In an interview with Goldman Sachs Asset Management, Daniel Nadler, the CEO of Kensho Technologies says he was surprised to learn that there were no tools to assess the impact of world events on financial assets when there was clearly an immediate impact.

I was stunned to learn that as important developments were occurring around the world—central bank announcements, elections in Europe, the European sovereign debt crisis, turmoil in the Middle East, etc.—there was no existing mechanism to track similar historical events and analyze the implications so as to glean insights. Neither regulators nor bankers had an efficient and effective method for assessing the impact of similar events on financial markets beyond digging up old news clips and manually creating spreadsheets.

Kensho is a big data search engine that does not merely match keywords in documents to throw up answers. It generates answers by analyzing relationships between events, regulations and any other factor that might impact a situation…and it does so in seconds. A team of analysts would have taken several man-hours to provide the same answer.

Kensho is one of the newer entrants using technology to make inroads into the financial industry. Nadler refers to this as the Fourth Revolution.

The First Industrial Revolution used water and steam to power production. The Second used electric power for mass production. The Third used electronics and information technology to automate production. This Fourth revolution is building on the third to create a “digital revolution.” In this vein, our goal is to bring advanced technologies, like machine learning, to bear on aspects of the capital markets in ways that, until now, have been the provenance of a very select set of elite hedge funds. By making this technology more accessible, market participants are able to gain a more efficient and transparent understanding of capital markets. Through our media partnerships, we are also bringing greater market insight and transparency to everyday investors, revolutionizing their access to information that helps them achieve their goals.

One of the first places that technology started changing things in the financial market was the stock market. Companies started using software to buy and sell shares for customers who had smaller investments to make. Bots were making buying and selling choices far faster and way cheaper than their human originals. Trading algorithms were placing trades based on pre-set instructions. Their speed and frequency made it impossible for human traders to match.

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New areas include project appraisals, where software are analyzing all types of data while considering approvals, not just credit scores. Complex software are helping retail customers invest in the stock market, with no interaction of a human financial advisor. Wealthfront is an example. Compared to dealing with a financial advisor who eggs you and calls you repeatedly, Wealthfront has made investing super simple and easy, with options to make recurring or one-time investments easy.

Technology is going to replace the $20 customer service representative, but it is also going higher up the value chain. As machine learning becomes more sophisticated, complex tasks that involve analyzing are being taken over by technology. The financial industry stands to lose 54% of its jobs to technology in the next 20 years. Here are some of the roles technology has already taken over in the financial industry.

Robo-advisors: These are online portfolio managers that work with minimal human intervention. According to Bloomberg robot-advisors are expected to manage $2.2 trillion by 2020 in the U.S alone. Robo-advisors help track portfolio progress, rebalance portfolios and provide options for long-term, short-term or liquidity as the case might be. Low advice fees, high speed, and minimum fuss make robot-advisors a top draw among small to medium investors.

Fund managers: Quant funds are algorithm funds that hedge managers use. In the recent years, pure quant funds have been topping the hedge fund list. Quant funds too are now expected to make more anticipatory moves, based on the insights they glean from multiple sources of data that includes mobile devices as well. Quant funds do not require human intervention, though in some cases subjective human intervention has been used. The call made by financial companies today for job openings are for big data analysts, cloud computing, machine learning and software developers.

Stock-brokers: Automated stock trading software is being used extensively. Rather than a one-time operation, this software uses pre-defined trading strategies to trade continuously without human intervention. Automated stock trading software analyses data, mimicking human behavior. Its speed of placing trades will also help investors make profits on market fluctuations. Investors are increasingly buying this kind of software and managing their portfolios themselves, rather than going through a stockbroker. 

Risk Management: Robotics can analyze data to reveal changes in risk exposure. It can also evaluate credit limits, changes in limits and propose remedial actions. They help ensure a uniform assessment and work at very high speeds. 

Process Automation: This is an area which is going to see an increased use of robotics. They help standardize repetitive task, with a low margin of error.

Accounting: Robotics is being used for journal entries, general ledger reconciliation, fixed asset accounting and maintaining master data. Expense reports, vendor invoices, and payments can also be managed by robotics

Is it all bleak news then for financial practitioners? No, it is in fact, an opportunity to learn new skills, bring in greater clarity while providing insights to customers. It also means the  opening of newer type of jobs. Judgment related tasks will open up for humans. But it is definitely a change of gears on the financial highway.

An Accenture report ‘From Reporting the Past to Architecting the Future’ discusses how to handle the technological disruption in the finance industry states the following:

Roles in financial analysis and planning will have to learn to anticipate alternative scenarios and contingency plans. Financial controllers will need to start focusing on preventive and real-time controls. They will need to manage outcomes, rather than processes. Employees in accounts payable will need to collaborate with other functions and look at exceptions since most of the other work will be automated. The report further speaks of emerging roles in the financial industry. Some of them are:

Data Scientist: Detailed industry knowledge; ability to generate rich data sets by combining data from various sources. Has the ability to manipulate large volumes of data.

Scenario Planner: Ability to generate multiple scenarios and their impact. Has the capacity to run several models at once.

Market Maker: A person who can spot new business and investment opportunities.

Social Behavioural Scientist: Model changes in customer behavior and understand its financial implications.

For companies and employees in the financial space, the need of the hour is how to stay relevant going forward. This will require a mapping of skills required to those existing now. The gap that will reveal itself will also be the skills required in the future.