5 technologies disrupting banking by 2023

Over the next five years banking is going to change dramatically and will be nothing like we know it today. The changes will come due to technology and will provide financial institutions with both opportunities and challenges.

The global recession put a spotlight on banks; these institutions were largely responsible for the near-collapse of economies and although they have weathered the storm, people’s trust in them has not been restored.

Out of the failure of financial institutions came the bitcoin protocol and blockchain technology. This was followed by the arrival of fintech startups and neobanks, both of which threaten the consumer account monopoly enjoyed by retail banks, which is referred to as ‘legacy’ in the financial media. According to various consultancies, new players could capture up to a third of incumbent banks’ revenues in the next 2–3 years. If banks don’t respond to this, they are in danger of disappearing.

However, there is good news for the traditional banks: the new technologies that are threatening the banking industry also present significant opportunities. They can leverage big data and advanced analytics to improve customer experience, as well as build trust, loyalty and revenues. Dan Cohen, SVP at Atos, said: “Banks are at a crossroads. Continuous fintech innovation and new technologies such as blockchain are disrupting the market. While it creates threats, it also opens multiple opportunities for financial services to reinvent themselves and thrive.”

Here are five of the technologies that will advance fintechs and potentially cause more disruption in the banking sector, unless the banks are agile enough to incorporate them.

1. A hybrid cloud

Cloud computing tech has gone mainstream in banks pretty fast. It was found that at least 75% of bankers said their most successful cloud initiatives had already achieved expansion into new industries, creation of new revenue streams, and expansion of their product/services portfolio.

2. APIs

The combination of open platform banking and open APIs will change the entire banking ecosystem in its current state. In this scenario, the bank will serve as a platform, on top of which third-party companies can build their own applications using the bank’s data.

3. Robotic process automation

Robotic process automation (RPA) has helped banks and credit unions accelerate growth by executing pre-programmed rules across a range of structured and unstructured data.

4. Instant payments

Consumer demand for instant payments is on the increase. With instant payments, more transactions will be made digitally instead of in cash, which means that payments will become less expensive and more user friendly.

5. Artificial Intelligence (AI)

The benefits of AI in banks and credit unions are widespread, reaching back office operations, compliance, customer experience, product delivery, risk management and marketing to name a few

5 AI trends in 2019

As the use of Artificial Intelligence (AI) has grown in 2018, we can expect to see even stronger growth in the technology in 2019. One of the reasons it is bound to increase its presence in our lives is that it makes life easier, whether it is chatbots in business or Alexa in the home. According to Analytic Insightsand Forrester Research, in 2019 we will also “see the rise of new digital workers with an increased competition for data professionals with AI skills.” But, what else can we expect from AI next year?

More chatbots and virtual assistants

We will see more advanced use of AI virtual assistants on websites to answer customers’ queries and provide customer service assistance. For example, companies will create virtual agents with a face and personality to match to handle complex tasks to drive business, like, Autodesk’s virtual agent Ava has a female face with a voice that speaks emulating the company’s brand.

Improved speech recognition

Alexa may have started the trend, but in 2019 voice-activated services are going to be even bigger business. Already Sony, Hisense and TiVo have unveiled TVs that can be controlled by voice, and even home appliance makers such as Delta, Whirlpool and LG have added Alexa’s voice recognition skills to assist people control everything in their homes.

Smart recommendations

When we shop online we are already inundated with a series of recommendations about what to buy next based on our previous purchases. This is going to get bigger in 2019, with recommendations based on “sentiment analysis” as well as your search history.

Advanced image recognition

We can expect some is changes here in 2019. Don’t be surprised if there is image recognition to detect licence plates, diagnose diseases, and permit photo analysis for a range of verifications.

Cyber security

In 2019, expect artificial intelligence to be more powerful in fighting off cyber threats and prevent potential hackers. Companies including Darktrace have deployed and machine learning technologies to detect online enemies’ in real-time and identify cyber threats early on, and so prevent them spreading.

Google offers $25 million for AI challenge

Related image

It’s today’s big story: Google is offering $25 million in grants to nonprofits, universities and other organisations working on AI projects that will benefit society,

as part of its AI for Social Good initiative. Google will open the application process this coming Monday and will announce winners next spring at Google’s annual I/O developer conference.

Details of the challenge explain that Google.org is issuing an open call to organizations around the world to submit their ideas for how they could use AI to help address societal challenges. Selected organizations will receive customized support to help bring their ideas to life: coaching from Google’s AI experts, Google.org grant funding from a $25M pool, credit and consulting from Google Cloud, and more.

Google says the programme is meant to help solve the world’s most pressing problems, such as crisis relief, environmental conservation and sex trafficking.

However, it is also clear that this ‘competition’ comes at a time when Google’s own use of artificial intelligence is under increasing scrutiny, including “in controversial military work or reported efforts to build a censored search engine in China,” as CNET says. There has also been Project Maven, a U.S. Defense Department initiative aimed at developing better AI for the military that resulted in a rebellion by Google’s own employees and some 4,000 of them petitioned the executives to stop the project, which the company duly did and promised not to engage in similar projects again.

At the press announcement, Google’s head of AI, Jeff Dean, avoided discussing these issues, although he did mention Google’s ethical principles that outline how it will and will not use the technology.

Yossi Matias, vice president of engineering, said in an interview last week, “The gist of the program is to encourage people to leverage our technology. Google can’t work on everything. There are many problems out there we may not even be aware of.”

It is going to be interesting to see what initiatives come out of this global challenge. Hopefully we will see a diverse range of ideas for AI use that can improve the world when it is so badly in need of repairs in all areas of existence.

 

 

 

 

 

 

 

 

How companies use machine learning

The machine learning market is growing at pace. According to Research and Markets it should reach $40 billion by 2025. Currently it is already over the $1 billion mark, but to reach the estimated value it will have to make a major leap in growth.

What will cause it to grow? Every company will start using it once they have identified a use case, and that is one of the barriers to adoption at the moment, but we can learn from the ways in which major companies are already using machine learning.

Apple

Apple is working on a cross-device personalisation tool and has already applied for the patent. It is rumoured that what this will do is allow your Apple Watch to connect with your iTunes playlist and find a piece of music to match your heart rate.

Twitter

Twitter is working on visibility problems with thumbnail images. It is using neural networks to find a scalable, cost-effective way to crop users’ photos into compelling, low-resolution preview images.

AliBaba

This Chinese retail giant has 500 million customers and each of them uses the store in a distinct way. So Alibaba is using machine learning to track every customer’s journey. Furthermore, all Alibaba’s online storefronts are customised for each shopper and searches will bring customers the products they want to see. There’s also a chatbot who handles most of the spoken and written customer service inquiries. Every element of Alibaba’s business has been built for engagement with the shopper, and every action the shopper takes teaches the machine more about what the shopper wants. It’s extremely effective.

Target

American retailing giant, Target, is using machine learning to reach and respond to its pregnant customers. In fact, Target’s model is so precise that it can reliably guess which trimester a pregnant woman is in based on what she’s bought.

Typically companies have been driven by the seasons, but machine learning can help businesses respond to ‘seasons’ in people’s lives. For example, a person who has just bought a car doesn’t want to see car ads, but motor insurance ads are appropriate. Basically, machine learning can pick up on those rhythms, helping companies recommend their products to customers when the timing is just right.