In years to come, not Gold but Data shall be the most valuable asset known to humanity, and that’s precisely where emerging technologies such as Blockchain, AI and IoT take the lead. Financial institutions like banks, non-bank capital groups or insurance companies have plunged at the opportunity of computing the raw data sets into valuable information.
While the infamous financial crisis of 2008 pushed the enterprises to get smarter, fintech solutions have been steadily sloping upwards. This article explores a few of the most recent applications used by financial institutions to replace the traditional methods.
Accounting on Blockchain for faster and leaner transactions as well as processes
The explosive rise in investments by 2100% upscaled Blockchain’s market value to USD 1.6 Billion in 2017. The Blockchain market value was found to be $30 billion in 2020 which is expected to reach up to $39.7 billion by 2025. In fact, banking alone accounts for USD 300 million and has emerged as the fastest adapters of the trends. Not to miss, the first Blockchain application (Bitcoin) was a financial asset and continues to encourage other finance verticals.
Accounting systems made over Blockchain can eliminate flaws that were present in the traditional procedures. Following the trust mechanism of Blockchain, such a system uses a triple entry system for updating the transaction ledger thereby enabling the SME sector to access high-level accounting services that were previously available only to large enterprises. Rather than maintaining transactional records on privately owned databases, both parties involved updating the transaction over a distributed ledger.
According to Thomas Reuters, finance institutions spend USD 500 million annually to assure customer due diligence. That is, tracking customers with multiple bank accounts and their transactional activity is a lengthy process and not entirely accurate. As one of the biggest pain points of the finance world, KYC (Know Your Customer) processes suffer from the never-ending manual undertaking. The Finance IT solutions in the face of Blockchain are resolving the complexity by leveraging a unique ID that can be used for a mutual exchange of customer information amongst different financial institutions without conflicting with data privacy of either party.
AI-driven tools for better Predictive Thinking
High-value loans released within minutes
Evaluating a customer’s eligibility against a requested loan application is a tedious process spanning across metric derivations such as income, savings, age, banking history and the type of employment. Usual delays in acknowledging the request often push the customer to withdraw the applications and explore alternatives – hundreds of such leads that don’t mature converge to significant business loss. AI systems are already cutting down on the manual effort to scan and perform verification checks; empowering the agents to authenticate the customer’s capacity and respond within minutes.
Besides closing more deals faster for the banks, customers benefit from on-demand loan needs being addressed in relatively lesser time.
Natural Language Processing (NLP) powered chatbots
43% of digital banking users in the US prefer to use a live chat for communicating. This is an important trend brewing to go mainstream. Chatbots can stimulate human-like conversation by computing thousands of inputs (text and voice) and address customer grievances without actually deploying manual agents. Customer Support units at banks receive the highest volume of queries while most of these are almost similar to each other. Offering more scope for automation, Chatbots engineered by Machine Learning and Natural Language Processing (NLP) can process queries and resolve most of the critical issues without any human intervention.
Revolutionized Fraud detection
Maturing from catching any violation to predetermined rules only, Machine Learning has gone a step ahead in identifying suspicious transactions. For instance, if a high-value debit transaction is executed from an account that generally does low-value transactions, AI algorithms won’t process the transaction until the account owner confirms it. Predictive Thinking continues to learn and enhance its knowledge base for sharper analysis and abnormality identification.
Internet of Things for Accurate Information gathering
Insurance companies are tracking your routine activity in detail. Thanks to the seamless adoption of the IoT, insurers are following a Usage-Based Insurance (UBI) Telematics Program that uses a dongle (or any other mobile device) to capture details of your driving activity. While costing gets accurate, drivers with a good record on the road are rewarded with lesser premium amounts.
As of now, trillions of observations in the form of snapshots and text records have been captured as part of smarter Insurance IT solutions. Coupled with AI, such extensive data is computed to derive the patient’s behavioral data.
Google’s Next has partnered with various insurance providers to identify the authenticity of the insurance costs claimed by the customer. For instance, where the house has caught fire, Next immediately notifies the customer as well as the insurer, the inbuilt sensors detect the intensity of the fire as fast, medium and slow-burning. Such accurate costing has helped insurers save up to 10% in premium payouts. This is just the beginning.
Finance drives the world and adapts to changes faster than anyone else. As the criticality of routine transactions increases, IT solutions are inevitably forced to evolve and deliver more profound insights securely and more smartly. Soon, all of the above mentioned technologies would make a noticeable impact in the financial sector and pave way for newer methods for financial transactions.