b'TABLE OF CONTENTSbe thought of as the fuel. Like any engine, AImay have been made with respect to such data, and delivers more power with more and higher qualityto comply with in-bound data licenses. fuel. Thus, data is increasingly valuable. ForWhen partnering with a third party for the sharing insurers, data obtained from the beginning to theand use of data, insurers must also consider end of a policys life cycle can help to identify,security, privacy and regulatory risks. Insurers price and manage risk for new policies. Insurersusually mitigate these risk through traditional might also be able to leverage the data forcontracting methods, such as representations and customer acquisition, customer retention, orwarranties, compliance commitments, risk otherwise to sell the insights generated by AI toolsallocation provisions, and termination rights. But to insurtechs, producers, data brokers, platformsthese partnerships may subject insurers to new or other industry participants.regulatory frameworks. For example, if the In 2021, we saw insurance companies increasinglypartnership requires the insurer to transfer data licensing data and developing data-sharingfrom its internal database to a third-party data partnerships. The sources of data can take manylake, the transfer may implicate a cross-border forms, including employment agreements,transfer, potentially triggering data localization and policyholder applications, supply agreements, jointexport control restrictions. Being aware of and ventures or strategic alliances, and research andtackling these challenges was a key focus of the development agreements. This external data candata strategy in 2021 for insurers.then be pooled with internal data, commonly in a cloud-based data lake, where ML algorithms andCollaboration vs. Disruptionother AI are deployed to achieve a variety of results, including driving decisions in real-time, cloud- The headlines that have grabbed attention in recent based customer acquisition systems.years have largely focused on insurtechs disrupting incumbent insurers and competing directly for These data strategies can provide enormouscustomers, but what we saw in 2021 was an uptick in competitive benefits, but come with challenges.collaboration, rather than competition, between One such challenge is tracking the origin, ofteninsurtechs and incumbents. The pandemic called provenance, of the data in the data lake.continues to challenge all companies, not just in the Existing data that is unstructured and siloed ininsurance industry, to change how value is delivered disparate systems or departments can be hard toto their customers. In the insurance space, 2021 saw trace back to its source. Consolidating data furthermany insurtechs focus on disrupting key elements of into a searchable data structure can lead to athe insurance value chain, rather than replacing it further loss of data provenance. Creating derivedentirely, thus creating an opportunity for data and insights compounds the problem. Withoutcollaboration with incumbents. From the insurtechs knowing where data came from, it becomes difficultperspective, partnerships with insurance companies and therefore costly to assess the associated rightsallow them to acquire new customers, and both and restrictions, to determine what commitmentsparties are interested in gaining insights from data generated by these collaborations. MAYER BROWN |129'