How AI fights against financial criminals and money launderers?

As criminal methodologies are growing more advanced, the fight against money laundering is becoming a huge challenge for all the financial institutions around the world. Therefore, it becomes necessary to put in AML (Anti-Money Laundering) measures. As AML requires to deal with a huge amount of customer data, they are turning to AI and Machine Learning, to help them identify and detect money laundering activities.

AI performs AML tasks faster than a human employee and also, through machine learning it possesses the capability to modify new threats and detect new money laundering methods. It ensures that financial institutions are able to adjust quickly to different regulatory environments.

When transaction data of a customer is incorporated into an AML program, AI and machine learning models analyze the behavior to make predictions and perceptions about that customer in the future.

How are AI and Machine Learning advantageous in fighting financial criminals and money launderers?

Customer Perceptions

AI systems enable the CDD (Customer Due Diligence) and KYC (Know Your Customer) systems, to take place at a faster rate and with greater deepness and reach. The AI-based CDD and KYC processes enable the financial institution to

Efficiently identify and collect data from a greater range of external sources which include watch lists, sanction lists, and create a factual profile of the customer.

Recognize valuable owners of customer entities by using external data faster and more efficiently.

Accumulate and reconcile customer data across internal systems to remove replication and errors and intensify the density of AML measures among customers.

Automatically enhance dubious activity reports with appropriate data from customer risk profiles or data from external sources.

Unstructured Data

There are other important steps beyond creating customer risk profiles. As a part of monitoring transactions, screening PEP, screening sanctions, and monitoring media, the AML process requires identifying and analyze the unstructured data. Every financial institution must make an effort to use the unstructured data to recognize their professional, social and political lives by inspecting a range of external sources which includes public archives, media, social networks, etc. in such circumstances, AI helps the institution to recognize those unstructured data. Once the data is collected and analyzed, AI helps the institution prioritize and categorize information to assist risk management.

Reporting Dubious Activity

AI can assist the reporting of doubtful activity by producing reports and also, by automatically filling them with accurate information. After their submission of reports to the authority, SARs goes through a process of internal reporting. AI technology can make the SAR process easy as algorithms can generate automated reports with accurate data and transmute that data into an accessible, standardized language in order to eliminate bureaucratic friction. Because of standardized language and terminology, AI increases the speed and efficiency of an institution’s AML reporting.

Noise Minimization

The AML system is complex and is a time-consuming procedure therefore it is an advantage to incorporate AI within an AML system which helps in adding speed and efficiency. But one of the major hindrances in the process is the level of noise or false positives which is the result of incomplete or inadequate data or over-sensitivity of AML steps. In such cases, AI systems play an important role by generating a significant transformative effect to the level of noise generated during the AML process. AI assists the institution to produce higher insight into customer’s transaction patterns and enables them to remove wrong and invalid alerts which makes the process costly for the institutions and inconvenient for customers. By minimizing noise, AI and machine learning tools enable AML employees to better prioritize and direct the most required money laundering alerts. By doing so AI more effectively contributes to the fight against financial crime.

Limitations of AI

In order to keep pace with the increasing risk of financial criminals and money launderers and the need to react faster to those new threats, often new AI and machine learning models are prematurely dashed into the market without proper training. This creates a huge skepticism around AI and Machine Learning technologies. Therefore, banks must remember that AI experimentation comes with diminishing returns. They should focus on performing strategic, production-ready AI micro-projects in parallel with human teams to deliver actionable insights and value.

The post AI: TECHNOLOGY TO FIGHT FINANCIAL CRIMINALS AND MONEY LAUNDERERS appeared first on Artificial Intelligence.

Here are 7 ways to earn a living with artificial intelligence, without working for a company.

Artificial intelligence is one of the most revolutionary technologies of our time and you can make money out of it. Every industry in today’s time is powered by AI as businesses are using it as a competitive tool. From chatbots for efficient customer service to using it for analytics to make predictive recommendations, artificial intelligence is leading the world forward. That makes AI an unmissable technology.

If you are in the IT industry, you must be habituated to use programming languages, work with different frameworks, build software for companies, and write various codes to escalate problems. But don’t disregard AI as an integral part of the IT field. AI and its many applications can help you earn a living and stay updated with modern tech trends. Here’s how.

1. Become an AI entrepreneur

It takes a problem-solver to become a business leader. There are so many things around us that need better solutions like global warming, excessive workloads, faster deliveries, improved emergency healthcare, etc. Basically, there’s always something to improve around us. So figure out a pain point you want to target, get a team to brainstorm ideas, define the target audience, plan a solution, pitch the idea to investors, and get going with your own AI startup and make this world a better place while earning profits.

2. Improve machine learning application in eCommerce

For good or bad, the COVID-19 pandemic has replaced the habit of shopping at physical stores with shopping online for almost everything. Because eCommerce shopping is in demand, this is the time to use machine learning and keep enhancing the experience. You can build a better recommendation engine, personalize the service, predict supply and demand faster, build improved visual search, and build a better security system. You can also create conversational interfaces and automate customer service tasks.

3. Get competitive with chatbots

Every eCommerce website has a chatbot that will pop up as soon as you open the webpage. This is because companies are tapping into the potential of chatbots to provide 24/7 customer service. That doesn’t mean you can’t contribute to this buzz. Chatbot as a virtual assistant is the next development. Because AI is the technology that allows chatbots to mimic a human while conversing, you can teach the system how to talk using NLP. There are pre-made platforms like Microsoft Bot Framework, Botkit, and Dialogflow that will make this easier.

4. Leverage your business with AI

If you run a business, you can make it more efficient with AI. You can use data from your customers and target their social media feeds to show useful products that your business offers, or make applications that will lighten your employee’s workflow. If your business has an app, there are several ways to improve it using AI. For example, you could use speech synthesis to make your app convenient for people with weak vision.

