The drumbeat message that AI is taking over in business as a key asset is unmissable, but proof can still be rather thin on the ground. Here are 10 use cases and proven examples of them in action to highlight how smart systems like AI advisors, chatbots and planning tools can help make your company more efficient.
1 AI makes insurers smarter
Risk is all about mathematical judgment, something AI is very good at handling. Insurers increasingly rely on AI to handle the level of risk automatically, providing customers with a faster quote and adapting the company thresholds or algorithms automatically to make further refinements to policies.
Zest Finance is one example (PDF) that uses AI to enables auto lenders to acquire more borrowers at lower cost and with reduced risk. It captures the benefits of machine learning-based underwriting quickly and safely while also satisfying compliance needs. According to the company, lenders using machine-learning underwriting have cut losses by 23% annually, more accurately predicted risk and reduced losses by more than 25%.
2 Reducing errors in business
Human error in a business can slow down a project, delay deals or cost it money, be it a small but significant sum to millions of dollars. Artificial Intelligence helps any business to reduce errors, especially when it comes to the finance department, and makes the it more efficient.
A new report from Oracle, based on a poll of 700 finance and operations leaders highlights how emerging technology can reduce errors by around 37%, helping 72% of businesses that use AI better understand their overall business performance. When used with tech bedfellows like blockchain and IoT in finance, businesses are growing their annual profits 80% faster.
3 Chatbots speed up business
Chatbots save the business time, as workers don’t need to be on the phone, responding to email or live chat unless the bot escalates an issue. Chatbots can typically handly 80%-90% of queries thrown at them, saving substantial amounts of time.
For example, insurer Lemonade has got the new customer onboarding process down from 10 minutes using traditional methods to 90 seconds using a bot, making customers happier to use the bots with no wait time, and improving how many new customers the company can acquire.
4 Avoiding fraud
Back in the world of finance, fraud – especially digital banking fraud – is a massive threat to that market, expected to cost $31.7 billion this year. American Express processes over $1 trillion in transactions and relies heavily on data analytics and machine learning algorithms to help with real-time fraud detection.
The US bank has developed AI tools that are far more accurate than manual if-then rules, while automated training and updated machine learning models on the ever-growing amount of data is faster than old ways of modifying fraud rules.
5 Improving the customer experience
Mezi is just one company that uses artificial intelligence (AI) and human expertise to personalize the online travel discovery and booking experience. By learning travelers’ preferences and understanding the way customers make requests using natural language, Mezi gets smarter and more efficient over time when it comes to suggesting flights, hotels and restaurant bookings.
The company was acquired by American Express to help improve the offerings that come in the many marketing emails and other messages the company sends out to cardholders, aiming to pick up an 80% response rate, which would be huge compared to the paltry responses rates to most digital marketing.
6 Chatbots improve teaching and training
Language teacher service DuoLingo is well known for digitising its time-proven training methods for learning foreign tongues. The company has invested much in AI and machine learning, using chatbots and gamification to make lessons more engaging, tailoring them to each individual user automatically.
To avoid the bots becoming repetitive or sounding boring, DuoLingo developed a statistical model called “half-life regression” that inspects the error patterns of millions of lessons to predict the half-life, or how long people remember a particular word, helping to give user engagement a 12% boost. Similarly, another new feature, Tinycards employs smart algorithms (PDF) to adapt to each person’s progress and keep them from forgetting newly-learned concepts.
7 Improved customer loyalty for travel and hospitality
The travel industry is already packed with successful bots, and recent McKinzie figures show that travel companies and airlines, in particular, are 23 times more likely to gain a customer acquisition, are 6x better at customer retention, and have a 19x larger likelihood of profitability if they use robust data strategies.
Bots and machine learning tools can help efficiently reserve and sell capacity, speed up procedures and customer interactions and create personalised choices for guests. Across these high-volume businesses, bots with personality can provide that personal touch, even as they help speed customers through bookings with upselling or gaining good reviews (or avoiding bad ones) all playing a natural part of in the conversation.
[…] chatbots are usually used to improve operational efficiency and ensure there is task automation. Chatbots in the finance industry prove to be an essential asset in reducing customer inconveniences and enhancing customer […]
[…] are plenty of pieces on how businesses can benefit from AI, from chatbots to analytics tools across insurers, consumer, FMCG and other markets. They can also […]
To leave a reply, please join the community: