Technology's Role in Risk Management & Fraud Prevention in the Financial Services Industry

In the past year, 46 percent of all small and big businesses in India have experienced economic crime to some degree. 52 percent of companies that rake in global annual revenues over $ 10 billion experienced fraud that surpassed a total financial impact of $ 50 million in value. Among smaller businesses, around 38 percent of companies experienced fraud that caused a financial impact of around $ 1 million.

Rising financial crime is one of the primary reasons for the agile adoption of cybersecurity solutions in financial services. As consumers move to digital transaction channels, cybercriminals are adopting sophisticated ways to scam consumers and businesses. However, integrating intelligent solutions into your customer journey could prevent fraud and mitigate risk in fintech.

Role of Technology in Risk Management
The digital-first approach to business brought about a paradigm shift in the role of technology in business. At this juncture, risk management took priority in business like never before. Using data analytics to peel through the layers of credit risk projections and AI/ML solutions to calculate credit default risk proved instrumental to business success in fintech this year.

Here's a look at some problems that technology can solve to aid risk management in financial services.

1.Intelligent Threat Analysis – Cyber threats loom large over fintech; when working with big data, a fintech business constantly runs the risk of ransomware infections, account hijacking, and data leaks. Setting up analytics on attacker sources, indicators of compromise, and behavioral trends can gather valuable threat intelligence feed. Aggregating this data and analyzing it at a scale using machine learning – can reveal threat-related insights for the business. These insights can be processed to create likelihood and predictability models to minimize risk in fintech.

2.Unstructured Data – When building systems for Information Technology security management in a business, unstructured data can be the most significant risk. Implement cognitive analytics to classify and mine this data. It will reduce risk, help the business gain a competitive edge and boost performance. Perhaps that's why Deloitte estimates that the global market revenue for cognitive solutions will surpass $60 billion by 2025. AI/ML-enabled risk management solutions can be used for enterprise risk management, creating simpler business processes, and using Information Technology resources productively.

3.Improving Compliance & Capabilities – Financial services deal with heaps of documents for processing.

For example, loan applications contain their customers' sensitive personal and financial information. Automating and digitizing processes such as document collection and file management can reduce the risk of exploitation of sensitive information. Not only that, it can also accelerate the process, improve regulatory compliance, and reduce workload.
The best strategy is to deploy fintech-specific services to reduce risk and improve compliance for our clients while keeping such risks in mind.

Role of Technology in Fraud Prevention
The financial services industry is leading the digital transformation revolution, and we are all excited to adopt innovative tech solutions that connect financial services to the end consumer. But at the same time, the industry must invest in tech solutions to protect themselves and their customers against digital fraud. It becomes essential in a country like India, where the challenge is keeping pace with technological evolution. The good news is that fraud prevention solutions can now be integrated into the customer journey and onboarding process to empower the system against miscreants. Here's a look at some examples –

The need of the hour is a comprehensive data-driven approach to risk management and fraud prevention

1.Synthetic Identity Fraud – Counterfeiting private records of an individual or organization to use their identity for financial gain is defined as synthetic identity fraud.

2.Misleading information during KYC, loan application, or insurance claim are just a few examples of synthetic identity fraud. It is advisable to invest in multi-layered security technology that leverages biometric technology. Behavioral biometrics can be vital in spotting and preventing fraud in real-time. Using intelligent video tech for KYC also allows service providers to verify all details instantaneously and prevents the use of synthetic identities.

3.Channel Fraud – The process of onboarding merchants is complex and risk-prone. Numerous diligence checks and third-party verification is imperative to ensure fraud prevention. Establishing an error-proof merchant onboarding process can send operation costs spiraling. Choose a blockchain-enabled solution to combat channel fraud and leverage emerging technologies such as liveness checks, face match checks, voice biometrics, and geolocation tagging to create a robust ecosystem that cannot be defrauded.

As the fintech market continues to grow, there will be more innovative, AI-integrated ways to prevent fraud and mitigate risk in fintech. The need of the hour is a comprehensive data-driven approach to risk management and fraud prevention. Fintech businesses should proactively implement the latest technology and gather data that offers better insight into patterns of fraudulent activities and uncovers all aspects of business risk.