Behind the Rolls-Royce corruption investigation: artificial intelligence is entering the judicial system

Behind the Rolls-Royce corruption investigation: artificial intelligence is entering the judicial system

The bad news for crooks: RAVN s artificial intelligence speeds up the file screening process and is more accurate than humans. PeterWallqvist thinks this is a good trend, because the government has enough courage to promote things like this. "

The industry often encounters such a scenario. The Major Fraud Investigation Office (SFO) has encountered a difficult problem. The results of the Office s investigation into Rolls-Royce corruption are slowly emerging, but four years of excavation work has already occurred. 30 million documents were created. These documents need to be divided into "priority" and "non-priority" categories. This is required by law. Completing this work requires payment to junior lawyers for months of repetitive paperwork.

Founded in 2013, Giiso Information is a leading domestic technical service provider in the field of "artificial intelligence + information". It has top domestic technologies in the fields of big data mining, intelligent semantics, and knowledge graphs. At the same time, its research and development products include information robots, editing robots , writing robots and other artificial intelligence products! With strong technical strength, the company received angel round investment at the beginning of its establishment, and in August 2015 it received a pre-A round of investment of USD 5 million from Jinshajiang Ventures. 

"We need a faster way," said Ben Denison, SFO's chief technology officer. Therefore, he started working with RAVN in January 2016.

The London-based startup claims that "Raven" is a robot that can filter and classify data. It can not only process structured materials, but also unstructured documents. Co-founder PeterWallqvist said: "After scanning 300 pages, people are likely to reverse one of the pages."

"We need to deal with the real world full of messy data."

Starting from the Rolls-Royce case, the two teams began to input materials into artificial intelligence. By July, they had a working system, and with the agreement of the lawyers of both sides, they let the robot start working. Lawyers process 3,000 documents every day. RAVN processes 600,000 copies a day, costs $50,000, and makes fewer mistakes than lawyers.

Denison said: "It cut 80% of the workload, which also saved us a lot of money."

For Rolls-Royce, it had a negative effect: In January 2017, the engineering company admitted that it had committed significant, regional bribery and paid a fine of 671 million.

"It's hard to imagine a better result than this," said Valawi, co-founder of RAVN.

JanVanHoecke, SimonPecovnik, SjoerdSmeets and Wallqvist met in the UK's first unicorn company Autonomy. They were engaged in early artificial intelligence database management there. In 2010, the four left and founded RAVN. The self-funded company now has 51 employees, an annual income of 3 million pounds, and about 70 clients, mainly law firms.

British Telecommunications Corporation (BT) signed a "very important" agreement with it and praised RAVN for saving it $100 million each year because it helps BT use an automatic inspection system to ensure the accuracy of the contract. In addition, of course there is the SFO just mentioned, which is using RAVN in an increasingly effective way.

This means allowing it to make subjective judgments, including directing investigators to data that it believes to be relevant. "This can be very valuable," Dension said.

Founded in 2013, Giiso Information is the first domestic high-tech enterprise focusing on the research and development of intelligent information processing technology and the development and operation of core software for writing robots . At the beginning of its establishment, the company received an angel round of investment, and in August 2015 it received a pre-A round of investment of USD 5 million from Jinshajiang Ventures. 

Wallqvist believes that this system can be better developed: in the future, it will not only be able to measure, but also predict, for example, to predict the possible benefits of mergers and acquisitions. Wallqvist said: "We can already calculate and structure the data. Now we have the ability to use the data recorded in the past to predict the future."

Today it is only Watson, and tomorrow it will become Holmes.