The business environment is changing across all industries, including the insurance and banking sectors, as a result of digitization, which is characterised by an increase in mobile devices and social media. Insurance companies and banks are connecting with their consumers more effectively thanks to social networks and communities, which helps with branding, customer acquisition, and customer retention. These businesses are also utilising digitization, leveraging data analytics for fraud detection, in addition to these opportunities.
Even if one or two instances of high-value fraud remained undetected, insurance and financial organizations have always found it expensive to manually handle fraud. Although different analytics aid in developing a genuinely global picture of the enterprise-wide anti-fraud activities, however the trend shows gap for frauds if data is not adequately reviewed
Given the increased adoption of channel diversification and the rise in potential fraud hotspots in addition to the traditional methods from face-to-face insurance to online information capturing trends, insurance-related activities can now be performed via mobile devices. This can be seen as an addition to information silos in the insurance and banking industry. Thus, it is crucial for insurers and banks to have easy access to enterprise level information.
We at TechnoDecibel are able to offer a non-intrusive solution to both insurance and banking verticals, where the genuine emotions and purposes underlying someone’s words are almost as significant as the substance of their responses. Instead of relying on outdated technology, well written dialogue scripts might help the underwriters and experts identify potential fraud much faster and would then be allowed to look deeper into possibly fraudulent claims for an informed decision.
This emotion-focused strategy would also greatly benefit claimants. Low risk claims might go quickly through the procedure without being delayed by unnecessary inspections. This would result in a significantly faster payout. Companies and claimants would both benefit from this strategy.
The challenge of NBFC also includes fraud. Apart from verifying the “cibil scores”, Does the applicant actually make INR 100,000 per month, or are they slightly – or greatly – exaggerating? Are they requesting credit because they have a history of making bad loan decisions and are at their wits’ end, or are they a sincere up-and-comer who needs some credit to help them realize their goals? These emotions can be revealed using the “Emotion Detection Platform” with a script that has been appropriately tuned.
A person’s score might go both ways when considering their emotions. Based on the outcomes of the scripted conversation, the applicant may normally be rejected might get a second look. On he other hand, the applicant who could be classified as medium or low risk by conventional scoring may be highlighted for additional investigation based on the system’s assessment of their responses to the phone experts. This gives the scoring
algorithm an additional layer, which might result in more loans and more accurate fraud detection and be helpful in making an well informed decision.
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