AI in Business: 17 Examples from Insurance, Healthcare, and Banking Companies
Wondering how healthcare, insurance, and banking companies are implementing AI? Check out these real-world examples, including the ones from our clients.
AI can streamline different processes and tasks in business. We’ve been helping companies in insurance, healthcare, and banking discover the possibilities of AI.
Using the real-world examples below, we’ll show you how artificial intelligence in business can improve operations in multiple sectors. We’ll also feature a few companies we’ve helped implement our AI solutions, so read on and see how your company can benefit.
17 AI Examples in Business
AI Examples in Business: Insurance
1. MetLife - Fraud Detection
AI can analyze large amounts of data to identify patterns that might indicate fraudulent activity. Because it can analyze much more data quickly than humans, AI takes a proactive approach that helps detect fraud early, minimizing the risk of fraud.
MetLife deploys advanced AI systems that sift through data to identify potential fraudulent activities. Detecting fraudulent activity early helps MetLife reduce costs associated with fraudulent claims.
Besides fraud detection, MetLife utilizes AI to streamline customer service operations. Using virtual assistants and chatbots, they provide instant responses to their customers, manage policy updates, and assist with the claim process.
MetLife also leads insurance with predictive analytics, automated internal operations, and better customer experience. As a result, this company helps reduce costs, complete administrative tasks faster, and improve relations with its customers.
2. Swiss Re - Advanced Data Analytics
Artificial intelligence can analyze large amounts of data from various sources, which helps improve decision-making and can make accurate predictions.
Swiss Re uses AI to predict natural disasters and help manage the outcomes. Using machine learning, Swiss Re can simulate various disaster scenarios to understand the potential impact. This gives them a chance to prepare themselves and their clients with risk mitigation strategies.
Besides managing the risk of natural disasters, Swiss Re also uses AI to conduct health risk assessments. AI can analyze more medical records, genetic data, and lifestyle information to predict an individual’s health risks. Using this information, Swiss Re designs personalized insurance policies with appropriate premiums.
We've discussed individualized assessment of a patient’s genetics and lifestyle using AI on our podcast with Jayodita Sanghvi, senior director of data science at Included Health. Here's what she had to say:
"AI has the power to enable us to deeply understand each individual, what their clinical needs are, what their demographic needs are, if they have any care gaps."
Using AI for advanced data analytics, Swiss Re offers more personalized and competitive reinsurance products. This company also improves customer engagement with virtual chatbots, automates underwriting, and prevents fraudulent activities.
3. AXA - Data Analysis
AXA employs AI to gain deeper insights into customer behavior and preferences. With AI, they can understand customers’ needs from multiple touchpoints. From there, AXA tailors health insurance plans to meet the specific needs of its customers.
AI also helps analyze market trends, economic data, and financial indicators, providing AXA with a better insight into investment decisions and strategies.
AXA also automates claims processing by analyzing claim types, supporting documents, and historical claims data. This speeds up the processing time, minimizes errors, and ensures a more transparent claim processing for customers.
Artificial intelligence also helps AXA with risk assessment, underwriting, and managing customer relationships.
4. Zurich Insurance - Underwriting
Zurich Insurance deploys AI to analyze big data, such as historical claims, weather patterns, and economic indicators. The analysis allows them to make precise risk assessments and provide better pricing models.
With AI, Zurich Insurance can identify patterns that aren’t easily discoverable with traditional methods. This competitive advantage helps them minimize underwriting errors and predict risk much more accurately.
Zurich Insurance also speeds up claims processing while minimizing errors, detecting potential fraud, and ensuring faster payout to policyholders.
5. American Family Insurance - Risk Management
American Family Insurance improves risk management by streamlining operations and processes, leading to better accuracy and reduced error.
Thanks to natural language processing, artificial intelligence can perform analysis that helps identify potential risks and suggest preventive measures. Companies like American Family Insurance reduce the likelihood of losses by deploying generative AI as a proactive risk management tool.
American Family Insurance also improves customer service by utilizing AI chatbots to provide 24/7 support, make more informed underwriting decisions, and expedite the claims lifecycle.
