For some time, Artificial Intelligence has entered our regular technology vernacular with continuous references and frequent mentions. Back in the 90s when tech thinkers were still speculating whether a machine can imitate rational human perception, we had no idea that in just two decades down the line this would be a massive reality. Whether machine can be a complete thinking being in the way humans are is still an unanswered question, but as for machines ability to adapt to user behaviour and preference, we have already have our answer.
Yes, Artificial Intelligence is now not only just a reality of our digital life, but it also represents the next frontier for many of our digital interactions in the time to come, most notably mobility and mobile apps. Thanks to enhanced capability of advanced mobile device sensors to procure user data, mobile apps are more equipped to address user situations and contexts.
While AI will continue to become stronger with more advanced data analytics and device capability, its implication will be huge on industries and niches where efficiency and security are two of the most important considerations. Obviously, finance and banking apps are supposed to be the biggest beneficiaries of Artificial Intelligence. In countries where mobile apps still have not penetrated deeper into the banking and finance sector, it opens up a whole new opportunity.
In some countries across the world where penetration of mobile banking reached an all-time high, AI based banking apps will only broaden the scope leaving users more satisfied. In India, China and many countries in Southeast Asia, AI based banking apps will take mobile banking closer to the users. Indian app developers have already taken the opportunity to leverage AI features in an array of sophisticated banking apps making customer service better. This is just the beginning of a trend that will redefine the banking experience.
What is Artificial Intelligence?
By definition, Artificial Intelligence is nothing but the intelligent and proactive actions that devices and applications perform without active human intervention. Such machine led automated as well as intelligent activities are visible on many fronts including machine learning, natural language processing, machine analytics, chatbots, algorithms, etc.
Implication of AI in finance as of now
The biggest promises of AI for banking and financial sector are efficiency, speed and stronger security for transactions. Top executives of a many banking and financial services confirmed that they have either began to use AI or planning to do so in their business process, as found by a survey confirmed by Narrative Science and the National Business Research Institute.
Most of these organizations confirmed that they found advanced AI technologies like predictive analytics, algorithms for recommending products and voice command and recognition helpful technologies for their present business process. While 32% of these organizations already adapted AI to an extent, 62% of respondent organizations confirmed their plan to do the same by 2018.
What are the precise ways Artificial Intelligence can make a difference in Mobile Banking?
Do you know an average user picks up his phone 45 times a day? Naturally, to reach the target audience of every business niche, mobile devices happen to be the biggest medium. Now, with smarter capabilities of devices to understand user situations and respond to them, apps representing business should also be equipped with more proactive, intelligent and automated abilities. For banking apps, this new exposure to machine intelligence unfurls the opportunity to make their customer service better and enhance customer reach.
Some of the key ways AI can revolutionize mobile banking include the following.
Personalisation is the watchword now for many service industries as mobile devices allow them serving each customer the way they prefer them. It is no different for mobile banking, and Artificial Intelligence plays a vital role in making personalized user experience possible.
Some of the key ways AI can push personalisation include recommending financial products based on the user preference, recommendations based on the user situations and constraints, directing users to correct channels they need-based as assessed by user analytics, notifying users about products and services based on their buying history and in-app behaviour, guiding users navigating through the app and browsing products with chatbot conversation, etc.
Financial advisory services
Banking and financial services need to advise their customers for decision-making concerning investments, financial planning, and insurance. AI-based advising algorithms, unlike their human counterparts, are less biased and more dependent on data analytics to pass their judgment on financial decisions.
For the financial planning of individuals, a tremendously complex calculation is carried out involving a lot of variables including individual earning, contingency, risk factors, liabilities, monetary inflation, etc. Naturally, for such a complex and multifaceted calculations and predictive analytics, a non-erroneous machine intelligence and analytics are more effective than human decisions exposed to calculative errors and bias.
Efficient and quicker transaction
Thanks to Artificial Intelligence in mobile banking apps, the same transaction can take much less time and consume much fewer resources than earlier times. AI-based apps can quickly guide users to their preferred channels without wasting time and resources and can further boost speed and efficiency with automated and real-time payment processing.
With the introduction of digital currency like Bitcoin, transaction data merges with the currency itself. This, in the long run, would make so called physical currencies obsolete creating transaction as easy as passing few bytes of digital data and this transaction data constantly feeding analytics to utilize for more user optimised actions.
With AI personalization can be made an era-defining reality for banking and financial apps. With device sensors and analytics telling the app about user location, context and preference, it can notify users about a new product or service that he needs.
With this personalization in place, while someone can be notified about his due premium and new renewal policy, another person can be offered a new product that he may find ideal.
Blockchain offering un-putdownable security
Finally, we have Blockchain technology, a new kind of open ledger system that keeps every piece of transaction information while not allowing any deletion, change and tampering with stored data. With Blockchain ledger storing financial data, the financial transaction will be secured than ever before, and AI-based security algorithms will further be strengthened with open access to this multi-layered, non-tamper able transaction history.
So, it is quite obvious that AI within a year or so will completely change the way we transact through mobile banking apps. The new era of AI into mobile banking will flourish and make more things easier that we are still unable to predict now.
Email fraud is nothing new, but online criminals have become ever more-effective at spoofing their identities to trick employees into sending them money. The Australian Centre for Cyber Security (ACSC) recorded losses of over $20M to business email compromise (BEC) attacks last year alone, up 230 percent over the previous year – and the full amount is certain to be much larger.
Cybersecurity Insights - Attack
No matter how robust your security, or how diligent your employees, network credentials are a free pass for cybercriminals. This is mostly because employees are relied upon for their own password management. And with more than 4.8 billion sets of stolen credentials said to be available online, odds are that at least a few of your employees’ user IDs and passwords are just waiting to be used by unscrupulous outsiders. Are you ready to stop them?
Cybersecurity Insights - People
Cyber resilience will be particularly important as Australian organisations face increased pressure to quickly detect, respond to, and manage the repercussions of breaches in the wake of 2018’s Notifiable Data Breaches (NDB) scheme.