“Machine intelligence is the last invention that humanity will ever need to make.”
Artificial intelligence is a reality today and it is impacting our lives faster than we can imagine. It is already present everywhere, from Siri in your phone to the Netflix recommendations that you receive on your smart TV. The revolution brought by Artificial intelligence has been the biggest in some time. There is no denying that it has already become a crucial and integral part of our life.
Artificial intelligence is the blend of three advanced technologies – machine learning, natural language processing and cognitive computing. The concept of Artificial Intelligence is to simulate the intelligence of humans into artificial machines with the help of sophisticated machine learning and natural language processing algorithms. The prime motive for the idea of transferring the intelligence from humans to machines is to overcome the very barrier of human intelligence: scalability. There’s always a limit to the speed with which humans can perform the given tasks. Artificial intelligence looks to overcome this very challenge with human intelligence by transferring the human intelligence to cognitive machines with supreme computational capabilities.
Let’s take two examples to better understand the concept of artificial intelligence:
- Consider a scenario where the task is to map inputs to outputs following a well-defined logical path. Let’s take an example of producing the product of two given numbers. Today, any computer can beat any human in this task in terms of speed and accuracy. This is the class of problems for which the software revolution took place in the late 19th century and is an integral part of everyone’s life.
- Now let’s take another scenario in which the mapping of inputs to outputs is not very well defined. Consider an example where the task is to identify whether an image has a dog or a cat in it. It’s safe to say that most of the humans will easily outperform computers in this task.
These are scenarios where artificial intelligence is focusing on, to simulate the mapping of inputs to outputs as it happens in a human brain which makes very difficult tasks for computers like image recognition, sarcasm detection, voice recognition, etc. seamlessly easy for even an 8-year old kid.
Top 10 companies using AI
There are many use cases for AI in a variety of industries. Bizofit, a platform that intelligently connects enterprises with appropriate service providers, has compiled the following list of top 10 AI companies.
One of the leading artificial intelligence companies, AIBrain builds AI solutions for smartphones devices primarily. Their key area of expertise is robotics and digital personal assistant.
Anki is another company in AI domain which has received funding from over $157.5 million from the likes of J.P. Morgan and other Ventures. The flagship robot of Anki – Cozmo – is one of the most emotionally intelligent robot while dealing with customers.
Banjo has raised over $100 million worth of funding till now.They use the strong social media analytics from multiple social media platforms to identify the events taking place around the globe.
iCarbonX is an artificial intelligence based startup in health care domain. They provide individualized health analysis and prediction of health index through the use of advanced data mining and machine analysis technologies. iCarbonX is valued at more than $1 billion USD.
Jibo is the first robot in the world made to help families with their daily tasks. Also, it learns about the behavior and personality of family as it interacts with them.
- Next IT
Next IT applies AI in healthcare and finance industries with focus mainly on natural language processing, chatbots and machine learning.
Being one of the most popular iOS app, Prisma brought a revolution in mobile app industry with the use of deep learning algorithms to recreate images as if they were painted.
ReSnap using AI and deep learning to take a large number of images from the user and create beautiful photo books out of these images. AI helps in selecting images and chooses best for the photobook.
ViSenze is revolutionizing the e-commerce market by recommending visually similar products out of the several millions products. They use deep learning and computer vision. They recently raised $10.5 million for developing their AI technologies.
X.ai’s virtual assistant is helping busy people schedule meetings without any human intervention. As soon as you copy a mail to Amy, it makes sure that with the use of natural language processing and machine learning, it identifies the most suitable time and place for your meeting.
AI & its relevance to Banking
In recent years, if Artificial Intelligence has impacted one industry more than any other, it’s the Banking industry. For organizations working in the banking industry, it has become increasingly crucial to keep up with competition, and increase their standing as an innovative company. The following graphic shows reasons for its widespread adoption in Banking & Financial Services.
Artificial intelligence has several applications in the banking industry.
Here are five key applications of artificial intelligence in the Banking industry that will revolutionize the industry in the next 5 years.
