3 Typical Insurance Misconducts that Must Monitor During Recession

3 Typical Insurance Misconducts that Must Monitor During Recession


Jun 1, 2020 2:20:15 PM / by Macy Choong

Misconduct is improper and wrongful behavior that acted by an individual or a group to gain certain benefits without considering the consequences. In the workplace, it is always a crucial issue that may cause huge unwanted loss to the organisations, damage the organisations' reputation and competitive position, thus it has been recognised as a type of risk, which known as conduct risk. During the recession that caused by dynamic changes like the pandemic, the occurrence of misconduct or even crime will likely increase due to the impact on profitability, potential business model transformation, lower sales and digital channels boost which cause financial pressure on more people. Therefore, the organisations must pay serious attention on monitoring conduct risk before causing any negative impacts to the organisations. 

Different industry may have different types of misconduct that can be committed based on its culture and specific workplace rules and regulations which may involve internal employees or external stakeholders which includes the customers. There is no complete list of the types of misconduct but the typical examples of misconduct that should be monitored by the insurers especially during the recession are:


Typical Misconducts in Insurance Industry


1. External Fraud - External fraud involves external entities from organisations such as partners, suppliers, customers, vendors, or more. One of the example for fraud cases in the insurance sector which involved physios, doctors and others is charging unnecessary referrals and false claims for services not rendered which raises the overall costs of healthcare. According to Ministry of Health in Singapore, some medical doctors are paid commission fees of 20% to 30% of the physiotherapy bill if they refer their patients to private physiotherapy clinics in 2018. Another most common example is suspicious applications that a client submitted without honestly providing his/ her current health condition or information. 




2. Mis-selling (Agent Gaming) - Mis-selling occurred when a product or service is sold without customer receiving accurate information and advice about how the product or service works. An insurance provider has a duty to ensure the insurance that they are selling is suitable for the customer's needs and circumstances. Due to financial pressure especially during recession, more insurance agents may tend to increase the premium rate of the customers policies to boost their sales performance inappropriately for their personal financial gain through forgery, improper switching of policies, and providing financial advice incompatible with the customers' financial situations. In 2019, Japan Post Insurance had engaged in 90,000 cases of inappropriate sales to their customers over a five-year span which mainly due to the disqualifying insurance agents. 


3. Conduct of business - This type of misconduct involving suspected breaches or circumvention of business conduct rules when carrying out financial services activities. One of the examples for misconduct cases related to conduct of business was acted by Prudential. In 2019, the Financial Conduct Authority (FCA) has fined Prudential £23,875,000 for selling retirement income products without informing customers if better rates could be found elsewhere and failed to take reasonable care to organise and control its affairs in breach of its obligation to ensure fair treatment of customers.



How to Monitor Misconduct?

What are the ways to avoid the occurrence of misconduct or mitigate the conduct risk? One of the most efficient and accurate ways is applying the right advanced technologies to monitor and detect conduct risk. 


Traditional way

The misconduct cases usually being reported or complaint by the clients after an issue has occurred. Some of the organisations have applied machine learning to reply on complaints, tip-offs, social media posts, audits or sampling and only a few of them are able to take action to avoid the occurrence of misconduct by detecting and monitoring the potential misconduct cases. There are now several advanced technologies that could be involved to enhance conduct risk management from reactive to proactive approach, find the suspicious fraudulent behavior, and improve the efficiency of investigating and auditing the potential misconduct cases.  


The New Frontier - Advanced Technologies that Mitigate Misconduct

1. Enrich Data with Alternative Data using Artificial Intelligence tools 

Data is the most important element in monitoring misconduct. Insufficient or siloed data will be difficult in mining misconduct patterns. Thus, alternative data from internal and external structured and unstructured data should be included to enrich the data in order to enhance the analytics results and outcome. Insurers should apply AI-driven data acquisition and data integration system to acquire, store and mash-up all relevant internal and external data from multiple sources like complaints, transaction location, digital footprint and more other types of data to generate a more holistic view of your data in nearly real-time in order to enhance misconduct detection accuracy.


2. "Connect the dots" with Knowledge Graph

A Knowledge Graph is a technology that connects and represent knowledge in an area of interest using a network of nodes and links. (Source from Deloitte) By applying knowledge graph in fraud detection or investigation systems, it allows users to gain actionable and deeper insights on impacts and links of the entities to find out the potential entities that have a high chance of carrying out any misconduct by analysing the multiple relationships and interactions while discovering the hidden patterns or suspicious behaviors. By adding knowledge graph, insurers could reduce the time and resources of manual investigation or tracking for the potential misconduct cases while minimising the false positives investigations associated with the traditional risk-management methods.


3. Use Natural Language Processing (NLP) to Gain Deeper Insights

Natural Language Processing or NLP is a field of Artificial Intelligence that gives the machines the ability to read, understand and derive meaning from human languages. (Source from Towards Data Science) Its techniques or tools allow organisations to enhance business functions from chatbots and digital assistants, compliance monitoring, BI, to analytics. It helps organisations to process, analyse, and understand all of the unstructured and semi-structured contents that can bring significant insights such as queries, email communications, social media, videos, customer reviews and support requests. Insurers could utilise NLP in gaining more customer data, capturing the context of customer dissatisfaction, classify the interactions and identify misconduct.


4. Develop the Predictive Machine Learning (ML) Models with Cognitive Engine

Cognitive technologies for predictions involved a range of machine learning, big data, and statistical approaches to process large volumes of information, identify pattern or anomalies, and recommend next steps and outcomes. (Source from Forbes) It allows organisation to build, validate and enhance the predictive models to "leave no stone unturned" and produces actionable predictive outcomes by incorporating all relevant data with several ML algorithms such as knowledge graph, supervised learning and unsupervised learning. Insurance sectors could apply cognitive engine to enhance the conduct risk management process while ensuring "no stone will be left unturned". 




Tackle Misconduct with the Right Advanced Technologies

Manual monitoring or simple rule based approach are no longer sufficient enough during a recession to mitigate misconduct. During this critical moment, insurance sectors should enhance their risk management strategies before any unwanted loss incurred or strike impact on the organisation. Therefore, applying the right advanced technologies are very crucial in enhancing risk detection and investigation efficiency with minimum resources and high scalability.



Macy Choong

Written by Macy Choong
Marketing Specialist

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