The metaverse is steering the next wave of digital transformation, which will provide insurers with powerful technology tools for differentiation as well as challenges to navigate. In the years ahead, the rise of the metaverse will begin to influence every facade of insurance, from the workforce experience to distribution, marketing, products, revenue pools, and operations.

Buy now, pay later (BNPL) is a type of short-term financing provided to consumers to purchase instantly and pay at a future date. The process involves multiple players, such as consumers, financiers, and merchants. The financier carries out a soft credit check on the customer and returns a decision within seconds. Financiers pay merchants on behalf of consumers when they purchase goods or services. The consumers later repay these payments over time in equal periodic installments.

Governance plays a pivotal role in any industry, domain, or technology, from operational governance to strategic governance. Any governance strategy can be effective only when you have the data for effective decision making and decision intelligence. With the advent of technology, decision support has evolved to decision augmentation and is evolving towards better decision automation, and every decision is tied to metrics, KPIs, and dashboards.

Decentralized Finance (DeFi) is a way of conducting finance-related activity using blockchain technology. It is a fast-emerging segment where many decentralized apps can be integrated and can allow anyone to conduct financial transactions by making use of public blockchain technology. It is increasingly being seen as a viable alternative to the conventional intermediary-focused approach of centralized systems.

The milieu of mobile applications is intensifying across all business sectors in the world we currently live in. It is because of these users; the world is seeing high usage of mobiles to the tune of billions of transactions. Organizations are prepared to take whatever measures are necessary and develop apps that are adored by their potential users to tap into these mobile users and turn them into a loyal customer base.

Artificial intelligence (AI) is advancing at a breakneck pace, and it is swiftly emerging as a potential disruptor and vital enabler for almost every business in every sector. At this point, the technology itself is not a barrier to the mainstream use of AI; rather, it a collection of challenges that, unfortunately, are far more human, such as ethics, governance, and human values, are.

The inventive and ever-evolving nature of technology creates as many opportunities as obstacles. The fact that software permeates every part of life demonstrates that corporate leaders should closely monitor the level of quality engineering to avoid a halt in ongoing improvement. The software industry and the digital quality assurance are confronted by an unprecedentedly fast-evolving technological macrocosm.

Data-driven decision-making is fundamental for any business that wants to thrive in today’s cut-throat environment. In fact, there is enough evidence today that proves that data-driven decision-making powered by artificial intelligence (AI) platforms can help businesses expedite their operations, thus saving valuable time and money. Such decisions involve leveraging past information to predict the challenges and opportunities that await an enterprise in the future.

Today, every business gathers a sizable quantity of data. From app usage statistics to repeat purchases stats, from time spent on the app to the location of buyers, almost every data point is collected and stored in databases. We all know the importance of data in the growth of a business. From stocking inventory in anticipation of demand to focusing on more profitable customers and areas, and optimizing employee productivity, data gives us accuracy.

We’ve all heard about the significant WhatsApp breakdowns that have happened in the recent past, during which the app was unavailable for the public for an hour. However, from a technical standpoint, WhatsApp returned in less than an hour. What would have enabled the engineers at WhatsApp to quickly restore the services? Technically speaking, the team experienced an extremely stressful production failure because of this.