CBHS connects better with members and improves claim leakage and error recovery with AI-embedded data platform

CBHS Health Fund Limited is a not-for-profit private health insurance provider founded in 1951 for current and former Commonwealth Bank employees, contractors and their families. In 2016, it launched CBHS Corporate, an arm of the company that’s open to all public and international workers and students.

With CBHS Group’s expansion, a range of new opportunities emerged to revamp its operations. One of the most exciting was to transform how the company drew insights from data. This enabled it to improve claims processes, better connect to members by personalising its services, and gain better visibility of its member base and the broader health insurance market.

CBHS developed its new cloud-hosted Business Intelligence Group (BIG) Analytics platform to scale its operations and automate a range of processes to improve services and reduce costs.

“Before the new platform, we were using multiple reporting tools from different siloed platforms, Excel files in some cases, and we couldn’t fully consolidate all that information into a single platform.

“Our data governance program required improvement as there were some levels of discrepancy between data across multiple platforms, that required review/validation at each reporting cycle. Also, there was no unified environment and tools that allowed us to properly govern the data we had gathered, and there were limits to our reporting mechanisms.”

The BIG Analytics platform provides CBHS sales, claims, finance, marketing, and clinical teams with insights that allow them to optimise their processes, reduce the risk of non-compliance, and consequently improve their key performance indicators.

Improved data governance and visibility

One of the most important features of the new platform is data governance. Private health insurance providers are heavily regulated by bodies like the Australian Prudential Regulation Authority (APRA) to protect member confidentiality.

The Data lake capability allows CBHS to store all types of data into a single storage unit and apply data governance methods into that unified environment. This significantly improves the analysis and reported on curated data.

The BIG Analytics platform gives CBHS the governance capability, along with unprecedented visibility over its data and data quality.

Powerful analytics capabilities

Microsoft Power BI provides a single source of truth for all CBHS’s reporting, which helps to avoid duplication and potential inconsistencies across multiple platforms.

Using the developed analytics products in Power BI, CBHS can now provide a wide range of insights from the data to relevant teams. For example, the marketing team have a better understanding on their digital campaign success and can track their advertising spend in line with budgets on a daily basis. Moreover, the sales team have wider visibility over their sales channels and the promotion impact on their sales performance. The developed analytics products also allow clinical teams to optimise pre- and post-hospital treatment programs.

Automating claim error and leakage detection with AI

CBHS has been able to automate some segments of the claims monitoring process. The Payment Integrity (PI) team in partnership with the BIG team deployed Azure Synapse Analytics’ features that analyse claims data to flag incorrectly billed claims. The technology enables the PI team to achieve their targets of improving incorrect billed claim recovery by 30 per cent compared to the previous year.

Previously, claims administrators would have to manually look through Excel files with thousands of claims to flag incorrectly billed. This was a time-consuming task and one that carried a risk of error. Now, the BIG Analytics platform automatically flags suspicious claims so that administrators are notified to set the claims review process in motion.

Exciting possibilities ahead

The BIG Analytics team launched a chatbot in 2020 that connects members to CBHS at any time of the day to find the information that they need. As members embrace digital interactions and demand more personalised advice, CBHS is looking forward to assessing and embracing AI solutions like Generative Pretrained Transformers (GPT) or Large Language Models (LLM) models to improve how it provides effective online support.

CBHS is also looking to embed AI and machine learning in new ways to improve their payment integrity processes, as well as exploring robotic process automation to reduce processing costs and improve efficiency.

The platform can also be used to streamline member services by automatically reviewing member activity against their policy criteria and flagging potential improvements. Staff will then be notified to contact members to discuss their membership.  This enables them to focus solely on member interactions rather than also having to review and manually flag improvements themselves.

“We wanted to build a solution that would grow alongside us as we anticipate rapid expansion and an evolving tech space over the next few years. To do this, we need a partner that can meet our strategic vision and that shares our appetite for innovation every step of the way,” explains Tafavogh. “Microsoft is that partner.”

For other organisations on a data analytics journey, Tafavogh’s advice is simple: “To deliver a meaningful service on time and accurately, you need to be in an environment that can grow with your business. Cloud is the solution that provides the scalability.”