By Ashley Keil, IBML’s VP sales, EMEA/APAC, discusses how artificial intelligence platforms can radically change, improve and automate how documents are handled and processed
Don’t panic! You might recall the famous inscription on the cover of The Hitch Hiker’s Guide to the Galaxy, a classic sci-fi book written by the late Douglas Adams which charts the adventures of Arthur Dent and Ford Prefect after Vogon’s demolish Earth to make way for a new hyperspace bypass.
Published in 1979, what might not be quite so well-known, is just how prescient Adams was in terms of referencing technology which has subsequently been developed. The fictitious Hitch Hiker’s Guide itself was almost a precursor to the Kindle – a handheld electronic book able to serve a million pages via a four inch square screen. The information stored in it is user-generated and constantly updated – exactly the approach adopted by Wikipedia – and the Babel Fish introduced the idea of putting something in your ear which could then translate languages – a concept actually brought to market in 2016 by Waverley Labs with the Pilot Smart Earbuds.
And talking of Babel Fish, rapid developments involving self-learning artificial intelligence platforms [AI] – which solve complex problems automatically – are now enabling information and business managers to quickly gain real insight from documents irrespective of the language, the computer file format used and whether documents contain machine print or cursive handwriting or both.
This is radically set to change how organisations cope with recognising and classifying millions of documents and then extracting and validating information without any manual intervention at all, thereby increasing productivity, accuracy and saving money.
Existing character recognition technologies have their limitations
To date, a vast amount has been invested deploying traditional recognition technologies such OCR, ICR and intelligent word recognition to analyse the content of documents and boost automation. It’s still very much a growth area. Research shows that the global OCR market is expected to reach $13.38 billion by 2025 – increasing at a CAGR of 13.7% from 2019.
Despite this, there are limitations. Many ICR/OCR engines struggle to process a mix of documents – encompassing structured, semi-structured and unstructured data – along with cursive handwriting, historical and old documents especially when the legibility of the paperwork is poor. The situation is exacerbated when volumes are high. And no one traditional ICR/OCR engine can seamlessly process a variety of languages – jumping from documents in English to Chinese, German and so on.
With such variability, correct read-rates drop markedly – it’s still tough to get more than 90-95% accuracy today – such that staff are required to then manually rekey information in. This is time consuming, costly and begs the question of whether enough trained employees are available to do it.
Of course, crowd-sourcing approaches are a good and cheaper work around than actually hiring people to enhance accuracy. Snippets of data are sent to online entry clerks logged into an Internet-based system who then check it prior to inputting it into line of business systems.
But the promise – and now reality – of AI is that these challenges are also resolved using powerful cognitive systems.
AI-powered solutions are available today for document processing
Utilising neural networks, AI-driven document processing platforms offer a leapfrog advance over traditional recognition technologies. At the outset, a system is ‘trained’ so that a consolidated core knowledge base is created about a particular (spoken) language, form and/or document type. In AI jargon, this is known as the ‘inference’. This knowledge base then expands and grows over time as more and more information is fed into the system and it self-learns – able to recognise documents and their contents as they arrive.
This is achieved given a feedback ‘re-training loop’ is used – think of it as supervised learning overseen by a human – whereby errors in the system are corrected when they arise so that the inference (and the meta data underlying it) updates, learns and is able to then deal with similar situations on its own when they next appear.
It’s not dissimilar to how the human brain works and children learn a language. In other words, the more kids talk, make mistakes and are corrected, the better they get at speaking. The same is true with AI when applied to document analysis and processing. The inference becomes ever more knowledgeable and accurate.
AI-based systems can be trained to automatically recognise specific forms, review specific content and its layout on the page and then convert cursive handwriting into standard electronic formats such as PDF or JSON for analysis or workflow purposes with validation and verification also taking place. This can also be done at a field-based level so that key value extraction can be completed. Admittedly this something that ICR/OCR systems can also do but they struggle to recognise cursive handwriting and require complex algorithms to find the fields.
Key value extraction on a form, for example, could be a generic box for ‘name’ or ‘age’ – the key – and then the specific values would be ‘Mr John Smith’ and ‘50’. Or on an invoice, the keys are items purchased and the values are the prices paid for each different one.
The benefits here are clear. Governments, healthcare providers, banks and insurance firms have to process a vast number of handwritten forms with identical formats for various purposes like questionnaires, applications, personal loans, mortgages or claims. Retrieving the handwritten information out of them and converting it into a digital format without human intervention reduces manual errors, lowers cost, allows big data analytics and makes turn around considerably faster.
