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Author: Chirag Malhotra |07/20/18

Fraud Prevention: How do we evolve with efficiency in the face of the latest identity thefts?

Frauds/scams and identity thefts have been a major cause of distress for human beings since the beginning of existence. With the advent of industrialisation in the start of 19th century to the constant advancements in technology, the level and complexities with which the frauds have beset us is only getting more potent by the day. The present situation when analysed, pleads us to answer the question - How do we overcome this situation?

First, let’s get the reality straight. We humans, with all our technological feats are still the victims of some of the frauds at an epic scale. In a customer-centric universe that we live in today, customer satisfaction is not at 100% in any organization.

Having briefly highlighted our current plight, let’s look at sustainable ways that can result in high customer satisfaction with negligible disruptions and maximum value addition.

1. Know your customer beyond the conventionality

It is important to start evolving in ways where we get to know our customers beyond their 360-degree view; wherever being conversant with the customer does not extend beyond the challenge-response questions. A multi-layered customer authentication to peg the knowhow has its own challenges when it comes to customer experience.

Getting to know the customer requirements and knowing more than just the conventional Know Your Customer (KYC) is an arduous process. It requires a sustained interaction with the customer insights to decipher the ways in which the customer behaves online/offline; the interaction needs to define and identify with the customer at the core. Decomposing these interactions down at the atomic level will help get a paradigm shift in which the customer authentication is thought about in ways beyond the conventionality, as defined now by the industry set processes, will lead to know the customer mitigating frauds which affects our services to them.

2. Breaking away the silos when it comes to customer understanding

Silos may be defined as entities and relations which operate at disparate levels and myriad of interactions. We need to understand that the customer definition is not valid with just an interaction, but it depends on the multitudes of interactions and derived relations to many degrees, i.e., the relations between:

  1. The customers and their subsequent customers
  2. Customers and vendors
  3. Customers and their competitors

The above are just a few levels of interactions, which can be further dissolved to have an expansive understanding of the customers which only exists in silos.

The above concepts will lead to additional gridlocks which can provide an adequate protection against the frauds and identity thefts.

3. Agility and scalability using service-based models

Fraud strikes like a lightening bolt and it takes a keen sense of discerning the observable patterns which might aid in understanding the fraud and the complexities involved in its identification. This data needs to be gathered to analyse the risk models and to conclude about dealing with the fraudulence.

Once analysed, it takes weeks or even months to build and deploy the models that deal with the fraud effectively. Circumventing this can be done by turning to the service-based models that provide a quicker turnaround time (TAT), agility and scalability. An added advantage is that these service-based models also support the business with growth in volumes, and the expansion in different geographies too.

4. Application of AI technologies like Machine Learning

Machine Learning (ML) is a highly adaptable technology which can effectively perform the analytics of enormous data sets and deliver a risk susceptibility score in real time.

Behavioural analytics help in building digital foot prints which can prove to be effective in tackling the primal characteristics of fraud - long tail distribution, i.e., too may unique cases and high frequency of changing patterns. Let us list the most evident advantages of machine learning.

  • ML can reduce the manual review of the queues through a fast-paced algorithmic application
  • Adaptability to new business lines using experiential data
  • Force multiplier in human decision making with an augmented precision
  • Reduction in false positives with behavioural analysis

The latest innovation in technological applications can help overcome the challenges that fraud and its continuous advancements bring to the table. ML is a promising science that has the potential to deal with fraudulence in a productive and powerful manner. Applicability of this across multiple environment makes it a necessity in the future which is both algorithmic and technology heavy.

Do you think ML can help reduce the evolving identity threats and fraudulence in a better way?

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