PaymentIntelligence – Welcome to the future of Payments. When Payments meets artificial intelligence, blockchain, and data science it produces a culture in the payment industry called PaymentIntelligence. Today in most of the developing/developed economies/countries need specific payment methods/channels as per their environment. One thing which should work as a common goal i.e. how to eliminate corruption, meaning cash. A new technology and payment system with intelligence i.e. PaymentIntelligence (PI) System is the answer.
Artificial Intelligence in the Payments Industry
The more the volume of digital payments it brings more help, a hindrance to spotting fraud and more human health (bacteria and viruses through dirty currency bills and coins). The digital money boosts big time a fraud-detection system to its limits. By adding machine learning flavor to the data the digital money system generates it brings trained algorithms and data models to detect anomalies, unusual patterns and fraud hunting which can not be with the human eye.
The current payment systems or typical traditional digital payment system has too many limitations and static/rigid variables like merchant type, currency code, country code, location, product type, usual spending range, etc tied to users. These attributes are almost impossible to change/adjust in an automatic manner as there is no learning curve. So as the user/customer behavior changes system has no velocity to adjust but just raise/block as potential fraud.
Payments wrapped in AI cover (machine learning), so-called payment intelligence improve threat hunting and fraud detection significantly. Score based risk assessment and then adjusting the scores and learning from user behavior i.e. spending amount over the period of time or change in spending locations etc. Online transactions with different source IP and physical distance between transaction originating IP are few examples that Machine learning can pick and analyse much better and faster. Machines can decide to send OTP in case second level authentication is needed and also mobile phone cell ID would be an awesome combination there.
PaymentIntelligence – A new dimension of payment science by combing Artificial Intelligence, Blockchain, Data Science and Machine Learning as its foundation level.
This post is an extract from my presentation done at GECommunity 2017 Summit in Kuala Lumpur Malaysia. GECommunity summit is an annual event that attracts the best and the brightest talents from academia as well as industry.
Payment Data Inventory – Intelligence Hub
Working with payment data is more complicated than ever. Data fabrication is needed to solve the data intelligence/efficiency gap. Converting idea data which is sitting in silo to a flow of trustworthy data that anyone can use is a very big and complicated task as well, once it’s done then it can bring lots of value.
AI can push organizations to get faster access to trusted data and make decisions more confidently. The AI-based payments give customers and businesses too many benefits which are almost impossible to forget. Payment Data Intelligence brings
- Ensure and trusted data at first sight with Data Inventory
- Dramatically increase efficiency and productivity with Pipeline Designer
- Automate more integration tasks with AI and APIs
Payment intelligence is radically transforming the face of financial services i.e. from payment systems to clearing to financial settlements. New products like data Inventory creator, powerful & capable machine learning algorithms that can accelerate and modernize data engineering.
PI Systems Desired Outcomes
To bring people from technical and business backgrounds who can understand, appreciate the need and concept of artificial intelligence. This is to create products, services, and solutions in the financial technology and banking domain. This new phenomenon Payment intelligence can bring new opportunities to build a strong, thriving and secured national payment system. The system can raise the bar on delivering the convenience and security of digital currency to people all over the world.
Payment intelligence system will reduce the risk of a cyber fraud which targets the merchants, financial institutions, banks and customer on the street. PI fraud management module provides the ability to support early identification of common issues in payments and purchase through intelligence and prevent compromised payments.
Developments in the FinTech space – an industry that received $19 billion in venture capital last year. FinTech has grown exponentially on the basis of best practices like the rapid response, triage and preventive analysis of technical forensic investigation. Paymentintelligence system comes with the ability to conduct a cyber analysis, develop digital money platform infrastructure.
PaymentIntelligence a New Dimension
PI at the national level can bring the whole nation together. It can secure the economies and flush out the underground economies. In a scenario when you are in a shopping mall and get an SMS. That reads “Walk on to the 3rd floor to buy your favorite brand of cloths to 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 others are all connected to PI System so this kind of system can generate business. In US alone real-time payment eventually got its the first new core payments infrastructure which the most advanced in more than 40 years.
AILabPage – Intelligence in one-liners
Now a second scenario on top of the first one “you fall short in your balance system to make payment”. In this system case, the Payment intelligence system can offer microcredit of $10 to $500 credit depending on your credit rating. Even if the system charges you a 10-20% rate of interest for 3 months period (80% over 12 months) and you won’t even mind or make the note.
PaymentIntelligence (PI) System – Can open a lot of opportunities to young entrepreneurs and boost the economy of the nation. Data alone is life-less and inherently dumb. It doesn’t do anything alone without support, knowledge, and tools on how to use it, how to act on it.
Algorithms are where the real value lies. Algorithms define & drive actions. The whole point of the PI algorithms involved in high-frequency in business is to detect, analyze and make decisions faster than a human heartbeat.
FinTech & AI – Payments with Artificial Intelligence.
FinTech Intelligence can help 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 them to fly. Not surprisingly, these companies each have a clear market application and reduce friction in the business problems they address.
Payment Intelligence
Fintech’s Artificial Intelligence revolution is a perfect example and era of pervasive AI financial technology services. The aim of payment intelligence is to explore AI potential in the financial sector and to become a major business disrupter. The AILabPage team did a small research project through its freelance members on a global practice that designs and implements digital transformations.
