The ability to foretell the future is nothing short of a superpower. Back when Insurance was a business of pen, paper, and trust, insurers used their intuition and years of experience to evaluate and analyze the risks involved and calculate appropriate and reasonable premiums. The importance of staying ahead of the competition and making data-driven decisions is now more than ever, but with the sheer volume of data that insurance companies collect and store today, it can be overwhelming to make sense of it all using just human intuition and experience.
This led to the inception of optical character recognition (OCR) solutions that could convert scanned documents into editable text through data capture and entry. While this helped save a lot of time and money for the insurers, these traditional OCR solutions were not equipped to handle these complex documents and data at scale since they were not able to understand the context or structure of the document, which is where Intelligent document processing solutions come into the picture.
An end-to-end intelligent document processing (IDP) solution can help insurers overcome these challenges by advanced AI models making sense of the data being scanned while reducing processing time, enhancing operational efficiency, increasing data quality, and achieving cost reduction. Let’s delve deeper into these key challenges to get a sense of how an IDP solution can help insurers.
Document Variation
Document formats vary based on lines of business as well as the business function in the entire insurance value chain. For instance, an ACORD form for a Commercial Insurance application is completely different from that of a Property Insurance; similarly, the variation in terms of documents that are attached as part of an underwriting submission versus those that come as part of an FNOL have a significant difference. Documents such as Loss Runs, Policy Quotes, and Insurance applications are more free-flowing in structure and have variations for each carrier and line of business. There is often no standardization in business workflows which makes the adoption of existing traditional out-of-the-box solutions difficult.
Manual Processing
The current methods of document processing have not been able to keep up with the scale at which new documents populate insurers' databases. The knowledge workers' valuable time is spent on labor-intensive tasks rather than further analyzing the data to generate actionable insights.
Insight and Intelligence
The unpredictability of the insurance industry means understanding data and using it to make informed decisions. Insurers receive and generate a colossal amount of documents of various types, formats, and templates and due to the lack of efficient automated document processing, a huge amount of data present in these documents remains untouched. This unprocessed data contains insights that can help predict future outcomes and help in detecting outliers and abnormalities.
Key executives and decision-makers have realized the massive costs of lost opportunities and delayed decision-making resulting from a lack of a system of document management that automates insurers' entire workflow from document ingestion to producing output in a machine-readable format like .xml, .json, .xlsx, .idx
How can Insurers tackle these obstacles?
Intelligent Document Processing has proven to solve insurers' issues regarding inefficient processing and document complexity. Companies that adopted IDP solutions have reduced processing time while also lowering resource costs by as much as 30%. The Automation of workflow using AI-powered Document processing has generated 30-200% ROI in the first year alone.
A large number of insurers typically start their digitization journey to achieve two immediate outcomes - reduce the time spent by knowledge workers on repetitive work and the error rate due to manual processing. AI-led document intelligence platforms such as Dociphi are ideal for such requirements.
Dociphi, Quantiphi’s intelligent document processing platform, allows insurers to achieve over 90% accuracy in the classification and extraction of data from multiple formats. We also configure real-time monitoring of inboxes to ingest emails along with the email body and attachments onto Dociphi. Dociphi supports all relevant doc types including PDF, word, excel, images, and even embedded documents within a parent document.
How does an end-to-end intelligent document processing solution work?
Modern document management platforms such as Dociphi ™ (A Quantiphi Product) are intelligent, scalable, and can be easily integrated with your existing enterprise applications.
- Ingest: Documents are seamlessly ingested from multiple data sources via an omnichannel platform.
- Process: The documents are then classified into precise document types with the help of ML-based classification models.
The necessary information is extracted from key value pairs, tables, checkboxes, forms, handwritten texts, etc using cutting-edge AI Technologies and then sent to an underwriting or adjudication system with the help of downstream integration. Additionally, insurers can also automate their entire policy review process by viewing and comparing multiple policy, quote and binder documents using Dociphi’s document comparison feature. - Generate Insights: Automating your submission pipelne is just the beginning. Insurers can leverage the extracted data to fulfill not only descriptive and inquisitive reporting needs but also further enrich the data using third-party APIs to develop predictive models for risk scoring and prioritization.
How can these generated Insights help Insurers achieve their goals?
The Data that's extracted from these documents contains a treasure trove of insights and knowledge that is hidden and often overlooked. Dociphi, Quantiphi’s intelligent document processing platform, allows you to visualize your data using dashboards and reports that are customizable, dynamic, easy to use, and simple to interpret.
The visualization provides you with a snapshot of your data, the reports provide detailed information regarding your policies and how their success varies across regions, demographics, and customer groups assisting in deciding the optimal marketing and sales strategy
The extracted data combined with the accuracy of Machine Learning models can be leveraged to predict and forecast future outcomes. Applications like recommendation engines and fraud detection not only help in increasing profitability but also increase overall customer satisfaction
Some of the applications of Predictive analytics in combination if document automation are:
Pricing
- Analysis of consumer behavior patterns, buying propensity
- Personalized pricing and premiums on the basis of customer behavior, risks associated and affordability
Risk
- Predictive analytics to help identify claims that are outliers
- Analyze claims risk using historical claims data, customer behavior, loss runs, etc.
- Predict the possibility of any potential illness, and take this into consideration while printing insurance policies
- For property and home insurance, analysis of data regarding built quality, year of construction, history of losses & claims filed
Fraud
- A 2022 study on insurance fraud found that insurance fraud can cost U.S. consumers $308.6 billion yearly and predictive analytics can help bring this number down by using innovative techniques to predict, detect & mitigate fraud
- Predictive analytics can identify potential fraud by detecting outliers, monitoring suspicious claims activity, and signs of fraudulent behavior using the data gathered from claim adjustment and monitoring insureds’ online activity for red flags.
To learn more about our IDP solution - Dociphi's capabilities, visit www.dociphi.com or reach out to our experts.
