As insurers are increasingly turning to technologies like AI, machine learning, and cloud-based solutions to streamline processes, detect fraud, and enhance customer satisfaction, data integrity is crucial to leverage these technologies effectively. As Jean Sullivan, VP of Insurance at Precisely, states in her interview with InsurTech Digital, “with the ongoing implementation of technology across the sector, it is essential for insurers to have data integrity, in other words, trusted data that is accurate, consistent, and contextual”.
Yet despite this being known, insurers are facing challenges with data existing in various formats and silos, hindering collaboration. However, one company is building a platform specifically to address this issue - and that company is Synatic.
Overview:
Founded in 2018 by Martin Nuade, Synatic is a modern data automation platform that combines iPaaS, Data Warehousing, ETL, and API Management into a simple yet powerful tool. Their platform allows for seamless integration and easy use for businesses to 1) connect disparate data sets, 2) modernize legacy systems, and 3) automate operational processes in order to improve business efficiency
Solutions:
One of the things Synatic has done well is tailoring their solutions to the pain points that most insurance brokerages and MGAs deal with from a data quality standpoint. Below are some of the problems they are solving:
Transform your AMS data quality with Synatic’s DataFix Solution. As their ETL solution, DataFix streamlines cleansing, consolidate client info and integrate clean data back into your system
Automates policy downloads and converts data into the needed format. Integrates data, catches errors, and reduces suspense entries for reconciliation
Simplify commission management with AutoDB Commission. Automate calculations and statement access, and integrate with your AMS or financial system
Synatic’s data warehouse centralizes the data, enriches it for automation, and generates custom reports to improve business metrics and trends
Automates data to help insurance agents identify under-insured accounts, secure new leads and offer new products
Integrations:
Since inception in 2018, Synatic has built a robust inventory of off the shelf integrations with leading AMS and CRM platforms that are commonly used at brokerages and MGAs. With integrations with Salesforce, Vertafore, and Applied, it’s clear that Synatic understand and know the systems that their customers use, specifically in the P&C insurance space (as Applied and Vertaforce are the leading AMS providers in P&C). These integrations are why Synatic view themselves as a iPaaS provider. See below for the full list of integrations they’ve created:
Conclusion:
By creating a hybrid iPaaS/ETL tool specific for handling insurance data, I believe Synatic has built a very useful platform for insurers to manage the data they intake. A couple of areas I think they’ve built value-add solutions:
1) Being the ETL solution for keeping AMS data clean and accurate to be ingested into various of different platforms for accurate reporting, commission tracking, and financial reconciliation
2) Providing an off the shelf solution for commission calculation based on pre-built integrations to carrier websites and agents commission statements. With this solution, tracking and calculating commissions for producers will be significantly expedited and more accurate
3) The large ecosystem of pre-built integrations with leading AMS, ERP, and CRM systems in the insurance space. This is a huge advantage from a product standpoint as they are able to provide their solutions easier, as many of their customers use these systems
4) Continued partnership through various partnership techniques - OEM Partnership, Reseller Partnership, and Referral Partnership. This go to market strategy is an interesting way to get their platform into the market, and I think will allow them to grow organically very productively.
Overall, Synatic has built an interesting product, and I think many insurance companies could use their product to optimize the usage of their data.