Software Robots Get Smarter Thanks to AI
09 Décembre 2019 - 11:59AM
Dow Jones News
By Angus Loten
Software robots designed to handle routine work around the
office are undertaking more ambitious jobs.
By combining robotic process automation with machine-learning
capabilities, software makers are developing robots that can tackle
higher-level workplace functions, including many that require a
degree of judgment.
Some of these new roles include verifying a signature on a
check, assessing insurance claims and detecting fraud in
paperwork.
Most software robots in use today are programmed to complete
straightforward numerical tasks, such as processing weekly payrolls
or reviewing employee expense reports, which can be based on a
template.
"Organizations want to automate ever more complex, wide-ranging
activities, so we're pushing the boundaries of what RPA can do,"
said Pat Geary, chief evangelist at Blue Prism Group PLC, a
U.K.-based robotic process automation vendor with roughly 1,300
customers.
Blue Prism is testing an AI-enabled platform for insurers that
can interpret the validity of claims and make recommendations for
human examiners. With approval from the examiners, the robot can
process the claim, significantly reducing the time and effort
needed to handle a case from start to finish, Mr. Geary said.
UiPath Inc., an RPA maker based in New York, is working on an
AI-enabled software robot that can verify signatures on checks
deposited in ATMs.
"Checking a signature takes two seconds for a person," said
Daniel Dines, UiPath's chief executive. But if you want to automate
the entire banking process, he added, "this is the only missing
piece." Unlike many instant electronic-banking transactions, such
as mobile payments or transfers, checks deposited in ATMs need to
be manually verified, prompting some banks to withhold the
funds.
The problem is that legitimate signatures -- on checks,
contracts or other documents -- tend to vary in ways that are
difficult for automated systems to recognize and clear, Mr. Dines
said. Through machine learning, robots that continually repeat the
task can be trained to disregard these minor differences without
losing the ability to flag suspicious cases.
In early testing, these trained robots have had a success rate
of 80%, where checks were cleared with absolute certainty. For the
remaining 20%, the robots were less sure and sent the checks to
human tellers.
In another initiative, UiPath is developing robots that can
identify and extract the most valuable data from reports with a mix
of unstructured formats, sources and information.
The Canadian unit of energy company Chevron Corp. is testing a
version of the tool designed to extract critical operating data
from drilling and completion reports. Such reports are produced for
dozens of oil wells every day; they range from 75 to 300 pages.
Until now, the task had been handled by staff analysts who went
through reports page by page, eating up time and resources.
The AI-powered robot taps a Microsoft Corp. tool designed to
identify and gather desired data, and puts the data into a common
format. The robot then assigns a value rating, based on its
interpretation of the data, and stores it in back-end systems for
analysts' review.
The UiPath technology would allow Chevron employees "to analyze
data faster and to gain deeper insights," a company spokesman
said.
These and other smart capabilities are putting Blue Prism and
UiPath at the front of a fast-growing market, according to
Forrester Research Inc.
An estimated 60% of large companies world-wide deployed some
form of RPA technology last year, lifting total annual spending on
software robots by 57% to $680 million, according to tech-industry
research firm Gartner Inc. It expects such spending to reach $2.4
billion by 2022.
Write to Angus Loten at angus.loten@wsj.com
(END) Dow Jones Newswires
December 09, 2019 05:44 ET (10:44 GMT)
Copyright (c) 2019 Dow Jones & Company, Inc.
Chevron (NYSE:CVX)
Graphique Historique de l'Action
De Mar 2024 à Avr 2024
Chevron (NYSE:CVX)
Graphique Historique de l'Action
De Avr 2023 à Avr 2024