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Who Will Rise to Claim Payments in Southeast Asia?

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Who Will Rise to Claim Payments in Southeast Asia?

The Southeast Asia marketplace economy is booming, with arguments over whether Thailand — with 11 million online consumers expected to double every three years — or Indonesia, expected to have a $130 billion e-market by 2020, is truly in the lead for the region. Beyond those two nations, there are a number of e-commerce and marketplace economy startups in other Southeast Asian countries, including 270+ in Singapore and over 30 in Vietnam.

The landscape for payments in Southeast Asia is particularly intriguing because it’s a potentially huge market with no one payments player dominating the region. China, has seen Alibaba and WeChat Wallet split their payments economy. The U.S. has PayPal and Venmo (now the same company), and Africa has M-PESA. But despite nearly a trillion dollars of potential value in Southeast Asia, no one has risen to the top. 2.5 billion people globally don’t have a bank account, and a hefty chunk of those reside in Southeast Asia. Most payments systems in the first world are tied back to bank accounts; even the ones that don’t, like M-PESA, tend to have solid local reach.

The Challenge of Payments in Southeast Asia

Perhaps the biggest challenge with creating a regional payments platform throughout Southeast Asia is that each country has a very unique culture. The adoption of e-payments or mobile payments varies greatly among the individual countries that make up the region. Take for example Singapore, 74% of the population still prefers card payments over other options. Whereas only 27% of payments are completed by card in Indonesia. Creating a payments platform that fits the cultural needs of individual countries in Southeast Asia will be key to creating a payments service that gains regional traction. Companies can and are choosing to tackle this problem in a number of ways:

  1.  A country by country expansion backed by local teams with a deep understanding of the local market
  2.  Strategic partnerships with payments businesses in target countries
  3. Purchasing/investing in local payments providers

Which method will drive the most success has yet to be seen!

Contenders Vying for Payments Dominance

So what payments companies in Southeast Asia are standing out in a crowded, locally-driven marketplace economy? Who could rise? We explore four innovative companies looking to succeed in Southeast Asia below.

The contenders:

  • Grab
    Grab, the Southeast Asian decacorn that originally started as a ride sharing app, is now headquartered in Singapore after originally launching in Malaysia. It jumped into the payments industry in 2016 with the launch of GrabPay. Now available throughout Southeast Asia, Grab offers a variety of financial services through its digital wallet, including payments, with plans to expand into micro-loans, insurance, and monthly post-payment options. Grab is using strategic partnership to expand its footprint in Southeast Asia and has partnered with Maybank, OVO, and SM Investments Corporation, to expand its footprint. GrabPay is expected to launch in Thailand in 2019.
  • Go-Jek
    Go-Jek is another Southeast Asian company that started life as a ride hailing app and expanded into the financial services scene. Go-Jek powers payments through its Go-Pay digital wallet which is Indonesia’s leading e-money wallet.
    Go-Pay has made significant inroads into Southeast Asia and has purchased three fintech companies—Kartuku, Mapan, and Midtrans—to help provide the foundation for its financial services and facilitate its expansion. The addition of these business gives Go-Pay access to technology and talent in the payments, lending, and savings spaces to help power their spread throughout the region.
  • Ant Financial
    Ant Financial, which originated from Alipay, is another financial technology company that could rise to take the payments crown in Southeast Asia. With a large and loyal consumer base in China, its home country, Ant Financial is making deliberate steps into the Southeast Asia region. Ant has made strategic investments in companies offering mobile payments wallets in the region to extend the reach of it services. Through investments and partnerships in local businesses Ant Financial now powers payments services in both the Philippines and Thailand.
  • Singtel Dash
    The Dash Platform is an all-in-one mobile payments solution from Singapore’s largest telco Singtel. Singtel has developed the Via alliance, which builds partnerships with other e-wallet and payments platforms around the world including Southeast Asia. As a result of the continuously evolving alliances Dash platform subscribers can now or soon will be able to pay for goods and services using their Dash wallet in a number of countries including Indonesia, Thailand, the Philippines, Malaysia, Indonesia, India, and China. Singtel is using these partnerships to bridge cultural differences between the countries within Southeast Asia to create a cohesive regional payments solution.

