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APAC Banks Lag Behind In AI Implementation: FICO

AI Implementation

In a recent survey, Silicon Valley analytic software firm FICO found that 91 percent of banks in Asia Pacific (APAC) felt they lagged behind banks in the US and Europe when it came to implementation of AI in their operations. The remaining 9 percent indicated that they were at least on par with US and Europe counterparts, while not a single respondent felt they were ahead.

When asked about the biggest challenge in adopting AI and machine learning into existing bank operations, 42 percent indicated that it was the lack of available talent. The use of legacy systems (28 percent) came in second, followed by cost (16 percent).  

“The shortage of talent continues to be an issue worldwide as the use of AI continues to grow quickly,” said Dan McConaghy, president of FICO in Asia Pacific.“However, we continue to partner with organizations to help them through some of these growing pains and help them operationalize AI and machine learning models.”

The survey also found that more than half of APAC respondents see AI and machine learning as a means to help improve operational efficiency. Respondents ranked the areas that would receive the greatest benefit from the technology as credit decisions (68 percent), followed by fraud detection (45 percent) and then collections (35 percent).

Numerous Asia Pacific banks currently use the FICO Falcon Fraud Platform which has been powered by AI for more than twenty years and for which FICO holds over 100 patents in fraud-specific machine learning and AI.

“Falcon is a great example of how we help customers to operationalize artificial intelligence (AI), and make sense of their rapidly-growing transaction data,” said McConaghy. “The platform helps financial institutions detect and prevent fraud seamlessly, in real time. AI and machine learning models are engrained in FICOsolutions that encompass many areas of banking operations, including credit scoring and debt collections.”

FICO currently holds 192 US and foreign patents, and 95 pending patent applications, with many of these related to machine learning and artificial intelligence.

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