And the speed of this AI-based processing is impressive. Anywhere up to 50,000 pages per hour can be completed using a single server – with bigger deployments and cloud delivery also possible when more compute power is added.
Loads of different common files can be ingested for analysis such as plain text, PDF, TIFF, JPEG, GIF, PPM, PNG and so on with several neural nets then reading the text and classifying the type – whether it be handwriting or machine print – with ‘fuzzy search’ aiding the text to digital conversion process. And class-leading AI systems – in addition to handling paper documents – are designed to cope with pictures, video and audio, too. Put another way, they are content agnostic and can handle any source content.
AI in practice
This is real stuff. One German insurance firm is working over the next six years to shift its entire claim process to use an AI-powered system such that claims under a certain value will be handled automatically based on information extracted, assessed and approved from a form with no human involvement required at all. This will be accomplished as the AI solution automatically checks the name, address, insurance number and other key details about a given incident – capturing all the data from the form correctly first time every time.
When it comes to document processing, seeing AI in action is impressive. It’s ‘wow’ magical stuff to watch a machine ‘read’ a scanned paper document and extract data from it.
One of the consequences of the Covid-19 pandemic and the economic fallout from it is that many companies will want to improve efficiency in a bid to save money. Those who have a significant cost and operational overhead processing forms and other documentation many feel a sense of corporate anxiety or even alarm about how to do this.
As The Hitch Hiker’s Guide helpfully advised on its cover, don’t panic. AI has sufficiently matured such that it is now a real-world performant and reliable option for companies tasked with grappling and dealing with millions of paper documents.
What does cybersecurity look like for the financial sector in 2021?
By Neill Lawson-Smith, managing director at CIS
The landscape is changing incredibly fast, with cybercriminals using the most up-to-date technology to hack systems. Here are the six areas those in finance should be watching out for…
The finance and insurance sector is increasingly becoming a notable target for cyber attacks. Many of these breaches happening are believed to be due to inadequate security measures when teams or businesses are using cloud services.
The financial industry is also being affected by changes in processes with more fintech, virtual banks, and other digital disruptors impacting the market. The landscape is changing incredibly fast, with cybercriminals using the most up-to-date technology to hack systems, so it is therefore up to the financial sector to keep up to avoid security breaches.
What does this look like for the year ahead in the financial sector? Here are the Six areas those in finance should be watching out for:
- AI securityand cyber defence
Both Cybercriminals and cyber defence are commonly using Artificial Intelligence (AI). In cybersecurity, it is used to identify new threats, as well as assess the effectiveness of the responses to threats, enabling them to foresee and essentially block attacks before they happen. It is also used to spot behavioural patterns and can quickly identify possible infiltrations.
Hackers have also started to use AI to make it easier for them to get past security systems in place. This year, it is likely that AI will be increasingly used as a means of gaining personal details (i.e. credit card details) as well as optimising spam phishing campaigns.
- Mobile cybersecurity in banking
With the number of consumers using their mobile devices for banking and financial transactions increasing, especially since the COVID-19 pandemic has rendered society predominantly cashless, cybercriminals have been heavily targeting mobile systems. For example, mobile malware only targets mobile phone operating systems. The most common forms of mobile malware are virus and trojans, spyware and madware (mobile adware), phishing campaigns, and browser exploits.
This means it is now more important than ever to protect mobile devices to the same extent as traditional hardware.
The same protocols that are in place to ensure your staff PCs and laptops are secure now, need to also be applied to their mobile devices as well, such as:
- Ensuring the latest versions of the operating system and other applications are installed.
- Installing a firewall.
- Enabling mobile security software to protect against malware and viruses.
- Using password protected lock screens.
- Ensuring apps are only downloaded from official sites like Apple App store and Google Play.
- Multi-factor authentication
Multi-factor authentication adds an extra layer of security to all your business networks by ensuring every transaction or login is supported by at least two security measures for access. It is one of the easiest security measures to implement within your business and is becoming more common within the financial sector for many transactions. The traditional username and password are becoming increasingly easy for cybercriminals to acquire, whereas adding an extra identification method, that is not easily accessible to the hackers, ensures an extra layer of protection.
The most commonly used multi-factor authentication methods are:
- Passwords – They should be complex and comprise at least eight characters and be a combination of upper- and lower-case letters, numbers, and special characters.
