More investors are setting their sights on the financial technology (Fintech) arena. According to consulting firm Accenture, investment in Fintech firms rose by 10 percent worldwide to the tune of $23.2 billion in 2016.

China is leading the charge after securing $10 billion in investments in 55 deals which account for 90 percent of investments in Asia-Pacific. The US came second taking in $6.2 billion in funding. Europe, also saw an 11 percent increase in deals despite Britain seeing a decrease in funding due to the uncertainty from the Brexit vote.

The excitement stems from the disruption of traditional financial institutions (FIs) such as banks, insurance, and credit companies by technology. The next unicorn might be among the hundreds of tech startups that are giving Fintech a go.

What exactly is going to be the next big thing has yet to be determined, but artificial intelligence (AI) will play a huge part.

Stiffening competition

The growing reality is that, while opportunities are abound, competition is also heating up.

Take, for example, the number of Fintech startups that aim to digitize routine financial tasks like payments. In the US, the digital wallet and payments segment is fiercely competitive. Pioneers like PayPal see themselves being taken on by other tech giants like Google and Apple, by niche-oriented ventures like Venmo, and even by traditional FIs.

Most recently, the California-based robo-advisor, Wealthfront, has added artificial intelligence capabilities to track account activity on its own product and other integrated services such as Venmo, to analyze and understand how account holders are spending, investing and making their financial decisions, in an effort to provide more customized advice to their customers.  Sentient Technologies, which has offices in both California and Hong Kong, is using artificial intelligence to continually analyze data and improve investment strategies.  The company has several other AI initiatives in addition to its own equity fund.  AI is even being used for banking customer service. RBS has developed Luvo, a technology which assists it service agents in finding answers to customer queries. The AI technology can search through a database, but also has a human personality and is built to learn continually and improve over time.

Some ventures are seeing bluer oceans by focusing on local and regional markets where conditions are somewhat favorable.

The growth of China’s Fintech was largely made possible by the relative age of its current banking system. It was easier for people to use mobile and web-based financial services such as Alibaba’s Ant Financial and Tencent since phones were more pervasive and more convenient to access than traditional financial instruments.

In Europe, the new Payment Services Directive (PSD2) set to take effect in 2018 has busted the game wide open. Banks are obligated to open up their application program interfaces (APIs) enabling Fintech apps and services to tap into users’ bank accounts. The line between banks and fintech companies are set to blur so just about everyone in finance is set to compete with old and new players alike.

Leveraging Digital

Convenience has become a fundamental selling point to many users that a number of Fintech ventures have zeroed in on delivering better user experiences for an assortment of financial tasks such as payments, budgeting, banking, and even loan applications.

There is a mad scramble among companies to leverage cutting-edge technologies for competitive advantage. Even established tech companies like e-commerce giant Amazon had to give due attention to mobile as users shift their computing habits towards phones and tablets. Enterprises are also working on transitioning to cloud computing for infrastructure.

But where do more advanced technologies such as AI come in?

The drive to eliminate human fallibility has also made artificial intelligence (AI) driven to the forefront of research and development. Its applications range from sorting what gets shown on your social media newsfeed to self-driving cars. It’s also expected to have a major impact in Fintech due to potential of game changing insights that can be derived from the sheer volume of data that humanity is generating. Enterprising ventures are banking on it to expose the gap in the market that has become increasingly small due to competition.

All about algorithms

AI and finance are no strangers to each other. Traditional banking and finance have relied heavily on algorithms for automation and analysis. However, these were exclusive only to large and established institutions. Fintech is being aimed at empowering smaller organizations and consumers, and AI is expected to make its benefits accessible to a wider audience.

AI has a wide variety of consumer-level applications for smarter and more error-free user experiences. Personal finance applications are now using AI to balance people’s budgets based specifically to a user’s behavior. AI now also serves as robo-advisors to casual traders to guide them in managing their stock portfolios.

For enterprises, AI is expected to continue serving functions such as business intelligence and predictive analytics. Merchant services such as payments and fraud detection are also relying on AI to seek out patterns in customer behavior in order to weed out bad transactions.

People may soon have very little excuse of not having a handle of their money because of these services

Concerns Going Forward

While artificial intelligence holds the promise of efficiency, better decision-making, stronger compliance and potentially even more profits for investors, the technology is young. Banks need to find ways to lower costs and technology is the most obvious answer. A logical response by banks is to automate as much decision-making as possible, hence the number of banks enthusiastically embracing AI and automation. But the unknown risks inherent in aspects of AI have not been eliminated. According to a Euromoney Survey and report commissioned by Baker & McKenzie, out of 424 financial professionals, 76% believe that financial regulators are not up to speed on AI and 47% are not confident that their own organizations understand the risks of using AI.  Additionally an increasing reliance on artificial intelligence technologies comes with a reduction in jobs.  Many argue that the human intuition plays a valuable role in risk assessment and that the black box nature of AI makes it difficult to understand certain unexpected outcomes or decisions produced by the technology.

Towards the future

With the stiff competition in Fintech, ventures have to deliver a truly valuable products and services in order to stand out. The venture that provides the best user experience often wins but finding this X factor has become increasingly challenging.

The developments in AI may provide that something extra especially if it could promise to eliminate the guess work and human error out of finance. It’s for these reasons that AI might just hold the key to what further Fintech innovations can be made.

Long considered an impenetrable fortress dominated by a few well-known names, the banking and financial services industry is currently riding a giant wave of entrepreneurial disruption, disinter-mediation, and digital innovation. Everywhere, things are in flux. New, venture-backed arrivals are challenging the old powerhouses. Banks and financial services companies are caught between increasingly strict and costly regulations, and the need to compete through continuous innovation.