Such use of artificial intelligence in business makes American Family Insurance an excellent example of a forward-thinking leader in the insurance industry.
6. Nationwide - Claims Processing
Nationwide utilizes image recognition and machine learning to expedite claims processing. By automating repetitive tasks, Nationwide enhances operational efficiency, allocates resources more efficiently, and delivers faster to policyholders.
Nationwide also predicts and mitigates potential risks by assessing factors like demographic trends and economic indicators. This helps them adjust their offerings and pricing models accordingly.
Artificial intelligence also helps optimize risk exposure and ensure financial stability. Taking things a step further, Nationwide uses deep learning capabilities to decipher customer sentiments across channels (such as social media). This helps the company gain valuable insights into preferences and expectations. Using this information, Nationwide tailors service offerings to its customers.
AI Examples in Business: Banking
1. Direct Mortgage - Mortgage Processing
Direct Mortgage wanted to address their challenging, primarily manual loan application workflow. Using our AI Solutions, they now process 200+ types of documents 20x faster than before at a reduced cost of 80%.
Using two AI Agents, Direct Mortgage automatically extracts customer data and classifies a range of documents (including bank statements, pay stubs, and many others). What usually took hours to manually extract, review, and verify before proceeding to the next step is now automated.
This way, the employees spend less time on time-consuming and repetitive tasks. Instead, they focus on more important tasks that lead to faster decision-making and maximized accuracy.
2. Bank of America - Personalized Financial Recommendations
AI tools are applicable in many different areas of banking. Bank of America improves a wide range of operations with artificial intelligence, with a primary focus on personalized client support.
Analyzing data using AI helps identify patterns and trends, which allows the Bank of America to make informed decisions in risk assessment and lending. It also helps this company learn about its customers by analyzing transaction history, spending patterns, investment preferences, and life events.
Using individual financial behavior information, Bank of America offers targeted advice on savings strategies, investment opportunities, debt management, and retirement planning. This level of personalized customer service allows clients to make much more informed decisions.
This bank can also identify relevant products and services that align with each customer’s financial goals. This helps the company recommend suitable credit card and investment options and advise on mortgage referencing in a personalized and faster manner.
Using AI, Goldman Sachs can predict market trends and execute trades at optimal times, helping it maximize profit at reduced risk. Through machine learning models, Goldman Sachs gains insight into complex market behaviors, allowing it to adapt to new market conditions faster than competitors who rely on traditional methods.
With sophisticated assessment models in place, this company can analyze historical data in real time. Using such information, potential risks are identified, and the company can take preemptive actions even before the risk is materialized.
Goldman Sachs also deploys chatbots and automated advisors. These AI-driven tools provide instant yet personalized advice. By speeding up the service and eliminating the need for phone calls, customers are more satisfied.
4. Barclays - Fraud Detection & Risk Management
Artificial intelligence can increase transaction security and improve the overall stability of financial operations by analyzing data and comparing patterns in real-time. Barclays uses AI extensively to prevent fraud and manage risk.
Barclaysanalyzes transactional patterns across multiple channels by leveraging machine learning algorithms. Being able to do it in real-time, anomalies that indicate fraudulent activity immediately flag unusual transaction locations, high-risk merchants, and atypical spending patterns.
When compared with customers’ historical data, unusual behavior patterns can stop fraud in real-time thanks to immediate alerts and automated actions.
Artificial intelligence can also model risk scenarios and predict the impact on the bank’s portfolio. Analyzing borrower’s data helps predict creditworthiness, which is considered in the decision-making process for loan approvals. AI improves accuracy and minimizes risk, allowing Barclays to make much better decisions compared to traditional risk management methods.
5. Wells Fargo - Customer Relationship Management
Wells Fargo uses AI to analyze personal preferences and interaction patterns. AI can then deliver highly customized financial advice and product recommendations, resulting in a much more informed customer.
For example, Wells Fargo’s AI systems identify specific life events such as buying a house or similar customer activity. With such insights, the bank proactively offers relevant products like mortgage options. These options are tailored to individual customer needs. Such an approach results in a much more positive customer experience, but it’s also a way to gain more business.