- One-time use code – A randomly generated code sent via SMS or email which is used only once. With weaknesses in mobile networks and email accounts, these can however be intercepted by hackers.
- App generated codes – a code generated by an app on a mobile phone often created by scanning a QR code that contains a ‘key’. As the key is stored on the phone itself this is less likely to be intercepted by a third party.
- Physical authentication keys – this is a USB which the user inserts every time they login from a new computer. Unfortunately, they don’t work on all devices without adapters (such as iPhone, MacBook or Android).
- Biometrics – Using a fingerprint, voice, or an eye dent is an effective identifier. They are extremely difficult to hack but if they are, they cannot be used ever again for anything.
- Information – this could be something that only the user would know – either a password or a piece of information.
Most of these methods are free or relatively cheap to implement and don’t require anything other than a mobile phone for the user. The added security of multi-factor authentication means even if a hacker has acquired a username/password combination there is still an extra security barrier preventing access.
- Refined testing
As the finance industry is constantly changing, then so too are the security threats. Financial cybersecurity is an ongoing commitment, so installing new anti-virus software and implementing MFA, and stopping there is not going to keep you protected for long. It requires ensuring software and firewalls are up to date as well as ensuring access is regularly updated. In addition to this constant maintenance regular testing of the systems is essential. All systems have vulnerabilities, and as these change, cybercriminals learn to overcome them, and therefore software develops.
One thing to remember is that it is not possible to be over-cautious when it comes to cybersecurity. Regular penetration testing essentially identifies any weaknesses in your systems before the cyber criminals do. It is essential to schedule penetration testing or vulnerability scans at least once a quarter unless compliance dictates otherwise. They can be carried out using a vulnerability scanner.
- Hiring the right people
It is crucial to have the right team on hand to ensure your systems are up to date, regularly tested and maintained is essential.
Your IT team should have the following skills and knowledge:
- Knowledge and understanding of the company’s IT infrastructure
- Knowledge of cybersecurity best practices
- Understanding of company processes and data flows
- Up to date knowledge of cybersecurity solutions
- Plan a Defence, Prepare for Attack…
Although businesses can take many precautions, there are limitations on skills, investment and timescales in implementing a comprehensive cybersecurity infrastructure, it is essential that appropriate procedures, policies and processes are established to ensure that an appropriate response is carried out in the event of a detection – whether manual or ideally automated – so that whenever an attack occurs, the appropriate and proportionate response is carried out immediately to limit any further damage or intrusion.
Data protection: it’s time to reassess your security strategy
By Tony Pepper, CEO of Egress
It’s no secret that the Covid-19 pandemic has created a perfect storm of cybersecurity risk. External threats are heightened, but there’s also a higher level of internal risk too, exacerbated by home working. With most financial services organisations planning to continue with mass remote working for the foreseeable future, it’s important for security teams to review their strategy and assess whether it still works in this new landscape. When it comes to insider threat, there are three key areas that IT leaders should focus on: building a positive culture around security, understanding their organisation’s level of risk and protecting their people.
- Build a security-positive culture
Many organisations have unknowingly instilled a security-negative culture among their employees, where people are punished or shamed if they cause a security incident. While they might think that this would discourage employees from causing data breaches for fear of repercussions, this actually makes your organisation less secure. Our Outbound Email Security Report found that 62% of organisations rely on their people to report email data breach incidents – and if employees are too afraid to come forward, that means your business is at risk of developing a security blind spot.
A security negative culture won’t actually prevent data breaches caused by human error, something which organisations need to recognize as largely unavoidable without technological intervention; it just delays remediation, which makes every incident worse. By creating a security-positive culture, you can better engage and educate employees, as well as ensure you’re able to rapidly triage any incidents if they occur.
- Understand your risk
When mapping out your risk, you’ll likely find that the picture looks very different to how it did even a year ago. In the past, organisations have focused on their networks and their devices when it came to security strategy. While these are vital areas for consideration, what hasn’t been as well-addressed to date is the human aspect of risk, particularly human error. You need to look closely at the tools that your employees are using daily to facilitate digital communication with clients and colleagues, including when sending sensitive information.