Mobile-First

One of the reasons for the crowded payments space in Southeast Asia is that it’s genuinely a mobile-first part of the world. Consider the case of Indonesia:

Further evidence that Indonesians have embraced mobile-first initiatives comes from social media, with Indonesians having the highest mobile Facebook usage rate worldwide, with 63 million users in 2015. Further projections put Indonesians’ future Facebook access via mobile being almost 99 percent by 2018, showing a real dominance over desktop platforms. The mobile-first path that Indonesia has taken also allows retailers to focus on creating mobile functionality, presenting unique opportunities to dominate in the retail space.

Because some countries in Southeast Asia have massive populations (Indonesia, for example, is north of 250 million), the mobile-first movement is a huge deal. This allows the seller side to have hyper-personalized data and tailor their products even more, as opposed to generalized swaths of information about a huge population. That’s also why so many companies are rushing into the payments space — it’s a relatively low barrier to entry, and the inherently mobile nature makes for better decision-making around what users want.

70-80% of Southeast Asians should be on smartphones by 2021, which would approach U.S. and Japanese levels. But there are already major payments players in those spaces, and not so among the southeastern Asian economies.

Uniquely Southeast Asian

It should also be noted that one quirk of the Southeast Asian marketplace economy is that e-commerce developed before payments or logistics, meaning it spent years as a series of informal markets on platforms like Instagram. Only recently have payments been formalized in the area.

Also critical to understand in Southeast Asia: if you analyze net promoter score, a quality metric for customer advocacy, local payment systems — if fragmented — consistently score higher than major enterprise options based elsewhere. For example, in Indonesia Tokopedia (local) has an NPS of +7 while Amazon’s NPS is -24.

To fully understand how the sharing economy might impact and affect Southeast Asia and other regions where it’s not fully emergent, it helps to more broadly understand the landscape of the sharing/marketplace economy.

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Creditsafe Announces New Partnership with Provenir

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Creditsafe Announces New Partnership with Provenir

“This new approach to data will allow organizations to successfully deploy their risk strategies and in turn allow them to focus on providing their customers with a better experience”

Global business intelligence specialist Creditsafe has announced a new partnership with risk decisioning and data science solution Provenir to provide automated investment and credit risk decisioning to businesses.

The partnership will see Creditsafe incorporate Provenir’s risk decisioning and data science platform into its Connect API, allowing connection to major CRM and ERP systems. This will allow users to be able to access and analyse financial data regarding possible investment and lending opportunities in real-time. Thanks to this new partnership companies will be able to make more informed choices, reducing the risk of bad debt and empowering business growth.  Automating the credit check process will allow businesses to incorporate data concerning a company’s financial health into the onboarding process, reducing the need for manual data checks that take time and increase the likelihood of human error.

Read the full press release here.

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Lost in translation—are risk model deployment challenges slowing you down?

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Lost in Translation—
are risk model deployment challenges slowing you down?

If they are, you’re not alone.

The recent Rexer Data Science Survey found that only 10-15% of companies “almost always” successfully deploy analytics models.

If your organization isn’t in that top 15%, you’re probably already feeling two things:

  1. Frustration caused by deployment delays
  2. Pressure from above to make it happen

The cost of delayed or failed deployment

So, before I get into the challenges preventing rapid deployment and how organizations can overcome these hurdles, let’s answer the bigger question… why should we care about model deployment rates?

There are many reasons why a business needs to be able to deploy a new risk model quickly and easily, but there are a few that really stand out in today’s digital-first world. Rapid deployment:

  1. Drives business growth—Analytics models are a key part of a risk strategy, they help drive business growth by making risk decisioning more accurate, which means more customers and lower default rates.
  2. Improves customer experience—Customers now expect instant everything, risk and analytics models help businesses make real-time decisions and gain customers in increasingly competitive markets
  3. Empowers competitive advantage—Companies that can test and deploy models quickly are able to make iterative changes to models using the most up-to-date data, making them better able to adapt to market demands.

Could you say that in Java, please?

One of the biggest reasons strategic analytics projects are often deployed late is the disconnection between the risk team and the development team.

