Fintech services

Home » Fintech services

What is Fintech?

/ˈfɪntɛk/

fintech

fin-tech

Even in an environment of rapid change to the design, delivery and providers of financial services, the core needs those services fulfill remain the same. We have identified six core functions that comprise Fintech services (financial technology):

Cashless world

New consumer functionalities are being built on existing payment systems and will result in meaningful changes in customer behaviour.
Decentralised payment schemes leverage cryptographic protocols to transfer value virtually in a secure, low cost, near-instantaneous manner.

New consumer functionalities are being built on existing payment systems and will result in meaningful changes in customer behaviour.

Integrated billing

Mobile ordering & payment apps
Integrated mobile shopping apps

Next generation security

Biometrics / location-based identification
Tokenisation standards

Insurance Disaggregation

Emergence of online insurance marketplaces and homogenisation of risks will force big changes in insurers’ strategies.
Ubiquity of connected devices will enable insurers to highly personalise insurance and proactively manage clients’ risks.

Sharing economy

As sharing economies emerge from pay-as-you-go rentals to shared vehicles and houses, the concept of ownership may radically change, challenging traditional insurance models developed based on one-to-one ownership structure.

Self driving cars

Fully or partially self-driving cars are emerging leveraging smart sensors, connectivity and machine-to-machine communications. This will considerably reduce the risks associated with driving and may shift the principal of insurance from drivers to manufacturers.

Internet-of-things

Data from vehicles, properties and individuals are gathered and analysed in real-time to provide timely, relevant insights and information to users.

Deposits & Lending

New lending platforms are transforming credit evaluation and loan origination as well as opening up consumer lending to nontraditional sources of capital.

P2P

Alternative lenders leverage online platforms and legal contracts to provide direct matching of funds between savers and borrowers.

By acting as online marketplaces P2P lenders facing lower funding costs than traditional depository lenders.

Banking as Platform (API)

Banking-as-platform movement aims to standardise APIs across financial institutions allowing 3rd party developers to easily build and integrate customer-facing enhancements to the institutions’ core offerings.

Evolution of Mobile Banking

Free of legacy systems, non-traditional players are emerging to offer mobile apps that make financial transactions even more effortless for customers (e.g., P2P money transfer, photo bill payment, voice recognition)

Capital Raising

Crowdfunding platforms are widening access to capital raising activities, making the overall ecosystem richer.

Empowered Angel Investors

Some alternative funding platforms leverage the expertise of more experienced individual investors in certain fields (e.g., angel investors) by providing them an opportunity to lead funding for desired investments.

Some platforms allow these “lead” investors to gain additional income through fees, similar to carries paid to general partners of private equity firms.

Crowd Based

Alternative funding platforms provide a marketplace for individual investors to directly discover and invest in investment opportunities.

Investment opportunities are typically only funded when a pre-determined target is met, to weed out less credible or less promising opportunities through “crowd’s approval”

Alternative funding platforms

Alternative funding platforms provide a number of customisable parameters for businesses to adjust and easily design funding options desirable for them (e.g., term, equity share)

Moreover, some platforms allow businesses to build in unique clauses, such as rewards, to make them appealing to investor segments

Investment management

Robo-advisors are improving accessibility to sophisticated financial management and creating margin pressure, forcing traditional advisors to evolve. These innovations will create pressures for the wealth management industry to improve the value delivered while broadening access to more customers.

Automated Management and Advice

Offers high-value advisory services on portfolio allocation and money management at low costs based on automated analysis.

Automates the management of a personalised investment portfolio based on individual needs. Provides aggregated view and analysis of
multiple accounts

Social Trading

Empowers individual investors to build and share investment strategies and portfolios with other investors.

Empowers individual investors to share their opinions and gain market insights from the opinions shared by the crowd.

Retail Algorithmic Trading

Enables investors to easily build, test and execute trading algorithms with limited technical knowledge and infrastructure.

Provides platforms for sophisticated investors to share trading algorithms with others.

Market provisioning

As the popularity of high frequency trading declines, the focus of algorithmic trading may shift to smarter, faster response to real life events. New information platforms are improving connectivity among market constituents, making the markets more liquid, accessible, and efficient.

Machine Accessible Data

Process news feeds through algorithms in real-time without human interpretation (machine-readable news)

Discover major events faster than the news through social media / sentiment analysis

Big data

Access extensive real-time data sets through specialised databases

Uncover predictive insights on market movements based on correlations mapping

Update and access insights in real-time through cloud-based analytics

Artificial Intelligence / Machine Learning

Ask questions, discover and test hypotheses, and make decisions automatically based on advanced analytics on extensive data sets

Self-correct and continuously improve trading strategies with minimal human interaction through machine learning and prescriptive analytics