Employees are specifically using email more than ever before – our recent research found that 94% of organisations are sending more emails due to Covid-19, with one-in-two IT leaders reporting an increase of more than 50%. With this expansion of email volumes comes an increase in the risk that an email containing sensitive data might be misdirected. Remote working has also heightened the threat – our research found that 35% of organisations’ serious email data breaches were caused by remote working. Why? The causes lie in their behavior and the environments in which they operate. Some individuals may feel they’re able to take more risks away from the “watchful eyes” of their Security team, and every employee is faced with a myriad of distractions that make them more likely to make a mistake.
It’s time for organisations to take stock of their risk by looking at where gaps in their security might exist – and provide safety nets for their employees that can automatically detect and mitigate inadvertent data breaches and risky behaviour.
- Protect your people
It goes without saying that not all data breaches are caused by malicious activity. An overwhelming amount of data breaches are caused by hardworking employees making honest mistakes, from sending an email to the wrong person to responding to a phishing attack. Unfortunately, human error is an unavoidable part of life, and mistakes will happen. In the past, many organisations have taken the approach that employee error can be ‘trained away’, embarking on comprehensive security training programs in the hope that security incidents might decrease.
Unfortunately, if that were the case, then employee activated data breaches would be a thing of the past! Organisations need to employ a multifaceted approach when it comes to avoiding accidental insider data breaches – education and training remain an important element, but ultimately businesses need to implement the right technology to provide a safety net for their people. Many organisations have legacy DLP solutions in place that cannot mitigate the risk as they fail to fully understand employees’ behaviour.
Often, these tools stand in the way of productivity, prompting users even when there isn’t a legitimate risk. When click fatigue sets in, these solutions become ineffective, with users ignoring prompts whenever they appear. Luckily, advances in machine learning mean that there’s technology available to prevent insider data breaches such as misdirected email, by deeply understanding the way that users behave and the context in which they share data, to ensure emails are sent to the right recipients with the right level of security.
The vast majority of organizations will never go back to every employee working full time within the office environment, instead post-pandemic we will see a myriad of different approaches – with some based in the office, while others work at home part or full-time, and as the world opens up again, their locations may change throughout the day. To mitigate risks from inadvertent errors to intentional data exfiltration, CISOs must address their security culture and protect their human layer with intelligent controls that mitigate employees’ behaviors and stop breaches before they happen.
Sumitomo Life Insurance Selects Talend to Build Company’s Data Infrastructure
Leading life insurer uses Talend in data lake environment for data analytics
Talend (NASDAQ: TLND), a global leader in data integration and data integrity, announced today that Sumitomo Life Insurance Company, one of the Japan’s leading life insurance companies, has selected Talend Data Fabric for its data analytics infrastructure.
Sumitomo Life aims to become the most trusted and supported company by its stakeholders, including its customers, and to grow sustainably and stably. Sumitomo Life’s vision is to offer advanced products to enable customers to live vigorously. To respond to that, the company is developing and delivering cutting-edge products that respond to its customers’ current and expected futures needs in areas focusing on nursing care, medical insurance and retirement planning.
“With the trust from our customers as the starting point of all our activities, Sumitomo Life is providing optimal life insurance services to every person through the sound management of the insurance business,” said Mr. Masakazu Ohta, General Manager in Charge of Information System Department at Sumitomo Life. “As a new approach, it was necessary to build a common foundation for big data management, and Talend is the driver. Talend’s superiority in cloud implementation, development productivity, features, and licensing model convinced us to be part of this journey together.”
To meet the needs of its customers and offer them innovative products and services, Sumitomo Life has decided to build a foundation for data analysis (Sumisei Data Platform) in the cloud for the promotion of new insurance products. The company evolved its legacy data environment to the new environment where they can store the data extracted from various systems both on-premises and effectively in the cloud.
In order to meet the needs of each individual customer and provide the best insurance for them, Sumitomo Life uses Talend Data Fabric as the hub of its data infrastructure. This manages data across the organization and integrates data into a data lake, which makes them able to utilize data across the company.
“We have been able to release projects with the continuous support of Talend, even amid the changing business environment in the Covid-19 crisis. We will continue to collaborate with Talend in order to actively promote company-wide data analysis projects,” added Mr. Ohta.
“The insurance market is one of the most competitive sectors. By facing tight regulations and complex customer needs, companies must be at the forefront of innovation to offer even more services and new products to its customers,” said Kenji Tsunoda, Country Manager Japan, at Talend. “Talend helped Sumitomo Life reinvent its data-driven infrastructure to provide a data management platform that enables the development of advanced products for its customers. We are delighted to support Sumitomo Life in the pursuit of their vision.”
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