AI – The most defining technology in the financial services and insurance industries

While financial institutions are still in the early stages of adopting AI technologies, intelligent machines are expected to become the most defining for the future of institutions in the financial services and insurance industries. In fact, estimates suggest that 75% of insurance executives believe that AI will either significantly alter or completely transform the insurance industry by 2020[1]. Moreover, one-third believe that their own company will be completely transformed by AI within that timeframe.

AI is expected to redefine the way financial institutions gain information from and interact with their customers, with the benefits of embedding AI into user interfaces being better data analysis and insight. A range of institutions are already either experimenting or have implemented AI/ML capabilities[2] into various processes, with benefits encompassing improvement of straight-through reconciliation (STR) of incoming payments, higher conversions from service recommendation engine, better understanding of customer behavior and preferences, large-scale automation, etc.

Among the financial institutions, Goldman Sachs is one of the most vivid examples of an institutions embracing the potential of AI. Goldman Sachs brings significant automation into areas of trading like currencies and futures using complex trading algorithms, some with machine learning capabilities. MIT Review[3] reports that the number of US cash equities trading desk at Goldman Sachs’s New York headquarters employees went from 600 in 2000 to just two equity traders and automated trading programs supported by 200 computer engineers doing the rest of work.

HDFC, ICICI, BofA, Charles Schwab, and JPMorgan are also among the institutions applying AI/ML across a variety of use cases[4].

The insurance industry has its own examples. Allianz, MetLife, Transamerica, QBE Insurance Group, XL Catlin, and Aetna have explored various applications of AI, and some of them have reported important results.

MetLife, for example, has reported that Shift Technology, an AI startup based in France, helped a European coalition of insurers to analyze 13 million claims. The technology identified 3,000 new cases of potential fraud[5], including a large, organized crime scheme that impacted nearly all the coalition’s members. The scam had siphoned millions of Euros from the group’s insurance company members over the span of many years, according to a Shift Technology case study.

There is no shortage in examples of how intelligent machines are used to address critical areas of the financial services and insurance industries, but all of them rest on a single defining foundation – data.

Structured data is the foundation of successful AI adoption

While adoption of machine learning and artificial intelligence is critical for success in the era of rapid digital transformation, it’s even more important how organizations structure data[6] to make it usable for driving insights.

Financial services and insurance industries are

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