At NJ AMC, our Forensic & Governance Model is built to systematically detect forensic and governance laggards through a quantitative scoring framework. By evaluating key forensic parameters, the model identifies companies with potential financial weaknesses or governance risks. This structured approach helps filter out firms with red flags, ensuring a more robust portfolio while enhancing factor strategies and long-term risk-adjusted returns.

Based on the Forensic and Governance model, a specific score is assigned to each company in the Nifty 500 index. The companies are then grouped into 10 deciles, with Decile 1 comprising the highest-scoring companies and Decile 10 the lowest. Our portfolio strategies tend to eliminate companies falling the last two deciles based on this proprietary Forensic & Governance Model to safeguard the portfolios from potential corporate shenanigans. This process is repeated for every rebalancing date, and cumulative results of performance parameters are analyzed, as illustrated in the following charts.

Source: CMIE, NJ’s Smart Beta Platform. Data is from September 30, 2006 to December 31, 2024. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic model scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Past performance may or may not be sustained in the future and is not an indication of future returns.

Source: CMIE, NJ’s Smart Beta Platform. Data is from September 30, 2006 to December 31, 2024. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic scorecard scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Past performance may or may not be sustained in the future and is not an indication of future returns.

Source: CMIE, NJ’s Smart Beta Platform. Data is from September 30, 2006 to December 31, 2024. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic scorecard scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Past performance may or may not be sustained in the future and is not an indication of future returns.

Source: CMIE, NJ’s Smart Beta Platform. Data is from September 30, 2006 to December 31, 2024. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic scorecard scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Past performance may or may not be sustained in the future and is not an indication of future returns.

Source: CMIE, NJ’s Smart Beta Platform. Data is from September 30, 2006 to December 31, 2024. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic scorecard scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Past performance may or may not be sustained in the future and is not an indication of future returns.

The charts above clearly demonstrate a strong correlation between accounting quality and investment performance and risk. Portfolios with higher forensic and governance scores (Deciles 1–3) consistently outperform, delivering higher CAGR with lower volatility and reduced drawdowns. These results highlight the effectiveness of forensic screening in identifying financially sound companies with stronger governance.

Conversely, lower forensic and governance score portfolios (Deciles 8–10) suffer from diminishing returns (CAGR) alongside heightened volatility and severe drawdowns. Their high 3-year probability of loss further reinforces the risk of investing in companies with governance and financial red flags.

Scams are rarely sudden events. They are typically the result of years of financial misrepresentation and governance lapses. This reinforces the importance of forensic and governance analysis as a critical tool for early detection. By identifying potential red flags at an early stage, such analysis acts as a safeguard against significant financial and reputational damage.

Proactive measures like these not only help in mitigating risks but also contribute to building a more resilient, transparent and robust investment ecosystem.

Upon further analysis, the table below highlights key companies that exhibited persistent governance issues and financial weaknesses, placing them in the bottom two deciles for years before their respective scams were exposed.

Source: CMIE, NJ’s Smart Beta Platform. The portfolios are constructed by ranking all Nifty 500 companies based on their forensic scorecard scores and dividing them into ten deciles. Each decile forms a separate portfolio, with Decile 1 containing the highest-scoring companies and Decile 10 the lowest. Potential saving is calculated as maximum drawdown within 1 year from the date on which the scam unfolded. Prices are adjusted for corporate actions. Past performance may or may not be sustained in the future and is not an indication of future returns. The above should not be construed as a recommendation to buy/sell any stocks specified above. The above content is based on the internal research process. The AMC may or may not hold the above stock in its portfolio. Investors should consult their own advisors, and tax consultants before making any decision. * For Manpasand Beverages Ltd. max drawdown is considered from the date of unfolding of the scam till the date the stock was listed.

For instance, Manpasand Beverages, a fast-growing FMCG company, saw meteoric stock price gains before its auditors resigned in 2019, citing financial irregularities. However, our model had flagged the company well before this event, consistently placing it in the bottom deciles. As the fraud came to light, the stock plummeted, eventually losing nearly 48% value in just 4 days.

Similarly, the IL&FS crisis in 2018, exposed massive debt defaults and poor governance, causing a major shock to India’s financial markets. However, our forensic and governance model had flagged the company much earlier, consistently placing it in the bottom deciles due to its weak financials and governance concerns.

The case of Cox & Kings Ltd. further illustrates how financial frauds often build up over time. The company, which defaulted on debts worth Rs.5,500 crore in 2020, was involved in fund diversion, fake transactions, and inflated revenues. Yet, our forensic model had detected these governance issues as early as 2011, consistently placing it in the bottom two deciles for years. A similar pattern emerged with Religare Enterprises Ltd., where the company orchestrated a Rs.2,397 crore fraud by diverting funds. Our model had flagged governance concerns as early as 2009, long before the fraud was uncovered in 2018.

Lastly, Jet Airways’ collapse was a cautionary tale of how financial mismanagement, excessive debt and governance failures can lead to failure. The accumulation of excessive debt of around 8,500 crores while mismanaging cash flows was a clear indication of red flags leading to its placement in the bottom 2 deciles for several years.