How does an entire industry remain relevant, authoritative, and trustworthy while struggling to surmount inflexible legacy systems, outdated business models, and a tired culture? Is there a way for banks and other traditional financial services companies to stay on budget while managing the competitive threat of agile newcomers and startups that do business at lower costs and with better margins? The threat is real. Can established institutions evolve in time to avoid being replaced? What other strategies can protect their extensive infrastructures and win the battle for the customer’s mind, heart, and wallet?

Financial technology, or fintech, is on fire with innovation and investment. The movement is reshaping entrepreneurial businesses and shaking the financial industry, reimagining the methods and tools consumers use to manage, save, and spend money. Agile fintech companies and their technology-intensive offerings do not shy away from big data, analytics, cloud computing, and machine learning, and they insist on a data-driven culture.

Consider a recent Forbes article by Chance Barnett, which quantifies fintech startup investments at $12 billion in 2014, quadrupling the $3 billion level achieved a year earlier. Adding to the wonderment, crowdfunding is likely to surpass venture capital in 2016 as a primary funding source. And people are joining the conversation. Barnett writes, “According to iQ Media, the number of mentions for ‘fintech’ on social media grew four times between 2013 and 2014, and will probably double again in 2015.” All of this activity underscores how technology is rattling the financial status quo and changing the very nature of money.

Yesterday’s Bank: A Rigid Culture, Strapped for Funds

Established banking institutions are strapped. The financial meltdown in 2008 questioned their operations, eroded trust, and invited punitive regulation designed to command, control, and correct the infractions of the past. Regulatory requirements have drained budgets, time, and attention, locking the major firms into constant compliance reporting. To the chagrin of some, these same regulations have also opened the door for new market entrants, technologies, platforms, and modalities—all of which are transforming the industry.

For traditional banking institutions, focus and energy for innovation are simply not there, nor are the necessary IT budgets. Gartner’s Q3 2015 forecast for worldwide IT spending growth (including all devices, data center systems, enterprise software, IT and Telecom services) hints at the challenge banks face: global IT spending is now down to -4.9%, even further from the -1.3% originally forecast, evidence of the spending and investment restraint we see across the financial landscape.

With IT budgets limited, it is hard to imagine banking firms easily reinventing themselves. Yet some are doing just that. Efficient spending is a top strategic priority for banking institutions. Many banks are moving away from a heavy concentration on compliance spending to instead focus on digital transformation, innovation, or collaboration with fintech firms. There is a huge amount of activity on all fronts. To begin, let’s review the competitive landscape of prominent fintech startups.

Data Sciences Intervention

Digital data has snowballed, with the proliferation of the internet, smartphones and other devices. Companies and governments alike recognize the massive potential in using this information – also known as Big Data – to drive real value for customers, and improve efficiency.

Big Data could transform businesses and economies, but the real game changer is data science.

Data science goes beyond traditional statistics to extract actionable insights from information – not just the sort of information you might find in a spreadsheet, but everything from emails and phone calls to text, images, video, social media data streaming, internet searches, GPS locations and computer logs.

“Data sciences enables us to process data better, faster and cheaper than ever

With powerful new techniques, including complex machine-learning algorithms, data science enables us to process data better, faster and cheaper than ever before.

We’re already seeing significant benefits of this – in areas such as national security, business intelligence, law enforcement, financial analysis, health care and disaster preparedness. From location analytics to predictive marketing to cognitive computing, the array of possibilities is overwhelming, sometimes even life-saving. The New York City Fire Department, for example, was one of the earlier success stories of using data science to proactively identify buildings most at risk from fire.

Unleashing the power of Advanced Data Mining using Data Sciences

For banks – in an era when banking is becoming commoditized – the data mining provides a massive opportunity to stand out from the competition. Every banking transaction is a nugget of data, so the industry sits on vast stores of information.

By using data science to collect and analyses Data, banks can improve, or reinvent, nearly every aspect of banking. Data science can enable hyper-targeted marketing, optimized transaction processing, personalized wealth management advice and more – the potential is endless.

A large proportion of the current Data Mining projects in banking revolve around customers – driving sales, boosting retention, improving service, and identifying needs, so the right offers can be served up at the right time.

“Data sciences can help strengthen risk management such as cards fraud detection

Banks can model their clients’ financial performance on multiple data sources and scenarios. Data science can also help strengthen risk management in areas such as cards fraud detection, financial crime compliance, credit scoring, stress-testing and cyber analytics.

The promise of Big Data is even greater than this, however, potentially opening up whole new frontiers in financial services.

Seamless experience for customers

Over 1.7 billion people with mobile phones are currently excluded from the formal financial system. This makes them invisible to credit bureaus, but they are increasingly becoming discoverable through their mobile footprint. Several innovative Fintech firms have already started building predictive models using this type of unconventional data to assess credit risk and provide new types of financing.

While banks have historically been good at running analytics at a product level, such as credit cards, or mortgages, very few have done so holistically, looking across inter-connected customer relationships that could offer a business opportunity – say when an individual customer works for, supplies or purchases from a company that is also a client of the bank. The evolving field of data science facilitates this seamless view.

Blockchain as the new database

Much more is yet to come. Blockchain, the underlying disruptive technology behind cryptocurrency Bitcoin, could spell huge change for financial services in the future. Saving information as ‘hash’, rather than in its original format, the blockchain ensures each data element is unique, time-stamped and tamper-resistant.

The semi-public nature of some types of blockchain paves the way for an enhanced level of security and privacy for sensitive data – a new kind of database where the information ‘header’ is public but the data inside is ‘private’.

As such, the blockchain has several potential applications in financial markets – think of trade finance, stock exchanges, central securities depositories, trade repositories or settlements systems.

Data analytics using blockchain, distributed ledger transactions and smart contracts will become critical in future, creating new challenges and opportunities in the world of data science.