Enhanced annuity from a health questionnaire

A joint life annuity priced from a scanned health form, a prescription and two pension statements, with a referral for an unmatched medicine.

A demo basis, not a default model. The rates are illustrative and the case is synthetic: fictional people, specimen NI numbers and example.com addresses. See how it fits into an adviser's journey on Retirement income.

The line of business

Enhanced annuity from a health questionnaire

An annuity turns a pension fund into an income for life. In the UK, people with health conditions or a history of smoking can get a higher, enhanced income. The price depends on health and lifestyle answers, prescriptions and pension statements. These arrive as scans and PDFs, so most of the work is reading them.

Methodology

How the model rates

This is a rate table model on a demo basis, not a mortality projection. A base rate per 10,000 of purchase price is looked up by age and escalation.

The enhanced price looks the rate up at a rated age: the applicant's age plus years for declared health. The standard price uses the actual age.

Postcode area, guarantee period, payment frequency and timing, and the survivor's pension then adjust the income. Each factor is a lookup table.

Purchases under 10,000 and applicants outside 55 to 85 are declined. An unmatched medicine, a rating over 6 years or a purchase over 1,000,000 is referred.

18inputs

16steps

5lookup tables

8tests

Inputs

18 fields

Field	Label	Type	Default	Allowed values
`quote_date`	Quote date	date	2026-11-10	-
`main_dob`	Applicant date of birth	date	1961-06-01	-
`spouse_dob`	Spouse date of birth	string		-
`basis`	Single or joint life	string	single	single, joint
`survivor_pct`	Survivor's income	decimal	66.67	50, 66.67, 100
`escalation`	Escalation	string	level	level, rpi, fixed3
`guarantee_years`	Guarantee period	integer	0	0, 5, 10
`frequency`	Payment frequency	string	monthly	monthly, quarterly, annual
`timing`	Payment timing	string	advance	advance, arrears
`purchase_price`	Purchase price	decimal	100000	-
`postcode`	Postcode	string	EX1 1AA	-
`smoker_status`	Smoking	string	never	never, former, current
`cigs_per_day`	Cigarettes a day	integer	0	-
`years_quit`	Years since stopping	integer	0	-
`bmi`	Body mass index	decimal	25	-
`diabetes_type2`	Type 2 diabetes	boolean	false	-
`hypertension`	High blood pressure	boolean	false	-
`medicines_unmatched`	Medicine with no declared condition	boolean	false	-

The model

Step by step

Steps run in order. Each one can use the inputs and the outputs of every step before it.

01Transform

Ages and postcode area

Works out both ages at the quote date, and the postcode area from the postcode.

{
  "id": "case_details",
  "key": "case_details",
  "step": "transform",
  "name": "Ages and postcode area",
  "retain": true,
  "format": {
    "main_age": {
      "key": "main_age",
      "label": "Applicant age",
      "exp": "{{main_dob.age(YY, quote_date)}}",
      "type": "integer",
      "def": 0
    },
    "spouse_age": {
      "key": "spouse_age",
      "label": "Spouse age",
      "exp": "{{spouse_dob.age(YY, quote_date)}}",
      "type": "integer",
      "def": 0
    },
    "postcode_area": {
      "key": "postcode_area",
      "label": "Postcode area",
      "exp": "{{postcode.postcode(area)}}",
      "type": "string",
      "def": ""
    }
  }
}

02Transform

Health and lifestyle loads

Years added to the applicant's age for each declared condition. Type 2 diabetes 2, high blood pressure 1, current smoker 3, stopped under 10 years ago 1, BMI over 30 1.

