Equisoft commissions LIMRA and UCT to assess AI data readiness in the life insurance industry, helping carriers evaluate and prioritize data modernization investments.

Equisoft, a leading global digital solutions provider to the financial industry, and LIMRA, in collaboration with Universal Conversion Technologies (UCT), a global leader for insurance data services, published the findings of the Assessing Data Readiness for AI in the Life Insurance Industry report, which enables insurers to assess their data foundation and implement data strategies that will deliver significant organizational results.

The report found that 78% of respondents believe data readiness is the biggest challenge in getting value from artificial intelligence (AI) and that while most companies rank as “progressive” in terms of their data perceived readiness, 46% of respondents say they aren’t ready to implement AI.

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“Data is foundational to everything a carrier does, now and in the future. But carriers aren’t necessarily data ready for AI because they haven’t yet considered a wholistic view of their data practices. Data quality and integrity are still work-in-progress,” said Mike Allee, President of UCT. “While insurers have done a good job building their data infrastructure and are making progress on aligning data strategy with business objectives, many have yet to realize AI’s vast potential because their data practices aren’t fully aligned with their AI strategy and therefore aren’t fully mature. You can’t be AI ready if you’re not also becoming data ready.”

At the heart of the report is the Global Data Readiness Benchmark, a data maturity model that analyzed carriers across six key dimensions: organizational alignment, infrastructure, sourcing and integration, quality and integrity, governance, and analytics. The model reveals the relative preparedness of life insurance carrier data for implementing AI solutions and enables carriers to assess and compare their position on the spectrum to their peers.

“High-quality data is the bedrock of any AI initiative, and without it, the outputs of AI systems will be fundamentally flawed. Bad data leads to bad AI,” said Kartik Sakthivel, Ph.D., Vice President & Chief Information Officer at LIMRA and LOMA. “It is imperative that organizations prioritize data governance, quality, and integrity to harness the full potential of AI and drive meaningful business outcomes.”

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Other key global findings from the report include:

  • Global Maturity Score: Globally, carriers scored themselves “Progressive” in AI data readiness. Australian insurers led in their assessment of data readiness maturity across all dimensions, while North America scored somewhat lower than other regions.
  • 87% of respondents are currently using AI in some operational areas like underwriting, operations and new business. Machine Learning is the most widely adopted AI technology, with rapid future growth expected for Natural Language Processing and Large Language Models.
  • Data governance is also a significant area of concern, with many reporting that governance guidelines have been created but adoption and accountability are low. This is clearly an opportunity for progress globally.
  • Carriers that have already implemented AI solutions are encountering project challenges due to unexpected issues with technology, scaling challenges or the negative impact of erroneous assumptions made during planning.

Key regional findings from the report include:

  • Australia was a top performer across all dimensions, with 38% of carriers being “Optimal” in readiness.
  • Latin America outperformed global benchmarks; 82% of carriers are “Progressive.”
  • 66% of United States life insurance carriers feel unready for AI, with organizational alignment as the strongest dimension and sourcing & integration as the weakest.
  • Canada scored the lowest regionally with infrastructure as the strongest dimension, but sourcing & integration needs improvement.

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Source – PR Newswire

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