- AML Pattern Detection
Anti-money laundering (AML) refers to a set of procedures, laws or regulations designed to stop the practice of generating income through illegal actions. In most cases, money launderers hide their actions through a series of steps that make it look like money that came from illegal or unethical sources are earned legitimately.
Most of the major banks across the globe are shifting from rule based software systems to artificial intelligence based systems which are more robust and intelligent to the anti-money laundering patterns. Over the coming years, these systems are only set to become more and more accurate and fast with the continuous innovations and improvements in the field of artificial intelligence.
- Chat bots
Chat bots are artificial intelligence based automated chat systems which simulate human chats without any human interventions. They work by identifying the context and emotions in the text chat by the human end user and respond to them with the most appropriate reply. With time, these chat bots collect massive amount of data for the behaviour and habits of the user and learns the behaviour of user which helps to adapts to the needs and moods of the end user.
Chat bots are already being extensively used in the banking industry to revolutionize the customer relationship management at personal level. Bank of America plans to provide customers with a virtual assistant named “Erica” who will use artificial intelligence to make suggestions over mobile phones for improving their financial affairs. Allo, released by Google is another generic realization of chat bots.
- Algorithmic trading
Plenty of Hedge funds across the globe are using high end systems to deploy artificial intelligence models which learn by taking input from several sources of variation in financial markets and sentiments about the entity to make investment decisions on the fly. Reports claim that more than 70% of the trading today is actually carried out by automated artificial intelligence systems. Most of these hedge funds follow different strategies for making high frequency trades (HFTs) as soon as they identify a trading opportunity based on the inputs.
A few hedge funds active in AI space are: Two Sigma, PDT Partners, DE Shaw, Winton Capital Management, Ketchum Trading, LLC, Citadel, Voleon, Vatic Labs, Cubist, Point72, Man AHL.
- Fraud detection
Fraud detection is one of the fields which has received massive boost in providing accurate and superior results with the intervention of artificial intelligence. It’s one of the key areas in banking sector where artificial intelligence systems have excelled the most. Starting from the early example of successful implementation of data analysis techniques in the banking industry is the FICO Falcon fraud assessment system, which is based on a neural network shell to deployment of sophisticated deep learning based artificial intelligence systems today, fraud detection has come a long way and is expected to further grow in coming years.
- Customer recommendations
Recommendation engines are a key contribution of artificial intelligence in banking sector. It is based on using the data from the past about users and/ or various offerings from a bank like credit card plans, investment strategies, funds, etc. to make the most appropriate recommendation to the user based on their preferences and the users’ history. Recommendation engines have been very successful and a key component in revenue growth accomplished by major banks in recent times.
With Big Data and faster computations, machines coupled with accurate artificial intelligence algorithms are set to play a major role in how recommendations are made in banking sector. For further reading on recommendation engines, you can refer to the complete guide of how recommendation engines work.
How small banks can make the most of AI?
In several of our conversations with executives of smaller banks like Community banks in the US, it became very apparent that they were seeking a differentiator in their intense competition with the larger banks. Big banks are using cutting edge artificial intelligence techniques by using in-house teams of Data Scientists and Quants for risk assessment, financial analysis, portfolio management, credit approval process, KYC & anti-money laundering systems. On the other hand, small banks can use AI for achieving operational efficiency and better customer interactions.
Some of the several applications of AI that smaller banks can benefit from are:
- Better Customer interaction using chatbots
- Accurate recommendations using Recommendation engines
- Fraud detection using machine learning algorithms
In conclusion, it is evident that AI is here to stay, and is impacting a large number of industries, Banking is an early adopter of this trend. This trend is likely to grow exponentially in the future. Companies that embrace this trend are likely to be winners over the next 10 years.
About the Author
Devendra Mangani, Sr. Consultant, Bizofit
Having 12+ years of experience in strategy, business planning, B2B IT sales and raising capital for startups and companies in IT sector. Experience in managing multiple stakeholders and worked with global teams in previous companies including investment bank. He is guest faculty at management colleges and does workshops on design thinking. Devendra brings in strong understanding of research reports and consulting for building research capabilities of Bizofit. He is an IIT Bombay graduate and MBA from Queen’s University in Canada.You can also read this article on Analytics Vidhya's Android APP