The root of this developer-data scientist disconnection is that the two different groups literally don’t talk the same language. The modeling languages of choice for data scientists are generally Python, R (both open source languages), and the proprietary SAS. These are not usually the same languages preferred by developers, who favor Java, JavaScript, and variations of C such as C++.

So, typically data scientists create and test their analytics models—say a credit approval and verification application—using their languages. This work is then sent to the development teams, who then often spend a lot of time and costly effort recoding into their own languages so the model can be tested for security, compliance, impact on the infrastructure, and so on. Any changes that need be sent back to the data scientists for further review and approvals will kick off the same lengthy recoding processes, only in reverse.

The result? Fast time-to-market goes out the window. And if projects are deployed late enough, market conditions often will have changed so much that the reasons for deploying in the first place no longer exist, and the project is essentially dead on arrival.

Data delays

Another culprit in the model development and deployment process is the fact that data is very often located all over the organization in protected silos. This is particularly true in highly regulated industries like financial services, where security and privacy concerns meet compliance realities. Historical data may be found in one or more silos, and transactional and production data in others. Data scientists needing elements of all these data have to root around to find and gain access to it.

But that’s not all, the digitization of many types of data has led to a huge range of new data sources, many of which can be highly useful to data scientists when predicting credit risk or fraudulent activity. As each new data source emerges it needs to be integrated into the businesses decisioning solution if it’s to be utilized by analytics models.

While integrations should be simple, many organizations struggle with creating or updating data source integrations due to inflexible technology that requires extensive hardcoding. Each new data source included in a model can result in lengthy delays to model deployment as they need to be completed before the model can be fully tested and pushed to a live environment.

Say hello to your guide and translator: Platform technology

It’s fair to say that many of the delays to risk model deployment are caused by processes, not people. It’s also fair to say that the rapid advancement of technology has made it difficult to keep up with new analytics models to tackle an ever-evolving model. So, what can you do about it?

Well, what if your process problems caused by technology, like having to translate models from one language to another, or manually updating hardcoded integrations, could be solved by technology?

So, instead of your risk team creating a model in one language, then your dev team translating it into another language for your risk engine, you could opt for a model agnostic risk platform instead.

For data scientists and developers ‘talking different languages’, being model agnostic effectively removes the intermediate steps of recoding between the two different teams. Instead data scientists can upload their models directly in their native languages, which allows them to fully utilize new analytical techniques.

These types of platforms help prevent the loss of analytics models that never get deployed due to prolonged development and deployment cycles.

Technology can also be an effective solution for data integration challenges, which both fintechs and traditional financial institutions still struggle with as a result of hardcoded connections that are often built to serve a specific purpose at a specific time.

Today’s digital market requires businesses to be able to create agile technology that can be quickly updated or repurposed throughout an organization to meet many needs.

For optimum flexibility and business agility it’s essential that data integrations can be created, used, reused, and updated quickly and easily. Again, integrations have traditionally relied heavily on over-burdened dev teams for what should be simple adjustments. Instead of following these traditional integration processes businesses now have the opportunity to use technology that empowers business users to handle the integration mapping process.

This means that the risk team can be far less reliant on the dev team for ongoing adjustments as they can easily map source data into analytics models.

Gaining business agility through simplified model deployment processes

What this really comes down to is using technology to simplify business processes and empower people to do more. By using specialized software solutions that remove steps in the model deployment process and reduce the reliance on development your risk teams are able to focus on current problems and initiatives to drive business growth. They’re able to respond more quickly, make changes more easily and implement a risk strategy much more efficiently.

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Dzone: Tom’s Tech Notes: Container Fails [Podcast]

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Dzone: Tom’s Tech Notes: Container Fails [Podcast]

Dzone’s latest podcast examines how devs and ops can go wrong with containers. The podcast features conversations that Dzone’s research analyst Tom Smith has had with software industry experts from around the world. Provenir’s Anand Shah’s joins industry leaders to contribute to this podcast.

Listen to the podcast at Dzone.com.

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Beam Me Up, Scotty: A Day At Work With A Digital Native

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Beam Me Up, Scotty:
A Day At Work With A Digital Native

“Excuse me, sir.”

“Uhh… Are you alright?”

The man sitting in front of my desk had slumped in his chair while I wasn’t looking, his eyes closed.

