AI IN FINANCE & INSURANCE
Due to high volume, accuracy and quantitative nature, the sector of finance and insurance can derive huge value from AI. AI and machine learning applications can help finance and insurance professionals with everything from loan approval and assets management to risk assessment.
As computing power and machine learning tools have become more accessible, the ways of how it can be used within both finance and insurance are growing exponentially. AI and ML deeply change the functioning of this sector in areas including both products, processes, and analytics, solving specific problems in customer engagement, financial management and compliance.
By adopting and applying AI in finance and insurance, managers can take data-driven management decisions by “asking” algorithms and machine learning models questions that are pertinent to their business.
AI is being used actively in the financial sector today.
Examples of AI application in Finance
- Fraud detection: Previously, when detecting fraud in the financial world, the system relied almost exclusively on a set of complex rules. Today, fraud detection systems exceed a checklist of risk factors. Instead, it can learn and calibrate to both potential or real threats of security.
- Loan underwriting: Machine learning algorithms can be trained on a vast amount of variables within consumer data and financial lending or insurance results. Assessing trends within consumer behavior with algorithms can help companies predict trends that might have an influence on loans and insurance in the future.
- Portfolio management: Algorithms can be built to calibrate financial portfolios to the preferences and risk appetite of the user, integrating real-time changes in the market.
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