partners

As we kick off 2017, one specific vertical of technology is expected to see a particularly explosive year – marketing tech. While AI continues to develop and evolve, predictive technology is already reaping benefits and will continue to do so throughout the year with more robust and comprehensive solutions.

This will also be a huge year for personalization, specifically when it comes to account based marketing, as well as hyper-targeted advertising using more advanced adtech tools and cross-channel personalization.

Other fields to benefit from AI include bots, which will affect not only B2C campaigns but will have a deep impact on B2B as well. Finally, we will see much more advanced analytics and quantification of every dollar spent combined with much more automation, in both sales, marketing, and end to end processes within the organization.