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AI IN THE FINANCE SECTOR: WHAT’S NEXT?

By Rui Vasconcelos, Product Manager for AI/ML at Canonical – the publisher of Ubuntu

 

The last few years have seen the promise of general AI acclaimed across multiple industries and this vision has been particularly strong in the finance sector.  We’ve currently hit the trough of the hype curve and it will take some time for engineering solutions to deliver on the touted promise. The potential is so great, that hope for general AI will require a longer term and collaborative investment, rather than a quick ROI for a single financial company. As a result, we need to see a continued collective effort from organisations in the direction of making general AI a reality – whether that is in the near future or further in time.

 

Artificial intelligence within financial organisations has developed from an almost unfathomable vision into tangible deployments, with applications ranging from back-end decision making to front-end customer-facing services. Financial services companies are now placing a much greater focus on AI/ML and are rearchitecting their IT and business operations to take advantage of what this new technology can offer. However, these implementations are what is known as ‘narrow’ AI, which is focused on a single or limited task and operates within a pre-programmed state. Almost all of the AI that surrounds us today is narrow AI. Everyday examples within the financial industry range from Robo-advisors to tailored credit and insurance tools. In distinction, general AI is a progression of this and is often described as an AI solution that can solve a wide range of financial services issues – from natural language understanding to anticipating risk and detecting fraud  – with the additional advantage of self-learning to solve any problem without human intervention.

 

Rui Vasconcelos

Narrow AI is goal-oriented and solves a particular problem, which is not necessarily bad. We have seen AlphaGo perform a singular task (playing the complex game of Go) and beat the top human expert at it. Organisations focused on being highly competitive in specific use-cases, should concentrate on narrow AI, however it is a short-term win. Those looking at wider-range problems and planning to gain long-term competitive edge need to consider investing in work that will make general AI more accessible, benefitting both the company and society in the long run. Getting there will harness tools and insights that will be very  valuable to other financial services applications, even if we do not reach general AI in our lifetime.  Where a ‘narrow’ AI would take into consideration historical stock prices to make time-series predictions, general AI would look into all types of accessible data that might influence the mood of investors on that day.

 

It’s unsurprising that AI development is a resource heavy and challenging process, and general AI development will be even more so. However, we possess an unparalleled capacity today to move it forward, both in terms of computation and human collaboration. The open source community may be able to help tackle some of the hurdles to general AI development by encouraging collaboration as well as pooling knowledge and resources. For instance, open source software allows IT teams in finance companies to benefit from frameworks, data sets, workflows, and software models in the public domain at reduced costs. In addition, the open source community sees projects as a shared responsibility, so provides an extra layer of security by continually monitoring source code for potential flaws and vulnerabilities.

 

A further advantage of the open source community is that it assists financial businesses to overcome the AI skills gap – one of the most frequently discussed obstacles to AI adoption. In fact, recent research shows that  a third of IT teams cite a lack of skilled people and difficulty hiring for required roles as the third most-common challenge. The first hurdle is a lack of institutional support from within the business. In another study, technology’s lack of transparency was also cited as a major hurdle. With collaboration promoted at its very core, an open source approach to AI allows smaller IT teams to benefit from the wider expertise of the much broader community.

 

Open source will be fundamental to democratising the development of general AI. Financial services organisations who are invested in refining and improving AI for the benefit of their own operations and society will look to open source for future development. However, realising general AI will require long-term  investment. Without it, the likelihood of reaching  general AI in our lifetime is low. So, it’s up to financial services businesses to start concentrating resources into general AI now to make this future a reality in a short timeframe.

 

Top 10

WHY INDONESIA IS THE WORLD’S NEXT DIGITAL PAYMENTS BATTLEGROUND

Kelvin Phua, Global Head of Payment Networks at PPRO

 

The COVID-19 outbreak has seen the e-commerce sector surge. Despite economic uncertainty, consumers around the world are turning to the internet for the goods and services that they previously would have looked for in-store. In APAC, this has meant that some emerging markets have accelerated their adoption of digital services; the growth that was projected to take years has only taken months.

One notable example of this is Indonesia. According to a recent survey, Indonesia’s e-commerce sector is expecting 50% year-on-year growth with its value set to reach US$35 billion in 2020, up from $23 billion in 2019. What’s more, 30% of the country’s growing e-commerce market is new to online marketplaces and 40% intend to keep using e-commerce after the effects of the pandemic lessen.

With this upward trend has come a reliance on digital payments, and both public and private sectors have responded accordingly. Recently, the Indonesian central bank announced that all mobile payment providers were to replace QR codes with the standardised QRIS (Indonesian Standard QR code), providing a single integrated platform for all transactions made using QR codes across multiple e-wallet providers. On the private sector front, LinkAja has launched an online shopping solution to overhaul traditional marketplaces throughout Jakarta by enabling users to pay for goods using an app with the products delivered straight to their door.

For e-commerce and digital payment providers, these examples are good indicators that the time is right to go after a share of this market.

 

Understanding the playing field

Indonesia possesses many of the key characteristics that are critical to a market’s adoption of digital payments. With a smartphone penetration rate of 60%, well above the region’s average of 51%[1], and having witnessed its middle class grow from 7% to 20% of the population over the last 15 years, it comes as no surprise that Indonesia’s internet economy has more than quadrupled in size since 2015.