5. The trend of blogs never died

No, blogging is not dead, it just has different forms now like video blogging and audio blogging. If you are good at understanding and explaining complex tech concepts, you can start a blog to tutor budding engineers and developers. First, identify what you are good at. Then, start writing blogs on your own website or make vlogs or start a podcast. You can also create and sell online courses and even write a book. If you want to teach, there are many possibilities.

6. Develop your own app

If starting a business of your own seems like a daunting task that will bog down your mental health, solve the same pain point by developing an app. Almost every service-related app uses artificial intelligence. You can make a simple app powered by AI and monetize it by adding a premium subscription or selling ad space on it.

7. Compete and win

There are many machine learning competitions that allow programmers to earn money. Kaggle is a popular ML platform that offers prize money to winners, and Numerai is a tournament where data science professionals can compete to predict asset prices. Many other machine learning competitions allow programmers to practice before competing.

The post BE YOUR OWN BOSS & MAKE MONEY WITH ARTIFICIAL INTELLIGENCE appeared first on Artificial Intelligence.

Artificial Intelligence (AI) is poised to disrupt our world. With intelligent machines enabling high-level cognitive processes like thinking, perceiving, learning, problem-solving, and decision making, coupled with advances in data collection and aggregation, analytics, and computer processing power, AI presents opportunities to complement and supplement human intelligence and enrich the way people live and work.

AI is set to have a significant transformational impact on the industry as well as academia. The Indian Government is playing a key role in sustaining the intervention in order to tackle the challenges that AI-specific startups face in order to grow in their verticals. During the 2018-2019 budget, the Government of India has mandated NITI Aayog to establish the National Program on AI. According to the National Strategy for Artificial Intelligence, the underlying thrust is to identify the specific applications of emerging technologies with maximum social impact.

It is quite interesting that India ranks third in the world in terms of research publications related to AI and the India Government has initiated a number of startup schemes related to emerging technologies. AI is set to have a significant transformational impact on the industry as well as academia in the country.

India, being the fastest growing economy with the second largest population in the world, has a significant stake in the AI revolution. Recognizing AI’s potential to transform economies and the need for India to strategize its approach, Hon’ble Finance Minister, in his budget speech for 2018 – 2019, mandated NITI Aayog to establish the National Program on AI, with a view to guiding the research and development in new and emerging technologies. In pursuance of the above, NITI Aayog has adopted a three-pronged approach – undertaking exploratory proof-of-concept AI projects in various areas, crafting a national strategy for building a vibrant AI ecosystem in India and collaborating with various experts and stakeholders. Since the start of this year, NITI Aayog has partnered with several leading AI technology players to implement AI projects in critical areas such as agriculture and health. Learnings from these projects, under various stages of implementation, as well as our engagement with some of the leading institutions and experts have given a better perspective to our task of crafting the national strategy for AI.

However, we are still miles away from unlocking the true value of the huge repository of data collected from different sources using AI and ML techniques, in both the government and the private sector.

There are two broad requirements for diffusion: policy push for spread of AI adoption, and trust of consumers or users, which is the ‘policy pull’. The policy push has been inadequate. The other key ingredient of diffusion is to gain the trust of consumers and citizens by protecting their privacy and data, which is again missing due to the absence of privacy law in India.

First, there has to be increased long-term investment in Artificial Intelligence in both the public and private sectors. India lags behind the top five geographies for private sector investment in AI. The US is far ahead, with investments worth $18 billion, followed by Europe ($2.6 billion) and Israel ($1.8 billion). According to one estimate, China accounted for a greater share of global private-sector funding than the US.

Large companies can afford to invest in R&D but only a few are venturing into it; they are either scared, being risk-averse, or are slow. The start-ups don’t have the money to invest in developing AI and are facing capacity issues. Accordingly, they prefer using existing models rather than develop new ones.

Second: the scope of using AI and blockchain to unlock efficiencies of organizations and systems is maximum in our public sector and government departments. To boost AI infrastructure in India, there is an urgent need for government departments both at the Central and the state levels to adopt AI-based solutions to solve the legacy and intractable problems being faced by them – from increasing agricultural productivity to climate change, from air pollution to disaster management. This will have a multiplier effect that could spur the private sector to jump in.

Third: the government and the private sector must work hand-in-hand, particularly on the R&D aspects of Artificial Intelligence. Public-private partnership models bringing together the expertise of research institutions and universities (including the institutions of eminence), market knowledge along with financial skin-in-the-game by the corporations, and partial financial grants by the government will inspire confidence to innovate using AI. The involvement of the private sector could ensure the research output is market-competitive.

Fourth: promoting STEM courses in early education, revisiting the course-curriculum in colleges and on-boarding industry experts to teach final year students were some of the key recommendations by a tech policy think-tank, The Dialogue, sometime back. Indian higher education programmes also need to be tweaked to include training on AI that cuts across disciplines. The vast network of hugely successful and talented Indian-origin professionals heading large multi-national corporations abroad must be utilized to institutionalize knowledge-sharing, mentoring, and collaborative R&D initiatives.

Fifth: a fundamental challenge with regards to the development of AI in India is the quality of connectivity in the country. India needs to work towards improving its infrastructure and thereby allow for an environment that supports the growth of new technology.

Last: because Artificial Intelligence is so powerful as it has all the information about a consumer to potentially be able to manipulate their behavior, choices, and preferences, India immediately requires a data protection law to ensure individual privacy.

The post PROGRESS AND DIFFUSIONS IN DYNAMIC AI ECOSYSTEM MAPPED BY NITI AAYOG appeared first on Artificial Intelligence.