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It’s an uncomfortable fact we live with—but extreme weather is rising and becoming more severe as temperatures continue to rise, globally. In 2021, the United Nations published a report on the frequency of weather-related natural disasters in the past 50 years and reached the conclusion that extreme weather events have risen by 5 times. With this frequency comes rising costs of damages. While we still cannot predict nor control the weather, innovations in AI are making it possible for insurance providers to process claims as soon as disaster strikes. 

RPA tools have helped claims adjusters streamline some of the most mundane and time-consuming tasks. However, robotic processing automation (RPA) is no longer the cutting-edge tool it once was. The newest generation of AI-based automation tools far surpass legacy RPA software and dramatically accelerate claims approvals. 

In fact, Automation Hero’s deep-learning AI has helped insurance companies reduce claim processing times by 80%. This report provides valuable data on the rise of extreme weather events and the available technologies supporting insurance companies navigate the rising costs of damages.

Unstructured data is the driving force of digital transformation. As new customer information increasingly comes in through email, text messages, social media, photos, PDFs, and handwritten scanned documents — most new data we collect and produce is “unstructured.” 

Organizations increasingly differentiate themselves by tapping into their most valuable asset so they can drive their digital initiatives and gain a competitive advantage. In this whitepaper, TIBCO explains why businesses need intelligent document processing, and how this next-gen technology turns unstructured data into business value. 

TIBCO also evaluates the intelligent document processing market — highlighting Automation Hero’s ability to turn unstructured data into high-value business assets using cutting-edge AI, natural language processing, and OCR technologies built into the Hero Platform_. 

Finally, TIBCO evaluates many of the industries that will benefit the most from adopting IDP technology.

Financial services and insurance organizations worldwide are becoming increasingly aware of environmental, social, and governance (ESG) risk factors and the potential impacts on their investment portfolios and lending policies.

Hear from Element22’s Mark Davies and Automation Hero’s Irina Berdisa as they discuss how institutions can approach the increasing pressure from external shareholders to better manage exposures to environmental risks.

Client on-boarding is becoming increasingly complex, with financial institutions spending exorbitant amounts of time and money manually processing checks.

So how can your KYC document process be conducted accurately, efficiently, and without adding extra weight to your team’s workload?

Join Domenico Martinez, Solutions Engineer and Michael Smith, Sales Director at Automation Hero to learn about how digital KYC can help.

You’ll learn about the benefits of automation in KYC processes, such as:

• Eliminating Data Entry (process documents through an intelligent OCR (optical character recognition) model to extract the key data fields)
• Reducing Errors (perform ETL (extract, transform, load) on key data fields to normalize the data)
• Improving Reporting (update the calendar of the account manager to re-assess the account based on the expiry date of all processed documents)

Perhaps you’ve implemented robotic process automation (RPA) in your company. You may or may not have seen improvements and hit the goals or metrics you were hoping to achieve. Whether you’ve seen success or not, there’s still room for improvement by adding AI. 

In this piece, we’ll walk you through the differences between RPA (robotic process automation) technology and IPA (intelligent process automation), and spell out the advantages of each. 

For example: even after implementing automation, many employees still spend hours of time manually handling documents that are too complex for RPA. These include data extraction, data normalization, and turning unstructured content (e.g. text and images) into a structured, usable format. That’s where modern AI-driven automation technologies like intelligent document processing (IDP) come in.

What is intelligent document processing?

IDP was born out of the need for organizations to accurately extract data from documents. In essence, IDP leverages artificial intelligence (AI) and natural language processing (NLP) to effectively handle and oversee document-centric business processes. Through the adoption of IDP, organizations can optimize business processes involving a large volume of documents to reduce manual effort, enhance precision, and reach their digital transformation goals.

A notable advantage of IDP is its seamless integration capability with other automation tools like robotic process automation (RPA). This compatibility with existing technologies enables companies to enhance their current automation strategies, leading to improved overall efficiency and expanded operational scope. Read more to find out all of the advantages of upgrading from robotic process automation to artificial intelligence.

Learn How Advanced AI Keeps Your Organization Out of the Red

Text redaction is a crucial process for keeping customer data safe — and your company compliant. But even with automation solutions, it can be a labor-intensive, error-prone process that leaves consumers exposed to identity theft, and your company exposed to liability. That’s why you need a platform backed by AI. 

In our new eBook, “Redact smarter: How intelligent process automation is solving the oldest problems in data security,” you’ll learn:

• Why manual redaction is no longer feasible in today’s market
• The limits of specialized auto redaction software
• How end-to-end AI platforms solve them
• What Automation Hero can do to future-proof your company

To automate business processes with AI, business workflows need to be driven through AI models that were trained on historical data and that are continuously improved and refreshed. Traditional business process automation platforms are modeled manually and are less powerful and efficient than AI models that are trained on historical data. Individual steps such as updating a customer address or creating a quote are done manually by the human workforce.

A modern AI automation platform should drive and automate these steps through AI. The human workforce will remain a critical component in the workflow, but the real goal is to automate as many steps with AI – from data entry to reaching out to customers at the perfect time – as possible.