GGenerali CentralExecutive Cockpit
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Policy 360

The policy book as records, not summaries: every policy with its product, premium, sum assured, status and customer — and a lapse propensity computed from its own features. Read live from PostgreSQL.

Generali Central Insurance Company Limited · FY25 (Mar'25, audited)
Mid-tier private multiline general insurer — Top-10 private (rank ~10)
2,644 employees · 167 branches · 21,000+ agents
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Live records

Policy book by product

LIVE · PostgreSQLpostgres · demo_bfsi17 msread-only session

Written premium, average ticket and in-force versus lapsed, straight from the policy administration rows.

300
Policies
5 product lines
₹024974.5924960.9624951.8124940.8624935.5324836.9324820.8624807.5624793.4024792.3924781.0824737.6324708.5424705.4924680.8124675.0924633.3024606.8924566.6724499.7024490.5924451.7924444.1524433.4124427.2424377.5724354.1024340.2924320.3824280.4124265.3924264.7124245.0024214.5224209.7124173.3924100.3224061.4224051.0323987.8623979.1123931.8123916.5123882.7423879.5723819.8023803.7223768.5523756.9423736.5223694.4223688.0023674.6623672.0423655.2923636.3523636.2323549.0923538.5523536.2223484.1423446.9823426.4123309.9423288.9523247.4123219.6923214.7423208.9223188.7623150.1623117.6823083.2223022.4723003.2422911.8522891.7522885.0222869.2722867.0322861.1922852.9422834.7922800.5222779.3022769.8022691.9522691.4222673.9922664.6422663.2122651.7822622.1222551.4022490.4122460.1422436.0122399.0622391.7522385.5222378.0522330.5322278.7322165.8722158.0622119.2922113.5822036.8022007.6821940.6721940.0221912.2621898.0421885.4021870.4721859.8121823.2821805.9121760.1721758.9321749.9621709.2821703.8321701.6421676.3421638.6321493.3421458.1621306.9221280.1621272.0721252.2421237.4321234.8221194.8121193.8321190.6421173.1621154.5621151.4721149.0021140.0921102.6621091.0521060.7221044.1921028.9721027.2520983.8920978.9620963.1320959.0720944.2520886.3120874.6220860.2420829.2820828.6520809.0820773.0120734.8720723.3920685.2920672.5420668.3720663.3120640.9620493.5720485.3120479.9920395.7320358.6520334.8620257.2320247.9020232.0120222.6820193.7820177.9820173.0520154.4620153.6120103.4720094.5620032.0420031.5420026.9919973.2219906.2719900.7919872.4419847.0019825.3019823.9019822.2719809.1419781.4919776.1419673.7519669.2519629.9519539.8919497.4219482.2019477.7819454.6219439.1419423.0419372.1619350.6519321.2019303.6219179.0419171.2019145.7219126.7119114.4619102.6919083.5519073.3819060.0819038.8919026.2219008.5919005.9618936.0618931.8418838.1418752.5918681.8518666.8518659.9518655.2618653.5118601.0718588.1218586.0518550.9218487.3718477.2818400.8018397.7418393.9818357.7318298.4418251.5818249.1918234.0818228.8618227.3918158.3918145.0818143.3018086.1618074.4018045.1917950.5517915.0617903.8717898.1517895.3017847.9917842.0717787.5717778.9517773.2717772.5617761.6017730.8417722.0617694.9917599.9817563.2717542.4917458.2517432.3517315.6717305.3517267.6017239.1017217.3917174.8517170.2117124.3317109.7017107.0217104.9217101.2917065.5517062.8117007.7016981.3916980.5616960.4516871.8516855.1616820.3216815.0116762.6816716.07
Written premium
sum of policy premium
203
In force
status ACTIVE
248
Lapsed
status LAPSED
MOTOR198 policies · avg ₹12,749 · SA ₹25,76,758 · 42 active · 56 lapsed
HEALTH188 policies · avg ₹12,704 · SA ₹27,13,322 · 46 active · 47 lapsed
HOME181 policies · avg ₹11,507 · SA ₹26,17,078 · 36 active · 59 lapsed
LIFE167 policies · avg ₹12,774 · SA ₹25,03,179 · 42 active · 40 lapsed
TRAVEL166 policies · avg ₹13,504 · SA ₹23,57,130 · 37 active · 46 lapsed
Predictive · computed

Lapse propensity

Computed

Scored in code from policy status, time to expiry, premium as a share of declared income, claim experience, KYC currency and product type. Each score shows the features that produced it.

