Financial Technology has continued to gain widespread adoption across the world, with different technologies being applied to meet consumer demands, regulatory approvals, and security requirements.

Despite the growing concerns with the macroenvironment and the suppressed public valuations in FinTech, M&A activity has marginally increased as corporates and PE firms look for deals, given the declining valuations. Many start ups are choosing to sell as an alternative to holding a down round.

In this article, we highlight the key trends that have emerged in the FinTech sector.

Machine Learning is Influencing the Landscape of Insuretech

74% of customers would like to interact with modern technology and appreciate the computer-generated system of insurance advice.

Machine learning algorithms can spot “red flags” more easily in fraudulent claims and risk management data, giving workers more time to spend on unique cases. The overall result is that high-volume, low-cost insurance claims like broken windshields can be quickly resolved, and knowledge workers can spend more time on more complex claims and fraud detection.

Digital claims can reduce expenses by 25-30% by improving effective claim handling and increasing customer satisfaction. Transforming the entire claims process requires a fresh look at the current process.

Companies that adopt new-age technology to develop innovative products, harness cognitive learning insights from a myriad of data points, streamline processes, and more importantly, personalise the entire customer experience will be the winners in the AI dominated insurance space.

Acquisitions in this space include that of Metromile Enterprise, a developer of insurance software intended for property and casualty insurance companies by EIS group software and Unemployment Tracker by Trak Capital.

61% of market leaders expect alternative data will experience more widespread adoption by 2025.

Alternative Data Providing an Edge for Financial Players

The demand for alternative data has been outpacing supply as active asset managers continue to look for an edge to outperform markets, as well as compete with low-cost index funds where investor spending on alternative data has grown exponentially as of recent.

By 2025, it’s predicted people will generate 463 exabytes of data each day. With this staggering amount of data on the horizon, alternative data analysis is primed to become more prevalent than ever over traditional sources of data such as quarterly earnings and SEC filings.

Market participants today agree on two seeming certainties for the near future: consolidation and expansion.  Currently over 1,000 alternative data providers are attempting to differentiate themselves in a market around $2.7bn in size, with consolidation amongst the existing field appearing inevitable. The constant birth of new datasets will also create a ‘comet’s tail’ that will always keep the picture from simplifying too much.

Acquisitions in this vertical include that of Korean based Aicel Technologies, a developer of an alternative data platform designed for financial markets by US based FiscalNote, an information services company focused on global policy and market intelligence.

 

The Need for Relationship Automation in Capital Markets

As relationship structures become increasingly complex and with most work today taking place in the digital space, it is critical to invest in the right tools to foster a culture of transparency.

Dealmakers need to consistently nurture relationships, enhance client communication, and support intentional collaboration. Despite dealmakers agreeing on the value of their professional relationships, oftentimes they fail to fully leverage them.

Without the help of technology to support the relationship management process, firm leaders, and dealmakers alike struggle to keep track of who knows whom, how well they’re acquainted, how these relationships are changing or how to strengthen them. The sooner capital markets users have access to a CRM that understands their complex workflows, with the right data integrations already in place, the faster they will start deriving value from real-time intelligence and a 360-degree view of their clients.

Acquisitions in this vertical include that of US-based Altvia by Marlin Equity Partners and SS&C’s takeover of Tier 1 Financial Solutions.

FinTech businesses are increasingly looking at partners to build bespoke solutions, so they can differentiate themselves from other companies that have very similar business models.

The Rise of Blockchain-enabled Wealthtech

Solutions based on distributed ledger technology (DLT) and blockchain have taken great strides in the past year. Real-world offerings are online and available and companies in the financial sector are taking the first steps in the process of adoption. The focus at these companies is now less on the technology itself and more how they can digitally transform for maximum benefit.

Moreover, the tokenisation feature in DLTs with smart contract capability makes it easier to inject liquidity into traditional assets initially thought to be illiquid such as real estate and collectibles. These assets are more accessible and comparatively cheaper in the secondary market with digitisation and liquidity.

In a digitally transformed industry that makes use of DLT infrastructures, wealth and asset managers can deliver hyper-personalised services to more channels and more underserved affluent bands than is feasible today. Investors now expect high levels of customisation, transparency, and information on demand; a managers’ capacity to grow at scale while still providing made-to measure services is inherent in this new world.

Overall, DLT reshapes wealth management to be a more innovative and responsive industry via a data-based and client-centric business model.

Next Steps

To find out more about the latest M&A trends in the financial technology sector, view our latest Q3 Financial Technology M&A Report here.

Looking to buy or sell your financial technology business? Get in touch with one of our specialist M&A Advisors here.