By Admin / October 26, 2020
In years to arrive, Gold and not Data shall be the most valued asset known to humanity, and that’s precisely where emerging technologies such as Blockchain, AI and IoT take the lead. Financial institutions, be it 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. And leading the list of challenges includes so that high NPA (Non-Performing Assets) counts and other credit challenged customers could be contained.
Here’s a quick run through at few most talked about applications used by financial institutions.
Finance ERP over Blockchain – faster and leaner transactions and processes
The explosive rise in investments by 2100% upscaled Blockchain’s market value to USD 1.6 Billion in 2017. Banking alone accounts for USD 300 million and has emerged as the fastest adapters of the trends. The first Blockchain application (Bitcoin) was a financial asset and continues to encourage other finance verticals.
For example, Oracle Finance cloud could experiment with an accounting system on the Blockchain framework with a vision to to eliminate inconsistencies in the traditional procedures. Following the trust mechanism of Blockchain, the ideated platform could uses a triple entry system for updating the transaction ledger thereby enabling the SME sector to access high-level accounting services previously available to large enterprises only. Rather than maintaining transactional records on privately owned databases, both parties involved updating the transaction in a shared book.
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.
There will be more AI driven tools for better Predictive Thinking
Evaluating a customer’s eligibility against 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 to 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.
Chatbots – Natural Language Processing
The software could stimulate human 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 can process queries and resolve most of the critical issues without any human intervention. Needless to day that the best ERP finance solution would inculcate the feature.
Revolutionized Fraud detection
Maturing from catching any violation to pre-determined rules only, Machine Learning has gone a step ahead in identifying suspicious transactions. That is, 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 identifying any abnormality.
Internet of Things – Real-Time Data Streaming Across Devices – Accurate Information and Lesser Costing
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 an instance where the home has caught fire, Nest immediately notifies the customer as well as the insurer, the inbuilt sensors detect the intensity of fire – fast, medium and slow burning. Such accurate costing has helped insurers save up to 10% in premium payouts. This is the just the beginning.
On a final note,
Finance drives the world and adapts to changes faster than anyone else. As the criticality of the routine transactions increases, IT solutions need to mature and deliver more profound insights in a secured and smarter way.