It is already hard for millennials to imagine that their elder generations actually stood in queues to do simple stuff like pay bills and deposit or withdraw money. In fact if a modern digital transaction takes 10 seconds instead of 5 , you can already see millennials getting impatient. This is the generation that will demand even more frictionless transactions. Why go through the pain of opening an app, navigating a menu, entering an amount and then a PIN, when all you should be doing is clicking a button and saying something like “Hey Assistant, pay my electricity Bill”; and let the assistant authenticate your transaction using your voice biometrics, figure out who your electricity provider is based on your past transactions history and figure out what is the amount due using a GET Quote API. That is the future.
Personal finance, mobile payments being managed through AI-powered solution backed by robust machine learning algorithms, big data analytics, statistical modelling, facial recognition, and chatbots are some of the wide-ranging set of technologies, which is currently being adopted by Mobile Financial Services Industry.
Some other notable application areas where AI is being considered:
- Using AI to generate new revenue potential through new product solutions and services
- AI-powered risk management
- AI-powered reporting/analytics
- AI-powered internal processing automation
- AI-powered customer acquisition
- AI-powered customer support
According to a recent survey (127-page report, titled (Transforming Paradigms A Global AI in Financial Services Survey) conducted by the World Economic Forum in collaboration with the Cambridge Centre for Alternative Finance at the University of Cambridge Judge Business School and supported by EY and Invesco:
- AI is going to be the major business solution offering, according to more than 77% of the respondents
- Risk Management is the most critical and widely adopted solution by 56% of the respondents
- FinTech’s are more inclined towards AI-based products and services and are offering more solutions as compared to incumbents
- 85% of FinTech’s are currently using some form of AI
Areas where AI can be adopted in Mobile Money solutions?
Transaction Experience – as described above, the AI, can take over the heavy lifting in the transaction experience. Let’s face it, we remember to pay our bill very often when we are shaving. And in today’s short attention spans, if we leave it for after, we might forget until the next shave. AI and voice can make it a hands-free experience that takes so little time, that it matches the speed of our thoughts. And in the off chance that you forget that you already made the payment and attempt it again, AI will tell you that “You have already made your electricity bill payment for this month”
Another example: AI can decide if a payment being made at a merchant establishment is an expected purchase based on historical trend, location (which AI can cross-verify with other known location sources e.g. google services, car parking location etc.), merchant type etc. to decide if the payment should be auto authorized or it should throw extra authorization challenges.
Customer Onboarding – Customer onboarding is cumbersome and process-oriented. However, this process can be streamlined using a digital assistant available 24x7 in a self-service onboarding model. One, which can offer customers the convenience to onboard anytime of the day and no need to wait for the approval of documents. They simply can answer a few questions, upload some documents and the AI assistant can guide them through to process completion. This can immensely help in reducing the risk of losing a customer.
AI-enabled communication channels like chat bots by providers, which come close to replicating real human interaction, the chatbot for mobile money services is one of the examples which leverages messaging and artificial intelligence to deliver customer engagement and enhance users’ experience.
Risk Management – A secure mobile money solution is always going to be the first choice of customers and solution providers. Detecting fraud and safeguarding customers from frauds can be managed using AI. AI can be used for detecting fraud using hybrid algorithms either developed in-house or through 3rd party enabled services. e.g. a user can be thrown additional validation when using mobile money solution on a bad reputed source by using historical analytical data.
Customer Services & Retention - AI-based mobile money solutions can be equipped with financial assistance to help manage your money, answer general queries regarding customer recent transactions. Such AI assistants can track expenses and learns about customer spending behaviour (completely semantic process). This means the AI can eventually predict customer actions and can make useful recommendations.
Such recommendations can help a user to get rid of bad spending habits and will help them make an informed decision to manage their money in a better way.
Process automation – AI engine can be developed to improve the efficiency of the core operational processes and completely automating them e.g.
- Report Generation
- Customer Onboarding etc.
This eventually will lead to more efficiency for the service provider.
AI and Internet of Things (IoT) – and if you further imagine a world which marries the capabilities of AI with the capabilities of IoT, the future is a science fictions enthusiasts dream, what with (a) automated cars automatically paying tolls, (b) onboard diagnostics automatically ordering when parts are due for replacement, (c) insurance getting linked to kilometres travelled rather than being linked to time and what not.
Saving Time and quick grab and go Applications with AI- with the help of speech recognition and pre order via text and making quick payment through bots user can buy anything from the store using the Mobile App which will help users to save time by grabbing the items from store in go without standing in queue etc.
AI can improve the Fraud detecting services and help in reducing the false declines- AI having equipped fraud detection system which has been used by the payment services to secure the payment process in encrypted secure way. The system is capable of improving itself consistently by learning every time any fraudulent payment detected to cope up with different Machine rule.
AI (Artificial Intelligence) has arrived and it’s going to change the face of financial sector services across the globe. Though FinTech companies are more inclined towards AI incumbents have also started implementing AI solutions. The AI particularly has a greater impact on Mobile Money / Payments industry and it’s going to expand the access of mobile money services to the unbanked and eventually, this will lead to social and economic assistance for the society and the overall world economy.
However, there are some transitional challenges when a new technology is implemented like:
Quality of data – AI is based on machine learning and the overall learning process is iterative and it takes time to develop a robust machine learning engine to power the AI solution
Skills Gap – Sourcing the right talent for working and creating AI solution is also another hurdle in implementing the solution
Privacy Invasion Concerns – AI implementation requires to be purely based on machine learning (without involving any human interferences) and users need to believe that else it would promote scepticism and aversion towards adoption of technology.
Finally, at a philosophical level. A future where AI makes Humans more efficient at managing their money and saves them enormous amounts of time and stress is a future where Human beings can do what their heart wants to do most…spend time in creative pursuits that maximises their satisfaction of being Alive.
Till then “Hey assistant, send me news alerts for every AI powered Mobile money innovation”
Surajit has more than 25 years of experience in Mobile Financial Services and Telecom Technologies and Products. He is an avid lover of French cuisine and loves to blog about Mobile Technologies and the history of telecom in India.