Importance of Big Data and IoT for Financial Intelligence

Importance of Big Data and IoT for Financial Intelligence

The always-connected ecosystem in everyday lives has gained further traction with more and more sensor embedded wireless connected devices. Connected cars, smart healthcare wearables, and smart homes, are some of the active components of an IoT network today. Together with the hyper-mobility adoption, more data is being generated seamlessly in real-time. Increases in computing power and cloud deployments have also enabled this big data to be stored, processed and analysed at great speeds.

Big data Analytics, Machine Learning, Internet of Things (IoT) and Wearables, have emerged as leading disruptors in financial services, insurance and wealth management.

Big data meets IoT

According to the Mckinsey – The Internet of Things: Sizing up the Opportunity Report, “the installed base for IoT devices will grow from around 10 billion connected devices today to as many as 30 billion devices by 2020”. These new technologies are reshaping the value proposition of existing financial and insurance products and services.

The wealth of data generated by smart devices at various touch points, enables data-driven insights for transformation into cumulative customer experiences. So when a customer walks into a car sales showroom, you are able to send a personalised message of how much financing and insurance is approved even before he makes the deal.  

A wealth of data for customer intelligence

In the highly competitive FinTech sector, innovative services and products are the ultimate differentiators. So, how does a FinTech company use the big data to define an engaging customer experience? It crunches historical data from multiple sources and devices to create a customer profile, uses transactional and behavioural data to understand patterns in customer behaviours, and applies predictive analytics for service most likely to engage the customer.

As the concept of ‘smart cities’ gains momentum, companies have more access to rich data related to the lifestyle and preference of customers. At the core of the IoT-generated big data is customer intelligence – getting-together vast amounts of raw data from embedded sensors for actionable insights

Huge implication in InsurTech

The IoT technology has been the greatest disruptor in health insurance. Companies are able to collect data from wearable devices, for product pricing, insurance claim settlements, health tips through IoT devices or premium payment reminders. In the automobile sector, data recorded in devices fitted in cars (telematics) are helping evaluate risks, and segment policies based on historical customer behaviour.

Connected homes and appliances in the IoT network generate critical data related to home safety and customer behaviour patterns. Insurance companies use the data for risk assessment or settlements.

One of Britain’s biggest insurers has embraced IoT by partnering with water leak detector, Leakbot, and security camera company, Canary. Aviva Insurance is using smart IoT-driven data to engage its home insurance customers and reduce claims. As more cities embrace the “smart city” ecosystem, a proliferation of household data from sensors and smart devices is expected to open up unlimited opportunities for insurance companies.

Creating innovations in FinTech

Big data in FinTech is driving cognitive analytics and machine learning for improved customer insights and enhanced customer experience for a longer Customer Life-cycle  Value (CLV). While big data from social media and agencies is mined for credit scoring and P2P lending, predictive modelling is empowering quick decisions in loan acceptance rates and default rates.

Big data analytics embedded in computing have the ability to isolate and minimise fraud risks, using smart algorithms and clustering models. Wealth management is another area of big data analytics application. Algorithms measure market and investor sentiment and integrate it with the big data generated by trading, for higher success rates. German online lender Kreditech uses big data and machine-learning algorithms to build a ‘digital bank’ for the “unscored”. The company uses customer online data instead of traditional credit rating information. IoT-driven insights also help offer geo-targeted deals based on the customer’s current location. For example, when the customer is at a restaurant, smartphone alerts can inform the customer of a 20% discount because of vendor partnership. Commuters in Singapore are already paying for train and bus rides using smart wearables.

Big data helps meet compliance standards

Ernst & Young, a global consulting firm, reports that big data has completely changed the auditing process. The seamless integration of big data and analytics deliver more insights and value to the users of financial statements. The regulatory mechanism with a big data analytics underpinning is also enabling auditors to improve financial reporting, to better detect fraud and operational business risks, for a more relevant audit.

The big data architecture together with the IoT ecosystem has created a tsunami of data for companies. This has created a digital shift in FinTech and InsurTech implementation. Sophisticated analytics tools are working together with innovative systems to produce business models in sync with customer needs. The additional IoT functionality of micro transactions and connected devices are enhancing the personalisation of products and services across insurance and financial sectors.

 

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