AI Boosting Info-security with Behavioural Biometric
- With account takeover and mobile fraud growing in leaps and bounds. The need has arisen to move beyond password protection and two-factor authentication which anyways has never been greater. Hackers routinely find ways to steal personally identifiable information (PII)
- With BBI 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. Such as how to enhance decisions on lending and how to optimize financial advising or execute better trading decisions. AI could also help improve the algorithms to create 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. This collection is 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 skillsets.
Banking Applications with Artificial Intelligence
Application Artificial intelligence has several applications in the banking industry. Top-5 applications of artificial intelligence in the banking industry that will revolutionise the industry in the next 5 years are listed below.
- Algorithmic trading
- Chatbots
- Customer recommendations
- Fraud detection
- AML Pattern Detection.
The blockchain is here already and while still relatively new to the financial space. It attracted interest from around 90% of banking sector executives though. According to a new study on the potential of technology in the industry. The blockchain is said to be the answer to 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
Artificial intelligence is ready for business but the business may not be ready for AI, this where the major issue is. AI hype putting almost every business in peril and many businesses are now forced to make claims then real work.
Intelligent tools for Threat Intelligence / Threat Hunting.
What is needed in today’s payment market is an intelligent system to do automatic threat intelligence. The system can perform threat hunting without rest in a 24×7 manner. Blockchain will also push PI (Payment intelligence) system demand towards the north at rapid speed. Why blockchain, when we have AI as a supportive partner to the payment system? The response this is actually out of scope for this post but for now, we can learn it has an important role for payment security reasons. As on date, 40% of the banks find themselves still at the exploration phase of blockchain technologies. While around 30% are pursuing proof of concepts. These are not at all good signs.
Digital Transformation for PaymentIntelligence
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. PaymentIntelligence brought real-time payment which eventually brought real-time threats as well. P2P and m-commerce payments are fuelling growth in real-time payment systems.
PaymentIntelligence as a Service
One of the technologies which have 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. Blockchain’s financial part underpayment intelligence encompasses 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 Knowledge discovery and data, CRISP-DM, BIG DATA, and Data Science and their relationship to data mining and Machine Learning are available all over the internet for free. 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 the basic architecture for both as per my understanding is a lot different as on date. Also, Deep Learning is different from traditional predictive analytics in my opinion hence my picture above shows the same.
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, regression and use of AI and its components. They are described as ‘ a tutor teaching students in an institute – if the outcome is continuous use linear and if it is binary, (Regression) use logistics.
New Job role Payment Intelligence and SECaaS Analysts
Soon in the market or it must have started already in the market in payments and info-security industry to fight cyber-crimes. These professionals will be a great value add to
- Serve as a Global Risk Subject Matter expert on various payment frauds via new brand new platform i.e payment intelligence.
- The new system or PI says will be able to analyse data and respond to alerts relative to SECaaS as the built-in metric.
- Statistics & machine learning techniques surrounding cybercrime case will report and investigated in an automatic manner.
AILabPage’s – Payments Series – Payment Intelligence System
These professionals will lead the design and production deployment of new and advanced techniques to recognise and prevent payment methods and cybercrime.
About the Summit
The summit took place on 12th and 13th December 2017. This was the biggest summit in Malaysia and the opening speech was done by “Sri Haji Mohammad Najib bin Tun Haji Abdul Razak”. Sri Haji is the current Prime Minister of Malaysia since 2009. The event was attended by almost 15,000 participants with speakers from 27 countries around the globe.
If anyone is looking for a complete and detailed presentation free copy, please leave your email address in below comment box. I will talk about different elements of PaymentIntelligence (PI) in this post on a very high level only. The idea is to show what is PI, what it can do and what all elements are in the ecosystem of PaymentIntelligence.
Objective
- Bringing Artificial intelligence to make FinTech better, demystified and simple.
- How PaymentIntelligence will become better with machine learning.
Artificial Intelligence is changing the face of payments so its frauds
In this independent discussion blog post, the idea is to examine the impact of artificial intelligence on the payments industry. How AI is being deployed by payments and FinTech services providers who are becoming the first few to make use of these technologies across financial services sectors.
Books + Other readings Referred
- Open Internet – NewsPortals, Economic development report papers
- Personal & professional working experience of @AILabPage members.
Disclaimer
All credit and credits of contributions remain with original authors and I sincerely thank for their contribution here. Welcome to the future of Payments. In this post, we have discussed the potential merger of AI and its bundle pack i.e. Machine Learning, data science and analytics. In the next post, we will pick up a specific use case to deliberate on.
Feedback & Further Question
Do you have any questions about Deep Learning or Machine Learning? Leave a comment or ask your question via email. I will try my best to answer it.
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. Africa has payment instruments such as mobile wallets for merchant payments, bill payments, prepaid airtime top-up etc. This infra is ultra modern mobile payment infrastructure with too much packed init.
#PaymentIntelligence #MachineLearning #DataIntelligence #DeepLearning #ArtificialIntelligence
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Original post: https://vinodsblog.com/2017/12/13/the-new-intelligence-in-market-paymentintelligence/
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