Risk-Marking The Potential Threats: How New-age Technologies Can Help Financial Institutions In Effective Fraud Detection
The past decade has seen a series of technological breakthroughs which opened many opportunities for financial institutions and took them to new heights. However, the year 2020 has shown a lot of challenges and speeded up the processes that many online companies were trying to implement before and also shed light on some new problems.
The process of active digital transformation has become the main growth driver for many companies. For the financial services sector, it has become obvious that moving online a significant part of business processes is inevitable and now is an essential condition for the development and maintenance of any company’s position in the market, as well as for obtaining new business in the future.
Many companies, strengthening their position online, faced some problems related to the processing and storing of personal data, in other words, data breaches. Indeed, the use of personal data is convenient and often does not require highly qualified personnel. Meanwhile, the lack of reliability of IT systems and organizational procedures for storing and processing personal data can lead to loss of information and cause irreparable damage to the reputation and financial losses to both data subjects and the operator.
The consequences of such attacks are severe. Though it may not be possible to stop such attacks from occurring, however, it is possible to stop fraudsters from using this information. We believe that financial institutions can gain even more value from non-personal data, which is often ignored and practically useless for fraudsters. Digital lending companies can thrive by bringing in extra tools of data and loan applications analysis and using poorly reproducible alternative data in the loan workflow. In the current scenario, lenders can fasten the entire digital lending process by leveraging different data sources and insights thereof for identity verification, compliance, credit underwriting, and fraud detection. Detecting unusual behavior, repeating devices, combined with cross-checking the data used in different loan applications sent from the same device along with analysis of large deviation markers could be useful for fraud detection. Business owners should pay attention to AI/ML solutions that leverage alternate data such as behavior, device, and network information for providing such insights.
New Regulatory Requirements
The importance of privacy and data protection is growing immensely. For financial institutions, it is necessary to take into account all changes in legal regulations, particularly regarding the requirements for the processing of personal data. Increasing regulations in 2020 in various regions is one of the factors that experts note among a number of reasons that negatively affect market growth. For example, regulations similar to the General Data Protection Regulation (GDPR) are being set up nowadays in other countries, such as the PDP Bill in India, a comprehensive overhaul to India’s current data protection regime, which may come into effect soon, and hence, financial institutions need to be prepared.
It also applies to the recommendations to the regulated entities (Banks, NBFCs), etc. by the Indian regulators to use a device-based fraud detection approach. For example, some of the parameters that should be monitored to flag suspicious transactions should include amongst others: Application/Transaction velocity (Multiple applications or transactions within a short period of time), excessive activity on a new account (e.g. mule account), IP Geolocation inconsistencies, etc.
Under the mobile application security controls, the following checks have been prescribed amongst others: the ability to detect remote access tools (RATs) and prohibit login access to mobile applications in suspicious scenarios, the ability to detect and prevent access from jailbroken and rooted devices, consider implementing alternatives to SMS based authentication, etc.
Leading online business companies have already been affected by some difficulties related to inconsistency with law regulations (or being not entirely compliant to them). This refers to the categories of collected and processed data regulated by law, including identity/address documents data, financial transactions data, calendar data, correspondence data, medical history, passport and other documents details, email, address, education, and work information, etc.
The best way to stay out of trouble is to use such antifraud and risk-management solutions that deliberately stay away from the data that may be viewed as direct identifiers or may be considered to be a part of bank secrecy or related to the privacy of correspondence.
New Environment, New Opportunities
We also advise taking a closer look at those anti-fraud solutions which pay great attention to consulting services, help to build custom scoring, adapt solutions for a specific client, investigate and individualize.
A smooth sea never made a skillful sailor. We believe that nowadays, those players who understand the importance of maintaining a balance between reduction of credit & fraud risks, as well as the speed of adjustment without inconveniencing good customers, turn out to be the most successful.
About the Author:
Manish Thakwani: Head of Business Development (India) at JuicyScore
Manish Thakwani is a seasoned leader and recognized expert with over 12 years of experience in the fraud risk management space and a strong affinity for leveraging data and technology to achieve business goals across varied mandates. An Alumnus of the prestigious Management Development Institute, Manish has been closely associated with sectors such as financial services, telecommunications, insurance, and e-commerce in the course of his career.
Founded in 2016 JuicyScore is a forward-looking company that creates fraud prevention solutions for online businesses. JuicyScore provides the anti-fraud score, robust device fingerprint, and a wide vector of predictive data attributes which may be used in internal fraud score and credit score models. On average, the company’s clients get 10Х+ ROI and 5+ GINI. API is unified for all countries of their operations and supports both web and mobile channels.
JuicyScore offers deep expertise in score modeling, decision-making engine and flow, customized score, and analytics. The company has its operations in 21 countries across the globe, 80+ clients, and works with the mission to make the process of obtaining financial services safer, by not using any consumer direct identifiers or any type of consumer sensitive data. JuicyScore is compliant with GDPR, current and prospective regulating rules, browsers and operational systems’ security policy, marketplace requirements. Visit the official website https://juicyscore.com/en/for further information.