Beneish M-Score earnings-manipulation API

Compute the Beneish M-Score (1999) earnings-manipulation detector: M = -4.84 + 0.92·DSRI + 0.528·GMI + 0.404·AQI + 0.892·SGI + 0.115·DEPI - 0.172·SGAI + 4.679·TATA - 0.327·LVGI, with the -1.78 threshold flagging likely manipulators and a per-index contribution breakdown. Answers 'is this company manipulating earnings','Beneish M-Score','accounting-fraud red flag score'.

Price$0.016per request

MethodPOST

Route/v1/score/credit-beneish-m

StatusLive

MIME typeapplication/json

Rate limit120/minute

CacheNo cache

scorecreditbeneishm-scoreearningsmanipulationfraudforensic

API URLhttps://x402.hexl.dev/v1/score/credit-beneish-m

Integration docs

Example request

{
  "dsri": 1,
  "gmi": 1,
  "aqi": 1,
  "sgi": 1,
  "depi": 1,
  "sgai": 1,
  "tata": 0.02,
  "lvgi": 1
}

Example response

{
  "model": "Beneish M-Score (1999)",
  "mScore": -2.386,
  "threshold": -1.78,
  "classification": "non-manipulator",
  "interpretation": "No manipulation signal",
  "breakdown": [
    {
      "factor": "DSRI",
      "value": 1,
      "weight": 0.92,
      "contribution": 0.92
    },
    {
      "factor": "GMI",
      "value": 1,
      "weight": 0.528,
      "contribution": 0.528
    },
    {
      "factor": "AQI",
      "value": 1,
      "weight": 0.404,
      "contribution": 0.404
    },
    {
      "factor": "SGI",
      "value": 1,
      "weight": 0.892,
      "contribution": 0.892
    },
    {
      "factor": "DEPI",
      "value": 1,
      "weight": 0.115,
      "contribution": 0.115
    },
    {
      "factor": "SGAI",
      "value": 1,
      "weight": -0.172,
      "contribution": -0.172
    },
    {
      "factor": "TATA",
      "value": 0.02,
      "weight": 4.679,
      "contribution": 0.094
    },
    {
      "factor": "LVGI",
      "value": 1,
      "weight": -0.327,
      "contribution": -0.327
    }
  ]
}

Input schema

{
  "type": "object",
  "required": [
    "dsri",
    "gmi",
    "aqi",
    "sgi",
    "depi",
    "sgai",
    "tata",
    "lvgi"
  ],
  "properties": {
    "dsri": {
      "type": "number",
      "description": "Days Sales in Receivables Index",
      "examples": [
        1
      ]
    },
    "gmi": {
      "type": "number",
      "description": "Gross Margin Index",
      "examples": [
        1
      ]
    },
    "aqi": {
      "type": "number",
      "description": "Asset Quality Index",
      "examples": [
        1
      ]
    },
    "sgi": {
      "type": "number",
      "description": "Sales Growth Index",
      "examples": [
        1
      ]
    },
    "depi": {
      "type": "number",
      "description": "Depreciation Index",
      "examples": [
        1
      ]
    },
    "sgai": {
      "type": "number",
      "description": "SG&A Index",
      "examples": [
        1
      ]
    },
    "tata": {
      "type": "number",
      "description": "Total Accruals to Total Assets",
      "examples": [
        0.02
      ]
    },
    "lvgi": {
      "type": "number",
      "description": "Leverage Index",
      "examples": [
        1
      ]
    }
  }
}

Output schema

{
  "type": "object",
  "additionalProperties": true
}