Mergers and acquisitions (M&A) amongst insurance agencies are common. In 2022, there were almost 600 such transactions. With these transactions come all sorts of challenges — one of them is merging and cleaning the data in the acquired agencies’ systems before converting this data into the acquiring agency’s solution stack. To take on this challenge, agencies need a solution that will automate the process so that data cleansing is done as accurately and in as short a time as possible after the transaction.
The AMSs that an agency invests in are only as powerful and useful as the data that is fed into those systems. Agencies that have merged usually take the approach of integrating their systems into a single AMS to make client, contact, and policy data available for the entire agency to use. However, the quality of the data often only comes as an afterthought, and cleaning it is usually done manually by checking each policy and entry one by one.
The problem with poor quality, or dirty data is that sharing it between multiple systems usually pollutes all the systems involved. Without a quality check first, the acquiring agency has no way of assessing the data from another agency's AMS before it enters its own system, risking its data quality and reliability. If dirty data still exists, the agency cannot get the full return on its investment and agents will find discrepancies which will negatively affect productivity and efficiency. While reviewing information manually is common for many agencies, this process lends itself to human error as manual processes often only fuel the creation of more dirty data.
There are different levels of data in an agency AMS. At the first level, the dirty data can be trivial, such as extra spaces in a field. There can also be more detrimental discrepancies such as a misspelled name, malformed addresses, or incorrect phone numbers. The challenges can grow deeper with fundamentally inaccurate policy data.
Getting people to do data checking leads to problems because of the volume of data that is merged. Even in a small M&A, the database size can be over 60,000 records, and each record has about 100 fields. That’s over 6 million items of information that have to be checked. Larger mergers can have several 100,000’s of records. The chances of mistakes because of manual checking are significant. For an agency to run a project to manually correct data can take anywhere from eight months to two years. And that’s just historical data, the agency will not be able to check the quality of policy updates that occur.
Another area of dirty data during the process of an M&A is data that a carrier needs. If a policy is renewed based on data that has not been corrected, the carrier’s internal data quality process could have the correct data, and when the renewal is received by the carrier it will be rejected.
DataFix By Synatic offers an all-in-one data quality management solution that specializes in identifying, matching, and consolidating client, contact and policy information, deduplicating data to provide a single record of truth and prevent future duplicate accounts and errors from entering an agency's AMS.
DataFix works by extracting the data from both AMS systems, aggregating it into a single database managed by Synatic, and doing an intensive data quality check on that data. The data quality management tool automates much of the data cleansing process, and does it in a fraction of the time that manual cleaning takes. As new data comes into the agency AMS, DataFix can produce exception-based reports to maintain clean data.
DataFix streamlines and simplifies the data cleansing process allowing agents to spend less time dealing with data quality issues and more time serving clients and being productive. Critically, DataFix allows the M&A process to focus on business cohesion instead of adminstrative cleansing of data. With DataFix taking care of data management tasks, agencies can rest assured their AMS data is accurate and duplicate-free, year-round.
Clean, reliable data makes an agency more agile and responsive and cuts down wasted efforts by agents and knowledge workers. Potential losses of revenue due to costly errors and omissions can be re-couped. DataFix ensures that agencies always operate on the most precise set of data. To learn more about how you can build a solid data foundation for your agency to harness the power of data-driven insights, contact Synatic today.
