The new languages that are exciting fintech geeks world over

<p>With Big Data and Artificial Intelligence (AI) coming together, it has created a thriving ecosystem for intelligent and highly automated applications which are based on data analytics, pattern recognition, image processing, and natural language processing. What are the technologies which excite fintech geeks?  Today’s accountants and financial experts excel at tools that handle finances, taxes […]</p>

With Big Data and Artificial Intelligence (AI) coming together, it has created a thriving ecosystem for intelligent and highly automated applications which are based on data analytics, pattern recognition, image processing, and natural language processing. What are the technologies which excite fintech geeks? 

Today’s accountants and financial experts excel at tools that handle finances, taxes and bills of individuals or companies. These experts are constantly on a lookout for tech innovations and disruptions which they evaluate, run pilots and become early adopters of. The plethora of promising technologies today can transform not just finance industry but the world at large.

The confluence of Big Data and Artificial Intelligence (AI) has created a thriving ecosystem for intelligent and highly automated applications based on data analytics, pattern recognition, image processing, and natural language processing. While these technologies have extensive cross-industry applications, the focus here is specific to the fintech world.

Machine Learning (ML)

ML uses algorithms that emulate human thinking to enable computational machines to learn from data and from other machines. It empowers machines to automatically detect patterns buried in data to provide actionable insights. In our highly connected world, the Internet of Things (IoT) is churning out data in torrents. Like fresh water, this data is a precious resource, which unless harnessed and channelled effectively, disappears into the saline seas or the archives. This tsunami of data can be overwhelming if it requires human programming at every turn to manage it. When algorithms guide machines to manage the data themselves, then the process becomes exponentially faster.

ML insights have been applied to credit management, lending decisions, fraud detection, and better identity management. ML and AI also offer enormous potential to SMBs. Tasks that are tedious and repetitive in nature can be performed more efficiently by machines that can sift through financial data much faster and provide reliable outcomes. Human error, fraud and duplication of effort are eliminated, freeing up business owners and their financial teams to focus on more creative and challenging work.

For example, applying machine learning has helped ease the tax filing process by offering informed advice to customers and cutting the time taken by 40 percent. Arduous data entry and audit related tasks can be left to automated systems, and accountants can instead use their skills to leverage business intelligence from data and help SMBs with high level decisions about improving their cash flow and invoice management, and future growth planning.

Conversational UI (CUI)

Another development in the AI-enabled ecosystem that will disrupt the customer experience is Conversational UI. Thus far, the onus on using a product or service has been largely on customers, who have to struggle to understand how the expert engineers mean for the product or service to be used. But now, CUI, built on natural language processing, allows customers to interact with apps in a manner as natural as speaking.

Instead of navigating a complex series of menu options to generate reports of payments, imagine saying or typing a straightforward command like “Get me all invoices for the first six months of 2017”. This invokes the Interactive Virtual Assistant (IVA) to parse the command and provide the results. The learning curve for becoming productive with tools and software becomes hugely simplified.  This technology also extends to make customer service much more effective. Chatbots can help customers more efficiently as they use machine power to process massive datasets to serve up the right information. Given that a majority of customers today, particularly the younger generations, prefer not have to use the telephone for customer service, this technology provides both an improved customer experience as well as a means of reducing operational costs.

Blockchain

This technology is groundbreaking enough that organisations across the globe are evaluating and developing pilots based on it. Similar to how the TCP/IP protocol helped develop the internet into a global connected network that is the basis for all technology today, blockchain has the potential to provide a networked, borderless, decentralised, “ledger” or database to record and maintain all types of digital transactions in an encrypted and tamper-proof manner. Doing away with centralised databases or clearing houses that maintain authenticated data eliminates these points of failures that are vulnerable to hacking and fraud.

Each “block” in the chain maintains a version of the encrypted digital data or transaction (which could be a birth certificate, land title, digital payment, bank transaction, etc.) and is verified by all other blocks. A compromised or corrupted block is quickly detected since it cannot be verified against other blocks. In what sounds contrary, this “trustless” and transparent system, where no one entity bears the responsibility of being trusted, provides the tamperproof and immutable foundation for applications in the sensitive areas of finance, asset management, logistics and transportation, regulatory compliance, and much more.

Financial organisations, with traditionally centralised databases vulnerable to cyber-attacks, view this technology as a way of reducing fraud. Malicious attempts on a block would automatically become part of the historical data of the block, making it easily detectable and also providing clues about the perpetrators. Blockchain technology could also allow banks to deal directly with each other for payment transactions rather than going through a traditional “trusted” third-party mechanism like RTGS or NEFT which adds up to huge savings. Yet another area where blockchain could provide huge savings and efficiencies is the Know Your Customer (KYC) process. Fintech companies spend a great deal of time and money to comply with this process, and can face severe penalties if they are found lacking. But in a block-chained system, a bank that has KYC’ed a new customer can create a block with all the KYC documents and compliance statements. This is now available to other financial organisations, who don’t have to repeat the process for a known customer entity. While much work in standardisation is needed before blockchain becomes production ready, there is enough interest and investment to make it happen.

Virtual Reality (VR) and other IoT related technologies like wearables also show great promise towards delivering a superior, immersive customer experience. Many of us in the financial industry have been among the early adopters when it comes to disruptive technologies, and our entrepreneurial attitude towards evolving technology often makes us technology pioneers.

Shares