How Quantum computing can help banks and insurance companies ?
Quantum computers are expected to revolutionize the financial sector. From securities pricing to portfolio optimization ,quantum computers will play a pivotal role in the decision process.
Financial institutions that can harness quantum computing are likely to see significant benefits. In particular, they will be able to more effectively analyse large or unstructured data sets. Sharper insights into these domains could help banks make better decisions and improve customer service, for example through timelier or more relevant offers (perhaps a mortgage based on browsing history).
We explore potential use cases in each of these categories, providing examples that apply to three main industries in financial services: banking, financial markets, and insurance.
Targeting and prediction
Today’s financial services customers demand personalized products and services that rapidly anticipate their evolving needs and behaviours. A similar problem exists in fraud detection. It is estimated that financial institutions are losing between USD 10 billion and 40 billion in revenue a year due to fraud and poor data management practices.
For customer targeting and prediction modelling, quantum computing could be a game changer. The data modelling capabilities of quantum computers are expected to prove superior in finding patterns, performing classifications, and making predictions that are not possible today because of the challenges of complex data structures.
Trading optimization
Complexity in financial markets trading activity is skyrocketing.
In this complicated trading landscape, investment managers struggle to incorporate real-life constraints, such as market volatility and customer life-event changes, into portfolio optimization. Ideally, money managers would like to simulate large numbers of potential scenarios and investment options to validate sensitivities when estimating expected returns
Quantum technology could help cut through the complexity of today’s trading environments. Quantum computing’s combinatorial optimization capabilities may enable investment managers to improve portfolio diversification, rebalance portfolio investments to more precisely respond to market conditions and investor goals, and more cost-effectively streamline trading settlement processes.
Risk profiling
Financial services institutions are under increasing pressure to balance risk, hedge positions more effectively, and perform a wider range of stress tests to comply with regulatory requirements.
In the face of more sophisticated risk-profiling demands and rising regulatory hurdles, the data-processing capabilities of quantum computers may speed up risk scenario simulations with higher precision, while testing more outcomes.
Financial Risk Model — J P MORGAN
One such solution developed is a financial risk model. Financial risk modelling is the use of formal econometric techniques to determine the aggregate risk in a financial portfolio.
The below mentioned circuit helps us achieve that.
J.P. Morgan is already leveraging Quantum circuit to
a. Improve trading strategies,
b. Enhance client portfolio, and
c. Analyse financial risk.
Quantum computing’s business value for financial services institutions result from four main scenarios:
– Enhancing investment gains
– Reducing capital requirements
– Opening new investment opportunities
– Improving the identification and management of risk and compliance.