Seeing as he was well into his 80s, that got me worried. But a light snore soon set my mind at rest.

The guy had just fallen asleep. Phew.

I didn’t blame him, for I had almost fallen asleep myself countless times as I read out middling policies and filled out forms for customers…  by hand.

Time often stood still when I worked in the private banking industry — and people weren’t happy, not on the customer side nor the employees.

Back To The Future

That’s how I felt clocking out of work at the end of my day.

I worked in traditional banking from 2015 to 2017. But stepping into the office felt like traveling back to 1985. It was a time-warp.

I was expected to be physically present at the same place and same time every day for the same amount of hours — whether there was work to be done or not. Phones were to be locked away, and the internet was censored.

But, more importantly, the day-to-day processes were extremely inefficient. Whether it was opening a new bank account, making a deposit or processing a loan, everything was manual from start to finish.

I’d fill in forms by hand then type them up on the aging computer, which meant simple appointments often ran over 2 hours. Decisioning processes typically took 5 to 7 working days, or even longer.

For a guy who had his first internet connection at 11 years old, and was used to web pages loading on their phone in under 3 seconds, this was unfathomable.

There had to be a better way. Well, there was a better way.

So why were we tied to antiquated systems and a rigid, inflexible work schedule?

A New Way To Work

I’m not alone in feeling like this.

Having grown up in a connected world, my generation is accustomed to getting things done faster. But, more to the point, we’ve embraced flexibility from a young age, we’re comfortable taking ownership and we like feeling empowered.

Technology allows us to design our workday the way each of us prefers it. We can get more done without having to sacrifice time with family and friends and other things that are important.

The simple fact is that, in this day and age, there’s no need to build your life around your work. As long as you have a laptop and an internet connection, you can work anywhere, at any time. So, it shouldn’t be surprising that we view the rigid, office-based workplace structure as antiquated and unnecessary.

As Upwork CEO Stephane Kasriel puts it:

“The traditional 9-to-5 office job doesn’t adequately support the lives millennials and Gen Zs want to live. They are flexible-work natives, raised during and after the dotcom bubble, where the acceleration of technology has sped up exponentially over time.”

Taking The Workplace From 1985 To 2019

This year, Generation Z — those born after 1996 — will make up 32% of the global population. The eldest has just finished or are about to finish college. And, by 2025, we’ll make up 31% of the workforce.

Seeing as employees are the face of your company, I think it’s about time we adapt the workplace and bring it in line with the times. Happy employees are more productive, more loyal and more effective. And, ultimately, it’s your customers who’ll benefit.

So what should the modern workplace look like, in my view?

Well, for starters, it’s all about flexibility. We’re more than happy to be connected round the clock. After all, that’s what we’ve been used to almost all our lives. But the beauty of having this level of access is that it can set you free.

A Stanford University study found that, over a 9 month period, flexible workers were happier, achieved more and took fewer sick days. And — would you know it? — they actually worked longer hours.

I’m not surprised.

Working from home makes the day seem to go by much faster. I can enjoy a leisurely lunch and make up for it in the evening. Or, I can deal with an issue Sunday night and take things easier Monday morning. There’s no counting the clock down and feeling like you’re being forced to work.

But, more to the point, the workplace should be about doing things smarter, not harder.

This is not to say we aren’t prepared to roll up our sleeves. We are. A survey run by recruitment website Monster found we expect to work harder than our older siblings the Millennials. But with technology at our fingertips, there’s no reason why repetitive tasks should take over the day-to-day.

Automating admin-heavy processes such as applications, pricing policies, onboarding and decisioning frees up your employees — young and old — to focus on what really matters. It also saves time, saves money and helps you serve your customers better.

And, as a business, isn’t that what you want?

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Data Science in Financial Services: A Guide for the Modern Chief Risk Officer

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Data Science in Financial Services:
A Guide for the Modern Chief Risk Officer

With digitization sweeping through the financial services industry, the role of the chief risk officer is changing quickly. Why? Because new types of risks, increasing consumer demands, and growing competition make the financial landscape much more complex.

What does this mean for the CRO? It means that they need to find new ways to assess risk in this rapidly evolving market: Enter data science.