Analytics driven by artificial intelligence also segment customers accurately, helping the bank craft a marketing strategy that likely resonates. The results include improved engagement and conversion rates.
6. Citigroup - Wealth Management
Citigroup manages clients' wealth with AI that helps with market analysis and insights, operational efficiency, risk management, client acquisition, and personalized client service.
Automating routine tasks like data entry, transaction processing, and report generation helps minimize errors and frees up human advisors. These advisors have more time to focus on value-added activities like client relationship management.
AI also analyzes market data to identify trends, generate insights, and forecast market movements. Citigroup uses such information to provide informed advice and make better investment decisions for its clients.
Assessing risk in real-time by analyzing client portfolios helps manage risk effectively while complying with regulatory requirements. Citigroup also has patterns in place to identify potential new clients and predict client needs.
AI Examples in Business: Healthcare
1. UnitedHealth Group - Administrative Tasks
Artificial intelligence can easily handle repetitive administrative tasks, which helps free up human resources. UnitedHealth Group uses AI to handle customer inquiries, update provider directories, and summarize patient and customer interactions.
Routine customer inquiries are automated with responses to common questions and information, which traditionally require human intervention. UnitedHealth Group can respond faster while having resources available to focus on more complex tasks.
UnitedHealth also reduces operational costs by streamlining the onboarding process for new clients. Their AI system can handle thousands of new clients efficiently because it automatically updates entries, verifies information, and corrects inaccuracies.
UnitedHealth Group is one of the best AI in business examples where they streamline business processes that require less human intervention and improve communication between departments.
2. McKesson Corporation - Predictive Analytics
McKesson Corporation relies on AI to gain analytics to help predict patient outcomes, manage chronic disease, and optimize treatment plans. Its AI system analyzes historical health data to identify patterns and predict risks.
Such information helps the company make more informed decisions while providing proactive care. As a result, customers get much faster and more proactive care, whereas McKesson Corporation has a much more efficient workflow that improves customer satisfaction.
McKesson Corporation also optimizes the supply chain and improves data security. AI helps track inventory levels, demand forecasts, shipping tasks, and logistics, which helps maximize distribution.
3. Cardinal Health - Drug Discovery and Development
Cardinal Health’s AI helps analyze vast datasets to identify potential drug candidates and predict how they’ll perform. Such support in drug discovery speeds up the development process and improves the chance of success in clinical trials.
AI also helps improve clinical decisions by analyzing large volumes of medical data. AI tools can detect patterns that aren’t apparent using traditional methods. Early diagnosis and personalized treatment plans are some of the ways of leveraging AI.
4. AbbVie - Clinical Trials
AbbVie uses AI to analyze datasets from preclinical and clinical trials to identify promising compounds, which helps them further optimize their portfolio. By analyzing biological data faster than using traditional methods, AbbVie accelerates the discovery of novel therapeutic targets.
During clinical trials, artificial intelligence helps analyze electronic health records and patient data to find suitable candidates. This speeds up the process and ensures a better match between patients and studies.
AI can even assist in trial design and optimization through simulations, improving protocol design and dosages, and identifying potential side effects. By investing in AI, AbbVie has much more efficient and cost-effective trials.
5. Regeneron Pharmaceuticals - Drug Repurposing and Literature Mining
Analysis of vast datasets of drug properties, biological interactions, and disease pathways, Regeneron Pharmaceuticals can identify existing drugs that can be repurposed for new indications.
AI helps accelerate the development of treatments for new diseases and identifies potential candidates for repurposing. Regeneron Pharmaceuticals utilizes deep learning to extract valuable insights from scientific literature, patents, and clinical trial reports.
Such an approach helps the company stay up to date on the latest discoveries. This leads to the identification of potential collaborators and can even serve further investigations.
Turn Your Company Into an Example Using AI
Do you like how these companies use artificial intelligence effectively? Would you like to implement artificial intelligence in your business? If you’re looking for a quality AI to implement in your workflow, please schedule a 30-minute call with our experts. We can discuss your needs and the best ways to integrate AI into your company. You’ll also get a chance to see how our AI Agents work live, so book a call today!
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