The financial technology platform, TIFIN confirmed recently that the company has secured $109 million in its Series D funding round to expand its operations. Franklin Resources and Motive Partners participated in the investment round.

Additionally, TIFIN’s existing investors enhanced their investment in the fintech platform. In October last year, Hamilton Lane joined TIFIN as an investor for the company’s Series C round. As part of the recent transaction, Rob Heyvaert, the Founder and Managing Partner of Motive Partners, will join the Board of TIFIN.

TIFIN has almost doubled its valuation since the company’s Series C round. Founded in 2018, TIFIN delivers a personalized investor experience through technology-driven solutions.

"As we focus on identifying and growing value within the financial technology sector, it is critical to have an eye on the emerging technologies that can play a crucial role in the reinvention across the industry. TIFIN's pedigree in overlaying data &  analytics  Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term to drive personalization improvements across businesses is just one area that we believe will be essential in building further value within our portfolio companies. Our team of Investors, Operators and Innovators look forward to partnering with Vinay and the talented TIFIN team to deliver the next generation of financial technology infrastructure," said Rob Heyvaert, the Founder & Managing Partner of Motive Partners.

Expansion Plans

According to the details shared by TIFIN, the fintech firm is planning to expand its presence outside the US. The funding will help TIFIN in the development of innovative products to facilitate investors. Vinay Nair, the Founder and CEO of TIFIN, believes that the use of AI and NLP will simplify the user experience.

“We are delighted to have Franklin Resources and Motive Partners join us on this journey, as well as Rob joining our Board. We look forward to working with them and learning from their globally recognized expertise and  connectivity  Connectivity Connectivity is defined as a term used for connecting devices to each other. In most cases, this refers to computer networking and more specifically includes bridges, routers, switches, gateways, and service as well as local networks. Connectivity can refer to simple forms, such as connecting a home or office to the internet or even connecting a digital camera to a computer or printer. Connectivity in FinanceConnectivity has taken on new meaning with the growth of fintech and Big Data collection. Today, financial institutions are often completely dependent on technology and data. This is more important than ever to improve, make transfers, lend, invest, and receive payments. Digital and mobile banking services also increase the level of customer convenience and accessibility. Blockchain assists with transactions, artificial intelligence helps with making smart investments, and multifactor authentication protects sensitive financial data. A blockchain is a form of connectivity, while connectivity is key to fintech disruption. Financial businesses need lightning-fast, low-latency, and secure networks to meet the challenges of fintech. A well-designed fiber-optic network offers exceptional connectivity. The superior connectivity provided by an enterprise-level fiber-optic network improves customer satisfaction, bolsters a financial organization’s reputation, and enables digital transformation through fintech. Today, connectivity providers are adapting financial markets by accelerating speedy networks such as 5G and alternatives. Connectivity also bridges brokers with liquidity providers to get fast trade execution. In this scenario, brokers can source liquidity from a single or multiple source, thereby delivering to their clients enough market depth for their orders to get filled. The main characteristic of liquidity is its depth, which will determine how quickly and how big of an order can be executed via the trading platform. Connectivity is defined as a term used for connecting devices to each other. In most cases, this refers to computer networking and more specifically includes bridges, routers, switches, gateways, and service as well as local networks. Connectivity can refer to simple forms, such as connecting a home or office to the internet or even connecting a digital camera to a computer or printer. Connectivity in FinanceConnectivity has taken on new meaning with the growth of fintech and Big Data collection. Today, financial institutions are often completely dependent on technology and data. This is more important than ever to improve, make transfers, lend, invest, and receive payments. Digital and mobile banking services also increase the level of customer convenience and accessibility. Blockchain assists with transactions, artificial intelligence helps with making smart investments, and multifactor authentication protects sensitive financial data. A blockchain is a form of connectivity, while connectivity is key to fintech disruption. Financial businesses need lightning-fast, low-latency, and secure networks to meet the challenges of fintech. A well-designed fiber-optic network offers exceptional connectivity. The superior connectivity provided by an enterprise-level fiber-optic network improves customer satisfaction, bolsters a financial organization’s reputation, and enables digital transformation through fintech. Today, connectivity providers are adapting financial markets by accelerating speedy networks such as 5G and alternatives. Connectivity also bridges brokers with liquidity providers to get fast trade execution. In this scenario, brokers can source liquidity from a single or multiple source, thereby delivering to their clients enough market depth for their orders to get filled. The main characteristic of liquidity is its depth, which will determine how quickly and how big of an order can be executed via the trading platform. Read this Term in our space. We are also grateful for the support from existing investors including Hamilton Lane and JP Morgan,” Nair said.