244
High lapse risk
81% of book
₹024974.5924960.9624836.9324820.8624807.5624737.6324705.4924680.8124606.8924566.6724377.5724320.3824280.4124265.3924214.5223931.8123879.5723819.8023768.5523756.9423694.4223672.0423288.9523247.4123219.6923188.7623083.2223022.4722911.8522885.0222869.2722867.0322852.9422834.7922769.8022691.4222673.9922664.6422663.2122622.1222551.4022391.7522330.5322165.8722158.0622036.8021940.0221823.2821749.9621703.8321701.6421493.3421458.1621280.1621237.4321234.8221173.1621151.4721102.6621044.1921027.2520944.2520886.3120828.6520809.0820773.0120734.8720723.3920395.7320257.2320247.9020177.9820173.0520153.6120094.5619872.4419822.2719781.4919497.4219482.2019439.1419372.1619350.6519303.6219179.0419114.4619102.6919083.5519073.3819026.2219005.9618936.0618681.8518666.8518655.2618601.0718477.2818400.8018397.7418393.9818357.7318298.4418249.1918158.3918145.0818143.3018074.4018045.1917903.8717898.1517847.9917787.5717778.9517761.6017722.0617599.9817563.2717542.4917315.6717107.0217065.5516981.3916871.8516815.0122779.3024245.0020963.1320493.5724793.4023214.7423117.6822399.0621898.0421885.4019825.3019809.1422007.6819038.8916960.4521140.0919776.1417007.7024173.3922385.5221638.6319126.7117104.9220685.2919454.6221912.2618752.5918588.1223538.5520640.9619973.2224209.7119423.0418550.9224792.3924675.0924633.3024264.7123979.1121193.8320874.6220663.3119906.2719673.7518251.5824951.8124061.4223484.1423003.2421060.7220829.2819171.2018586.0518227.3917842.0717432.3517170.2124451.7921091.0516762.6824444.1524340.2922378.0521306.9221252.2420860.2420334.8620232.0120103.4720026.9918838.1417915.0617772.5624940.8624935.5324781.0824427.2424100.3223882.7423736.5223636.3523636.2323549.0923536.2223426.4123208.9222861.1922460.1421805.9121758.9321709.2821194.8121149.0020983.8920978.9620485.3120358.6520193.7819900.7919847.0019669.2519477.7818234.0818228.8618086.1617950.5517730.8417305.3517239.1016855.1616820.3223655.2923150.1622278.7322119.2922113.5821154.5618931.8417694.9917109.70
Premium at risk
NaN% of written premium
54
Medium
watch list
2
Low
stable
PolicyTypeCustomerPremiumScoreWhy
POL-69019961LIFEYash Naidu₹24974.591.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-80997678MOTORNisha ChatterjeeHIGH₹24960.961.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-51418258TRAVELDev Arora₹24836.931.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-58827484HEALTHYash ChatterjeeHIGH₹24820.861.00High
Cancelled +0.35Past expiry +0.20Premium burden +0.18
POL-06623988TRAVELKartik Shah₹24807.561.00High
Cancelled +0.35Past expiry +0.20Premium burden +0.18
POL-62447378LIFERamesh PatilHIGH₹24737.631.00High
Cancelled +0.35Past expiry +0.20Premium burden +0.18
POL-84604421TRAVELBhavna Naidu₹24705.491.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-08995409HOMEGirish Tandon₹24680.811.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-41924491MOTORNeha Gokhale₹24606.891.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-09703835HOMEAnand Sethi₹24566.671.00High
Already lapsed +0.55Past expiry +0.20No claim experience +0.10
POL-15893568LIFESachin Shah₹24377.571.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-36107199HOMEAmit Bose₹24320.381.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-65269827HOMEAnkit Chowdhury₹24280.411.00High
Cancelled +0.35Past expiry +0.20Premium burden +0.18
POL-99151769TRAVELRekha Naidu₹24265.391.00High
Already lapsed +0.55Past expiry +0.20Premium burden +0.18
POL-10323858TRAVELNeha Gokhale₹24214.521.00High
Cancelled +0.35Past expiry +0.20Premium burden +0.18

Live rows: 300 policy records read from demo_bfsi.insurance_policy in PostgreSQL at request time. These are genuine records with genuine structure, but they are synthetic demo data, not Generali Central's book — status distributions are near-uniform, and person, provider, branch and payer names are localised to Indian display names at read time. Scores demonstrate the scoring mechanism, not predictive performance. The reconciled ₹5,548 Cr figures elsewhere in this cockpit come from the governed SQLite book.

Predictive · computed

Claim frequency

Computed

Claims per policy-year against the product's expected frequency (stated priors: motor 0.55, health 0.45, travel 0.30, home 0.15, life 0.05). Early claims and high-risk customers add to the score.

158
High-frequency policies
of 300 scored
66
Claim-free
no claims in exposure
5.03
Avg rate (claimers)
claims / policy-year
152
Early claimers
claimed inside 6 months
PolicyTypeClaimsExposureRateExpectedScoreWhy
POL-80997678MOTOR30.3y120.550.88High
Frequency far above expected +0.40Early claim +0.15
POL-41234738LIFE10.3y40.050.88High
Frequency far above expected +0.40Early claim +0.15
POL-79050864MOTOR10.3y40.550.88High
Frequency far above expected +0.40Early claim +0.15
POL-56307885HOME10.3y40.150.88High
Frequency far above expected +0.40Early claim +0.15
POL-87907422HEALTH20.3y80.450.88High
Frequency far above expected +0.40Early claim +0.15
POL-31383962TRAVEL10.3y40.30.88High
Frequency far above expected +0.40Early claim +0.15
POL-02618707MOTOR20.3y80.550.88High
Frequency far above expected +0.40Early claim +0.15
POL-21051328HEALTH20.3y80.450.88High
Frequency far above expected +0.40Early claim +0.15
POL-03699503HEALTH10.3y40.450.88High
Frequency far above expected +0.40Early claim +0.15
POL-32048252HEALTH10.3y40.450.88High
Frequency far above expected +0.40Early claim +0.15
Predictive · computed

Demand — new business by month

Computed

Policies written per month from the live start dates, with a three-month least-squares projection. The projection is a straight line over the last twelve months — stated plainly, not a forecasting model.

25-08
25-09
25-10
25-11
25-12
26-01
26-02
26-03
26-04
26-05
26-06
26-07
+1
+2
+3

Last 12 months: 266 policies, ₹33,82,078 premium. Trend +0.36 policies/month; projected next three months 25 · 25 · 25.