Financial payments and banking started in a very inefficient and traditional way, which was slow but still acceptable to the customers due to the stage in the information age. There are lucrative but under-utilised banking opportunities and banks in the region need to step up and grasp these opportunities to succeed otherwise its almost a lost game for them. AI technologies such as machine learning, deep learning, prescriptive learning, predictive analytics, virtual agents and natural language understanding technologies are gaining popularity among progressive banks.
AI is not a magic push button and it will never be but as a strategy if one adopt it will take them to new height though, particularly for financial institutions, fintechs and banks where data access and security play a critical role. Competition in Fintech world today at its peak, so adoption of new technologies to stay one step ahead of the competition is no brainier. AI in Fintech allows eliminating human error while boosting productivity and increasing bottom line. With advancement in technology, organisations outside the banking industry diversified into financial services targeting margins in the space.
These were organisations servicing millions of customers through broad distribution channels, be they mobile operators, retailers or on-line merchants. Artificial Intelligence offering numerous opportunities to payments and to almost every other industry of today. It’s a simple rule adapt or be adapted and become part of history books. Financial or banking is getting hit hard the most. AI reinventing and increasing info-security, reducing processing times, reducing duplicate expenses and human errors to make it more viable in the filed of FinTech.
Banks to set them on for new financial, banking and innovative business. What would have been considered impossible until a few years ago — transforming themselves from impassable monoliths to nimbler organisations, open to new kinds of partnerships. Now increasing levels of automation, offering game changing insights with data mining and balancing consumer budgets based on spending patterns are the latest powerful tools for any fintech or bank of today.
Banking-as-a-Service (BaaS) would become more acceptable and popular compared to Banking-as-a-Platform (BaaP) as BaaS aptly describes new strategy of providing public APIs and development portals. It would very exciting to see how and what role AI will play in Fintech in near future. Chatbots in financial services are not new though but chatbots are now getting much more smarter with help of AI and NLP.
Some of the one liners I always use for AI buzz words as these buzz words are around us almost every where and we often hear them in and out.
- Machine Learning – Never need your brain to program anything
- Deep Learning – is really deep not just name sake
- ANI – Narrow AI example Siri, Cortana and Google Assiatant.
- Bots – Not a boat, Not a Messenger, Not a Robot and not necessary an AI child
- ASI – Super intelligence much more higher then human mind or capability. May fall in love with your girl friend or wife be-careful.
- Big Data –This data is realy big and requires proper tool, seriousness and attention
- Natural Language Processing (NLP) – Yes its really natural upto an extent
- Artificial Intelligence (AI) – Attempt of human brain parody
- Data Science is not just BigData, may be an ocean which hold this small big data.
- AGI – at level of human failed capacity i.e Self-driving cars
AI is now bringing behavioral biometrics to a business tool for real. Static biometrics such as vein pattern, fingerprint, retina scan, selfie, are all nearly unchangeable but still not impossible. Deep neural networks (DNN) are being used to bring dynamic changes. Behavioral biometrics presents a fairly new approach to monitor and score customer and device interactions during transactions. Behavioral Biometrics: Dynamic Approach to Authentication and Security.
Behavioral biometrics solutions are able to create a more precise picture of the user by examining a range of behavioral pattern. BB is deductive, full of reasoning, and has extreme potential for problem solving abilities with AI for FinTech. Artificial Intelligence coming down from its 50,000 feet high hype to ground reality for the actual business benefits and every day life. AI is no longer a study material for PHD.
AI is now helping and supporting predictive analytics problem in quick manner to conduct specific observations to make broad general statements. It is now playing a master key role in creating personalized user experiences. Learning from customer preference history, browsing app history, notifying customer of similar products and services. Use AI to help break the tradition of using data to report historical trends and to justify reactionary decisions. Cultivate a proactive approach, which benefits both the business and the customers.
AI in Fintech is a great help & ease for understanding on how the automation can be achieved for automated tasks (yes its true). Machine Learning focuses on predictions, based on known properties learned from the training data using too much statistical inductive reasoning. It’s been said ML works very well as long as past gets repeated in future. Financial chat bots use predictive analytics to push out real-time, informed responses to customers without the need for human intervention.
Expert System is a computer system that emulates the decision-making ability of human expert using deductive reasoning. Big data helps to make strategy for future and understand user behavior. Not just data but a quality data – Focus on quality data rather quantity as data is next most expensive commodity after fuel. Treat network traffic as a ‘gold mine’ – Data is yours, use every bit of It. Capture everything to avoid blind spots – Look at the full/big picture.
Underlying technology-using AI as it provide deeper insights to understand business. We need to be agile enough to know and accept the fact that every business of today operates in real time so not just BI we need Intelligent BI. Intelligent BI with predictive analytics is masterstroke in any strategy formulation. AI is driving the ability to build knowledge at high speed, quicken decision making from Big Data. Data Analytics should have a purpose, be grounded in the right foundation, and always be conducted with adoption in mind.
Unfortunately so far only intelligence got artificial but risk still remains for real and natural. Natural language generation can create, write and tell your business stories but still raise hands when risk over takes. I am getting tempted to say — this time is really different. AI DAOs – AI that can accumulate wealth, that you can’t turn off.
Interoperability or “ As a Service” concept / economy or simply “Everything as a Service” now brining these most advanced expensive and out of reach technologies to every small business to benefit from. AIaaS- AI as a Service – To bring small & start up business close to industry standards – Help them to grow. MLaaS – Machine Learning as a Service is helping payment industry a big time, specially all those who are coming out of payment industry to payments 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.
High-powered algorithms are not a new phenomenon in finance though, and for this industry, the name of the game is efficiency and precision which suites more for FinTech due to their fast adopting nature and risk appetite. Artificial intelligence may be all the craze in Silicon Valley, but on Wall Street, well, there’s a lot of skepticism.
Conclusion – Artificial intelligence is set to transform the financial services industry. It helps ecommerce business and companies for driving more seamless shopping experience for its customers and taking orders directly from social media channels. For banks and Fintech it help and supervise consumer credit scoring and at end inform consumers for any upcoming event like payments due and to create realistic budgets. Smart machines producing smart payments with inbuilt payment intelligence.
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