Payment Intelligence Through AI

This is the extract from my presentation done at GECommunity2017 Summit in Kuala Lumpur Malaysia on 12th and 13th December 2017. This was the biggest summit in Malaysia and opening speech was done by “Sri Haji Mohammad Najib bin Tun Haji Abdul Razak” (Current Prime minister of Malaysia since 2009). Attended by almost 15,000 participant with speakers from 27 countries around the globe.

If any one is looking for full presentation free copy , please send me email or comment in below with your email address. I will talk about different elements of PI in this post on very high level only. Idea is to show what is PI, what it can do and what all elements are in ecosystem of PI.

Objective

• Bringing Artificial intelligence to make FinTech better, demystified and simple.
• How payment intelligence will become better with machine learning.

Desired Outcome

To bring people from technical backgrounds, business people who can understand and appreciate the need and concept of Artificial intelligence to create products, services and solutions in financial Technology and banking domain. Developments in the FinTech space – an industry which received $19 billion in venture capital last year – are touted to radically transform the face of financial services, from payment systems and clearing to financial settlements.

Payment intelligence (PI) a system at national level can bring the whole nation together, secured and cleaner of underground economies. Imagine a scenario like this “You walk in a shopping mall and get a sms which reads “Walk on to 3rd floor to buy your favorite brand of cloths and get 20% discount”. Because its 25th of the month and you got paid meaning have money. So here merchant, bank, employer,  telephony service provider,  credit service provider and many other are all  connected to PI System so this kind of system can generate business. At the same time once you fall short system can offer micro credit of $10 to $500 credit depending on your credit ratting and charge you 10-20% rate of interest for 3 months period (80% over 12 months) and you wont even mind or realise.

Payment intelligence (PI) System – Can open lot of opportunities to young entrepreneurs and boost economy of the nation.

Data alone life-less and inherently dumb. It doesn’t do anything alone without support and knowledge & tools on  how to use it, how to act on it. Algorithms is where the real value lies. Algorithms define & drive action. Whole point of the algorithms involved in high-frequency in business is to detect, analyse and make decisions faster than a human heartbeat.

FinTech known through the help of AI that, in one way or another how to make money. The application of any computer-enabled algorithm that can be applied against a data set to find a pattern in the data. Because of this, new wild and flashy AI systems that are making FinTech ‘s smart systems smarter  and can help to them to fly. Not surprisingly, these companies each have a clear market application and reduce friction in the business problems they address. Fintech’s Artificial Intelligence revolution is perfect example and era of pervasive AI financial technology services.

 

AI Boosting info security through behavioral biometric intelligence

• With account takeover and mobile fraud growing in leaps and bounds, the need to move beyond password protection and two-factor authentication has never been greater. Hackers routinely find ways to steal personally identifiable information (PII)
• Consumers will be able to perform complex transactions, such as making purchases and payments or transferring funds, without the need to type a single character.
• Behavioral biometrics presents a fairly new approach to monitoring and scoring customer and device interactions during transactions.
• Voice biometrics is been attempted to combine with AI in a bid to directly communicate with chatbots up to the emotional level of understanding. This could probably reduce the need for human operators in call centers in the future while protecting employee perpetrated data leaks
• Companies in the fintech industry will find multiple opportunities to enhance decisions on lending, such as how to optimise financial advising or execute better trading decisions. AI could also help improve the algorithms to create the optimal financial advising.

As digital business remains dynamic, and business teams become more engaged in the solution delivery process, we expect this will result in a more-complex collection of technologies, disciplines and practices to support the varying needs of users. Organizations must plan for the adoption, or replacement, of key technologies and practices, as well as the development of people and skill sets.

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.

• Algorithmic trading
• Chat bots
• Customer recommendations
• Fraud detection
• AML Pattern Detection.

Blockchain is here already and  while still relatively new to the financial space but attracting interest from around 90% of banking sector executives, according to a new study on the potential of the technology in the industry. Blockchain is said to be the answer for many information security threats. For business strategies, customer acquisition plans and revenue goals may be in danger due to (Not limited to though)

• Application tampering
• Rogue Apps
• Malware
• Overlay attacks

What is needed here an intelligent tools and systems to handle Threat Intelligence which will be on 24X7 job for Threat Hunting. Blockchain to push PI (Payment intelligence) at rapid speed as on date 40% of banks find themselves still at the exploration phase of blockchain technologies, while around 30% are pursuing proof of concepts. Intra-bank cross-border transactions are regarded as the most likely payment system to see blockchain implementation, followed by cross-border remittance and corporate payments.

One of the technologies which has received considerable hype in recent years is blockchain, a distributed ledger technology (DLT) that serves as the backbone of cryptocurrencies. Application development technologies and disciplines continue to evolve as the need to deliver business outcomes and accelerate application delivery with high quality intensifies. This encompasses basically all types of data science algorithms, supervised, unsupervised, segmentation, classification, and regression including deep learning.

That’s simplistic for a reader to appreciate the importance of Regression. Historical notes on KDD (Knowledge discovery and data), CRISP-DM, BIG DATA, and Data science and their relationship to data mining and Machine Learning are available all over internet for free but how to put them in real business and discover the hidden potential of such powerful tools to bring values are still not much talked or explored.

Please note I am not advocating AI on blockchain here as basic architecture for both as per my understanding is lot different as on date. Also Deep Learning is different from traditional predictive analytics in my opinion hence my picture above shows the same.

Conclusion – Artificial intelligence is set to transform the financial services industry. How AI will be transforming the future of finTech to elaborate items from the above list in African markets and opportunities are even more dramatic – In just the past five years. Modern mobile payment infrastructure availability – Africa has payment instruments such as mobile wallets for merchant payments, bill payments, prepaid airtime top-up etc. Smart machines producing smart payments with inbuilt payment intelligence. What fascinated me most in PI subject book (Currently being written) the explanation of such complex subject PI, regression and use of AI and its components described as ‘ a tutor teaching students in an institute – if outcome is continuous use linear and if it is binary, (Regression) use logistics’.

#ArtificialIntelligence #MachineLearning #ArtificialNeuralNetworks#PaymentIntelligence #DeepLearning 

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