Finance & Insurance – Retail & Marketing

Earlier this year McKinsey wrote “Two years ago people were asking, What is AI? A year ago, people wanted to learn how to trial minimum viable AI-fueled products. This year, the question is focused on how to get more value from AI”. So where to start if you want to achieve clear and measurable value with AI? In this blog series, we will address eight industries and their specific use cases, giving you insights into how implementing AI can increase business value.

AI can bring value across various industries, but it is only when you put AI into production, that it will add clear and measurable value. However, when having the capacity to scale AI to every corner of an organization, you will be ensured competitiveness for the next decade. Does that sound appealing? Then take a look at how our industry-specific use cases can help you get started on your AI journey.

In a series of posts over the next four weeks, we will address the eight industries listed below, providing you use cases, that can inspire you to take your first step towards actual AI implementation – closing the gap between AI ambitions and real value from AI.

  1. Finance & Insurance
  2. Retail & Marketing
  3. Transport & Logistics
  4. Pharma & Biotech
  5. Utilities
  6. Legal & Accounting
  7. Public
  8. Manufacturing

This week we will dive into the industries Finance & Insurance and Retail & Marketing.

Industry #1

Finance & Insurance

The use of AI in Finance & Insurance Industries

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 asset 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.

Areas of AI application in Finance & Insurance

  • 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.

Industry #2

Retail & Marketing

The use of AI in Retail & Marketing Industries

Narrow net margins and a highly competitive environment constitutes the industry of retail and marketing. Huge amounts of data, especially within high-frequency online retail, makes this an ideal landscape for AI. Intelligent planning and operating systems can help companies to enhance their capabilities and small efficiency gains can translate into big net income results and competitive advantages.

The value of AI in retail is magnified, however, it will not replace employees. It will alter their role and augment human capabilities. Implementing AI and ML systems can assist merchandise planners by taking over planning tasks and similar autonomous tasks across the supply chain and store operations. By processing huge amounts of data, AI systems can be developed to help sharpen promotions, prices, inventory allocations and improve customer engagement. This leaves employees with more time for useful and engaging tasks that require more creative thinking, making the best use of human skills and expertise.

Areas of AI application in Retail & Marketing

  • Customer analytics from acquisition to loyalty programs employs AI to a very large extent in order to optimize marketing actions while cutting down costs.
  • Personalizing customer experience through digitalization and customer behavior analysis is slowly becoming the norm for online retailers.
  • Predicting supply and demand is one of the applications heavily leveraging AI technologies as it impacts many parts of the businesses and helps reduce cost as well as manual labor.

The areas where various industries can benefit from AI are ever expanding. One way to get started with AI is to look into specific use cases, enlightening you on how AI can benefit your organization and enhance business value.

Stay tuned for next week where we dive into AI in the industries of Transport & Logistics and Pharma & Biotech.

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