February 2, 2018
The insurance industry is constantly changing to accommodate complicated new regulations and a changing competitive landscape. As data-driven insights become increasingly precise and personal, insurance companies are able to offer more customized products to consumers with greater efficiency. That efficiency, however, is contingent on critical components: data quality, organization, and management. Additionally, increasingly available diversity of data coupled with a rapid pace of advancements in the ways to organize and analyze it, allow insurers to discover opportunities and tune existing propositions.
Although there are more technological innovations available than ever before to minimize risk and maximize profitability, manual processes and paper still permeate the industry’s business practices. Unstructured documents such as Word, faxes, PDFs, and spreadsheets are widely used as key inputs and systems for core business activities.
Some of the biggest challenges organizations face when it comes to unstructured data include:
Managing and extracting value from the influx of unstructured data
Processing these huge volumes of data as quickly as possible
Finding new and innovative technologies within their industry
Even with their ease of development and deployment, managing vast amounts of data without error or consequence is very difficult with basic tools (like spreadsheets) because they are a modeling and reporting tool, not a business system. Narrative-based documents are helpful for client-facing input processes but they have proven challenging to date to get machine-scale access to the data locked inside of them.
Most companies underestimate their reliance on using these tools to run their insurance programs, appreciate the operational risks of doing so or see the clear business case of abandoning the status quo. If something isn’t clearly broken, why change? The reality is that the current approach is functional but at a tipping point.
The insurance industry has made investments over the last few years in business processing re-engineering and implemented Business Process Management (BPM) solutions. As a result, legacy/single-purpose systems are connected, but the solutions still fall short of providing an end-to-end view and are not yet performing straight-through processing (STP).
Manual work and paper persist and we have to step back and ask: why are we stopping this close to the goal line? The reality is that a comprehensive solution has not yet existed until recently to tackle the challenging, costly and risky last mile.
The last mile is exactly where technology bridges the gap between lost opportunities and unfair advantages. And unfair advantages are gained with modern tech advancements, such as machine learning, artificial intelligence, and business process automation.
A particularly interesting example of a company to bridge the gap is Pendo Systems, which is currently working with leading companies in the insurance space to shatter this last mile and drive valuable business outcomes. The Pendo Platform is a powerful suite that covers such use cases as Loan Lineage, Mortgage Risk Modeling, Derisking a Risk Model, Commercial Submissions, and Loan Servicing Agreements.
Recent estimates suggest that by 2021, more than 80% of data generated by enterprises will be unstructured.
The scale of the opportunity locked inside unstructured data is not just a banking issue; insurance is flooded with unstructured documents. From commercial submissions to P&C and beyond. This industry urgently needs to solve this problem if they are to take full advantage of their Artificial Intelligence endeavors. Pendo has both the platform and the in-house expertise to make this happen, shares Bill Hartnett, the President of Hartnett Advisors.
With a lion’s share of modern data being unstructured, businesses are presented with an opportunity to drive profitable outcomes. The Pendo Platform enables insurers to dramatically improve revenue performance through data-enabled decision management designed in alignment with the organization’s business strategy. Structured data sets produced by The Pendo Platform are mineable for valuable insights regarding market demand.
Pendo System’s data management and intelligence platform transforms unstructured data into AI-ready datasets at machine scale allowing businesses to explore, discover and analyze unstructured data accumulated across wide disparity of sources. Applying real-world, customer training data, the Pendo Machine Learning Platform (PMLP) improves the accuracy of standard NLP libraries to over 95%.
Moreover, using platforms’ classifications, users can train the platform to move beyond its query language and into a continuous learning mode where the platform is able to work with business users to understand subtle changes without having to lean on clients’ IT infrastructure.
The time has come for insurance companies to embrace innovation in order to deal with the growing problem of unstructured data that threatens to place a Kudzu-like grip on progress, Frank Sentner of Sentwood Consulting, emphasizes. The good news is, in working with several major insurance companies there is now a determination to solve this problem and take full advantage of everything that machine learning and AI has to offer.
The Pendo Platform is a comprehensive tool that improves operational performance, risk management and decision support yielding structured data sets ready for BPM workflows (Appian, Pega, IBM Blueworks) and/or RPA platforms (Blue Prism, UiPath, AutomationEdge, CIGNEX Datamatics).