Currently, there are 37 local payment methods (LPMs)[2] in Indonesia, with GoPay, Doku, OVO, Dana, and LinkAja some of the frontrunners in the battle to claim a slice of the payments pie. This number is expected to grow as Alipay formalises its entry into Indonesia in partnership with Bank Mandiri and Bank Rakyat Indonesia, joining WeChat Pay which was officially granted a licence to operate in the country this January in collaboration with CIMB Niaga.

The growing number of players jumping on board with digital transactions bodes well for the Government’s National Non-Cash Movement launched in 2014. Go-Jek’s recent funding round and Facebook’s plans to build an e-commerce ecosystem around WhatsApp will help accelerate the adoption of digital payments for millions of SMEs in Indonesia, with businesses already using the popular messaging service to interact with their customers. Similarly, PayPal’s arrangement with Go-Jek will see the latter’s users use GoPay at PayPal merchants globally.

With the influx of foreign payment services and investment catering to higher consumer demand while creating the digital infrastructure needed to facilitate higher payment volumes, Indonesia is shaping up to be Southeast Asia’s next digital payments battleground. But what does this actually mean for businesses and consumers there?

 

Navigating a fragmented payments landscape

With all this consolidation and market movement, payment providers are innovating quickly to strengthen and enrich their offerings by partnering with others to develop their own unique payment ecosystems. Initially, these new partnerships will result in greater efficiencies when it comes to connecting consumers and businesses through one platform. But the fundamental pain point remains; the development of multiple payment ecosystems will continue to create the dilemma of choice. Consolidation in the truest sense of the word is yet to be achieved, and the payments landscape in Indonesia remains highly fragmented.

Since Indonesia loosened investment rules in 2016, foreign e-commerce players such as Amazon and Alibaba have entered the domestic market, competing against homegrown firms such as Tokopedia and Bukalapak. This has provided consumers with access to a wider variety of goods at more competitive prices.

To keep up with consumer preferences in Southeast Asia’s largest economy, merchants and payment service providers would need to evolve – by delivering a customer-centric experience where consumers are able to pay with the local payment method they prefer and trust.

In the long term, businesses should refrain from the drawing of battle lines in Indonesia’s fragmented payments landscape and create a payment ecosystem that takes into account payment preferences of the local consumers. Those who seek to enter multiple markets through one payments platform-as-a-service will be the ones most likely to succeed in capturing the lion’s share of the e-commerce market.

 

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Technology

ARTIFICIAL INTELLIGENCE AND FUTURE OF TECHNOLOGY

Ashish Jain, CEO, Future FX

 

Artificial Intelligence refers to machine intelligence that is programmed to think like humans and mimic their actions. For example while writing this article, I am not actually typing it but dictating it out using the microphone and the text is being typed by Microsoft Word itself.

The ideal characteristic of artificial intelligence is to rationalize and take actions to achieve a specified goal.

As technology advances the previous methods of artificial intelligence are taken for granted as new necessities are conjured. For example the computer was one of the most iconic invention of artificial intelligence but now it is considered as mandatory.

Artificial intelligence is continuously evolving and has to evolve. Machines are made in a way that they understand mathematics, linguistic, psychology and many more other terms that are related to human mind.

Artificial intelligence is used in many sectors for example the medical sector. It is used to test drugs and medicines.

We have applications and games which includes chess where the computer plays against us this is also a feature of artificial intelligence. Similarly self driving cars are also an invention of artificial intelligence. These have to be designed very intelligently.

This can also be used in the financial industry to trace and flag activities in banking and finance such as unusual debit card activity or usage and large deposits.

This also helps to estimate the demand supply and prices of the estimates and that makes trading easier.

Earlier, we had to pay a visit to bank on order to deposit a cheque. Then we updated to ATM/Debit Cards and now you can be identified by your retina. Many different sectors have also adapted this method to make actions it more convenient and safe.

Some more examples of artificial intelligence are iPhone’s Siri, Google’s Smart Assistant, Amazon’s Alexa, Google Maps, Ride- sharing apps like Uber and Ola, diseases mapping, Automated investing, virtual travel booking, social media monitoring, inter team chat tool, NLP tools, etc.

Artificial intelligence is all around us and playing an active role in our daily lives. Every time we open our Facebook newsfeed, do a Google search, get a product recommendation from Amazon or book a trip online, we are using it immensely.

In the coming years, computers might match or even exceed human intelligence and capabilities on tasks such as decision- making, reasoning and learning, analytics and pattern recognition, visual acuity, speech recognition and language translation.

Smart systems in commodities, vehicles, day to day use objects will save time and effort offering us a more customized and comfortable future.

It will help the medical sector hugely in upgrading the medicines and treatments, inventing new ones which haven’t been found yet and making everyone’s lives more safer and healthier. A large number of data can be collected from person to person about their health and nutrition and thus changes can be made in the lifestyle.

Artificial intelligence will bring changes in the educational system making it more revolutionary and advanced.

Overall, every factor has advantages and disadvantages and artificial intelligence has it’s lot too. Considering all the advantages artificial intelligence will also affect the human decision making power, analyzing and rational thinking, lifestyle etc. It will make people lazier and will affect their creativity. It can also lead to unemployment due to increase in usage of machines.

Like everything has a balance, artificial intelligence needs to be balanced too so that we can enjoy it’s benefits without suffering the negatives.

 

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