This whitepaper is the ultimate resource for any financial services leader who wants to learn more about how to successfully integrate data science solutions into their risk strategy. Download the whitepaper today to learn:

  • What data science is
  • The role it can play in reducing risk
  • How to overcome common data science challenges
  • How to get the most business value from any data science project

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The 2018 Dzone Guide to Microservices

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The 2018 Dzone Guide to Microservices

With the continued evolution of Microservices we are seeing more developers beginning to experiment with modular applications in both production and development. Dzone’s latest guide shares how top companies and fellow readers have adopted microservices and the challenges they’ve had to overcome. Look out for comments from Mike LaFleur, Provenir’s awesome Global Head of Solution Architecture.

Download the full guide at Dzone.com.

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The Data Disconnect: Why Even FinTechs Struggle

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The Data Disconnect:
Why Even FinTechs Struggle

Redefining the relationship with data, FinTech industry veteran and Managing Director of Provenir, Paul Thomas explores the data disconnect troubling financial institutions in this in-depth interview.

Paul Thomas has witnessed the data struggle firsthand in his work with both traditional financial institutions as well as disruptive fintech innovators. At first glance, the struggle doesn’t make sense. There’s no shortage of data—most organizations are drowning in data. It’s not the lack of tools that’s the problem—analytics-tools like Python are widely accessible. It’s not even a lack of talent, with some fintech firms employing the brightest data scientists from the most prestigious graduate programs. So what exactly are the issues that prevent financial organizations from fully using data and how can they be solved?

Thomas has a unique, perhaps even renegade, approach to solving data challenges. He believes that organizations need to reimagine their relationship with data and restructure their infrastructure to take advantage of new data sources and cloud-based technology partners.

In a fast-paced and far-reaching interview peppered with many industry examples and anecdotes, Thomas explains why—and most importantly, how—financial services providers can transform how they use data to deliver the products and services consumers want.

Read the full article here >> American Banker

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Saying Yes More: How GM Financial, Yapstone, and Insikt use Risk Analytics and Decisioning to Drive Business Growth

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Saying Yes More:
How GM Financial, Yapstone, and Insikt use Risk Analytics and Decisioning to Drive Business Growth

Provenir clients GM Financial, YapStone, and Insikt talk risk decisioning over on AmericanBanker.com today. The article delves into their risk decisioning processes and uncovers how robust risk analytics allow them to ‘say yes more’.

“To the outside world, loan decisions and payment approvals can seem like a simple yes or no decision: either the application is approved or it’s declined. However, the most successful financial services organizations know that determining a yes, no, or even maybe response requires a robust decisioning process that not only protects all parties, but also drives an organization towards its goals.

In today’s tech savvy world risk decisioning has become an artform that has the power to make or break a financial services organization in a number of ways, from its impact on user experience, to the risks it exposes the business to or protects it from. Businesses who embrace this new risk management artform are developing sophisticated risk decisioning processes that incorporate more than the traditional credit scores we all love to hate.

It’s no secret that digitization has created huge disruption within the financial services industry, replacing traditionally paper-based processes with tech-powered automated systems that make it possible to process loan applications and make payments instantly. But this ‘instant gratification’ culture has also created new opportunities for fraud and increased threats that have the potential to outsmart traditional risk decisioning processes that don’t keep up with the evolving risk landscape.

So how can businesses use risk decisioning not just as a form of protection but also as an opportunity to innovate and grow? GM Financial, Yapstone, and Insikt are three examples of organizations that are using strategic tech partnerships to create sophisticated risk decisioning processes that secure their positions as industry leaders.”

Read the full article at AmericanBanker.com to learn more about how these three innovative businesses are using smarter risk decisioning to drive business growth, expand market opportunities, and improve the consumer experience.

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Veejay Jadhaw Named Chief Technology Officer

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Veejay Jadhaw
Named Chief Technology Officer

We are pleased to announce that Veejay Jadhaw has been named Provenir’s Chief Technology Officer. Veejay was most recently CTO and Head of Digital Innovation at Finastra, the world’s third largest fintech company. Prior to Finastra Veejay held significant roles with SAP and Microsoft. Veejay brings strong technical knowledge and outstanding leadership skills. He will be based in Parsippany, Provenir’s HQ.

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