In an environment of endless streams of data,
Aclaimant has found a way to deliver automated
data collection and transformation, removing errors and overload
By Lori Widmer
David Wald recognized fairly quickly that the insurance industry was suffering from what he calls “dirty data.” Wald, president and co-founder of Aclaimant, saw that for all the sophistication surrounding risk and financial management processes, there were still far too many manual tasks slowing down business. Specifically, how the industry handled data.
“The process of getting claims and insurance data from various parties into a usable format was, to put it mildly, a mess,” says Wald. “It involved a staggering amount of manual data entry, endless spreadsheets, and a constant battle with inconsistent and often inaccurate information. This not only created significant administrative overhead, but it also delayed critical insights and decision-making.”
It was this particular pain point that Wald saw a solution for. He and his team “experienced firsthand the frustrations of inefficient, opaque, and manual processes in the insurance industry.” They decided to work on a solution.
The Aclaimant team talked with clients and partners to make sure they built a solution that truly worked for the end user. “We didn’t want to just create another data tool,” Wald says. “We wanted to build a comprehensive platform that would fundamentally transform the way insurance data is managed.”
Focusing on automation, validation and transparency, the team created a system, Wald says, “that is both powerful and accessible to users without a technical background.” That system: DIPDash.
According to Wald, DIPDash was built to solve insurance data friction—inefficiencies that generate workflow bottlenecks created when large volumes of data move among various platforms, slowing all data-driven processes.
DIPDash, Wald says, automates and streamlines “the entire data ingestion and management lifecycle.” The solution automatically takes in data from various sources, such as claims, TPAs, internal systems and partners, removing the need for manual input and reducing delays and errors. The system then transforms the data into a “standardized, usable format,” he explains. “Our system can handle hundreds of standard fields across major property and casualty lines of business, including claims, policies, and more.”
What happens next is DIPDash’s true value, says Wald. The platform conducts comprehensive data checks for accuracy and data quality. “This includes everything from identifying missing information and incorrect formatting to flagging inconsistencies based on predefined business rules,” he notes. “This multi-step validation process ensures that the data you’re working with is clean and reliable.”
From a risk management perspective, such clarity gives a transparent view into an organization’s data and allows companies much more control over their data, Wald says. From the DIPDash dashboard “you can see the status of data feeds, identify and resolve errors, and gain a much deeper understanding of the quality of data you’re receiving from your partners.”
What users say
Having quality data is imperative for insurance brokerage Holmes Murphy. “We rely on data to support client decision-making and risk management strategies,” says Jeffrey Austin White, chief data and analytics officer and shareholder. The company’s Client Learning and Understanding Engine (CLUE) P&C analytics platform analyzes trends and identifies key insights that they then share with clients.
“However,” White says, “the process of preparing loss data that feeds our analytics platform from carriers and third-party administrators (TPAs) has historically been a challenge.” The problem, he notes, is that each data source has its own format and structure.
“[From the DIPDash dashboard] you can see the status of data feeds, identify and resolve errors, and gain a much deeper understanding of the quality of data you’re receiving from your partners.”
—David Wald
President
Aclaimant
“However,” White says, “the process of preparing loss data that feeds our analytics platform from carriers and third-party administrators (TPAs) has historically been a challenge.” The problem, he notes, is that each data source has its own format and structure.
That meant far too much time was being spent on standardizing data and running quality and consistency checks before uploading the data to the CLUE platform. “This delay affects the speed at which we can deliver insights.”
His company began researching technologies that could help smooth the process. “Our selection process prioritized the vendor’s experience with diverse data feeds and the ability to manage varying file formats,” White says.
After considering various solutions, Holmes Murphy selected Aclaimant. The choice was “based on their domain expertise and demonstrated capabilities in the claims management space.”
And so far, so great. “By reducing manual intervention, DIPDash has helped us shorten the turnaround time from data receipt to readiness for analysis, providing improved transparency and consistency in the data preparation process,” White says.
Implementing the platform was a positive experience, he notes. “The onboarding experience for DIPDash differed significantly from our traditional approach to integrating carrier data. After understanding the data structure and financial logic, we worked closely with the vendor to configure the necessary mappings within the platform.”
“By reducing manual intervention, DIPDash has helped us shorten the turnaround time from data receipt to readiness for analysis, providing improved transparency and consistency in the data preparation process.”
—Jeffrey Austin White
Chief Data and Analytics Officer
Holmes Murphy
What users will find, he says, is an interface that is both visual and intuitive. Each action taken during the data processing, White says, is logged, offering instant transparency.
“While any new system comes with a learning curve, our team found it relatively easy to navigate. The collaboration with Aclaimant’s team was instrumental—they were responsive to questions and open to enhancements, which helped us adapt the tool more efficiently and continue optimizing its use.”
White says his biggest takeaway from the experience is the importance of “clearly articulating technical and business requirements up front. Defining data needs early allowed us to evaluate vendors more objectively and ask targeted questions.
“Another key insight was recognizing the value of a responsive support team; having an engaged, collaborative vendor relationship has proven critical to long-term success,” he adds.
For other agents and brokers looking to tame unwieldy data and get more useable information, White recommends standardizing early. “Aggregating and normalizing loss data across carriers and TPAs is complex, but foundational. Building or selecting a pipeline that streamlines this process can reduce delays and improve data quality.”
He also says it’s imperative to select a solution that integrates easily with one’s existing platforms. That reduces issues and improves the outcome.
Another thing that can impact outcomes: selecting a vendor who will collaborate. “A vendor’s technical offering is only part of the equation,” White says. “Long-term success depends on communication, responsiveness, and willingness to adapt.” Aclaimant, he says, delivered the collaboration that Holmes Murphy needed.
“While our use of DIPDash has helped us address specific pain points in our claims data process, the broader takeaway is that success in implementing a vendor solution requires a balance of technology, process, and people,” White notes.
For more information:
Aclaimant
aclaimant.com
The author
Lori Widmer is a Philadelphia-based writer and editor who specializes in insurance and risk management. BrokerTech Spotlight articles look at insurtech offerings from startups that have partnered with BrokerTech Ventures (BTV), a convening platform for brokers, carriers and wholesalers, and tech firms, and includes insight from other BTV member owners.