{
  "id": "health_loads",
  "key": "health_loads",
  "step": "transform",
  "name": "Health and lifestyle loads",
  "retain": true,
  "format": {
    "diabetes_load": {
      "key": "diabetes_load",
      "label": "Type 2 diabetes load",
      "exp": "{{diabetes_type2}} === true ? 2 : 0",
      "type": "integer",
      "def": 0
    },
    "blood_pressure_load": {
      "key": "blood_pressure_load",
      "label": "High blood pressure load",
      "exp": "{{hypertension}} === true ? 1 : 0",
      "type": "integer",
      "def": 0
    },
    "smoking_load": {
      "key": "smoking_load",
      "label": "Smoking load",
      "exp": "{{smoker_status}} === 'current' ? 3 : {{smoker_status}} === 'former' && {{years_quit}} < 10 ? 1 : 0",
      "type": "integer",
      "def": 0
    },
    "bmi_load": {
      "key": "bmi_load",
      "label": "BMI load",
      "exp": "{{bmi}} > 30 ? 1 : 0",
      "type": "integer",
      "def": 0
    }
  }
}

03Calculation

Health rating

The health rating in years: the sum of the loads.

{
  "id": "rating_years",
  "key": "rating_years",
  "step": "calculation",
  "name": "Health rating",
  "def": 0,
  "formula": "{{diabetes_load}} + {{blood_pressure_load}} + {{smoking_load}} + {{bmi_load}}"
}

04Calculation

Rated age

The applicant's age plus the health rating, capped at 100. The enhanced price uses the rated age; the standard price uses the actual age.

{
  "id": "rated_age",
  "key": "rated_age",
  "step": "calculation",
  "name": "Rated age",
  "def": 0,
  "formula": "min({{main_age}} + {{rating_years}}, 100)"
}

05Transform

Joint life terms

For joint life, the survivor percentage and the spouse's age less the applicant's. Both are zero for single life.

{
  "id": "joint_terms",
  "key": "joint_terms",
  "step": "transform",
  "name": "Joint life terms",
  "retain": true,
  "format": {
    "survivor_key": {
      "key": "survivor_key",
      "label": "Survivor percentage used",
      "exp": "{{basis}} === 'joint' ? {{survivor_pct}} : 0",
      "type": "decimal",
      "def": 0
    },
    "age_gap": {
      "key": "age_gap",
      "label": "Spouse age minus applicant age",
      "exp": "{{basis}} === 'joint' && {{spouse_age}} > 0 ? {{spouse_age}} - {{main_age}} : 0",
      "type": "integer",
      "def": 0
    }
  }
}

06Decline rules

Decline rules

Cases the demo basis will not quote. A purchase price under 10,000, an applicant under 55 or over 85, or joint life with no spouse date of birth.

{
  "id": "annuity_declines",
  "key": "annuity_declines",
  "step": "exclusion",
  "name": "Decline rules",
  "def": false,
  "items": [
    {
      "id": "min_purchase",
      "name": "Purchase price under 10,000",
      "exp": "{{purchase_price}} < 10000",
      "def": false
    },
    {
      "id": "age_range",
      "name": "Applicant age outside 55 to 85",
      "exp": "{{main_age}} < 55 || {{main_age}} > 85",
      "def": false
    },
    {
      "id": "joint_no_spouse",
      "name": "Joint life without spouse date of birth",
      "exp": "{{basis}} === 'joint' && !{{spouse_age}}",
      "def": false
    }
  ]
}

07Refer rules

Refer rules

Cases priced but sent to an underwriter. A medicine with no declared condition, a rating over 6 years, or a purchase price over 1,000,000.

{
  "id": "annuity_referrals",
  "key": "annuity_referrals",
  "step": "refer",
  "name": "Refer rules",
  "def": false,
  "items": [
    {
      "id": "unmatched_medicine",
      "name": "Medicine with no declared condition",
      "exp": "{{medicines_unmatched}} === true",
      "def": false
    },
    {
      "id": "high_rating",
      "name": "Health rating over 6 years",
      "exp": "{{rating_years}} > 6",
      "def": false
    },
    {
      "id": "large_purchase",
      "name": "Purchase price over 1,000,000",
      "exp": "{{purchase_price}} > 1000000",
      "def": false
    }
  ]
}

08Lookup table

Base annuity rates

Annual income per 10,000 of purchase price by age and escalation, single life, paid monthly in advance with no guarantee. Looked up at the rated age and at the actual age.

Showing the first 10 of 153 rows.

{
  "id": "base_rates",
  "key": "base_rates",
  "step": "collection",
  "name": "Base annuity rates",
  "retain": true,
  "collection": [
    ["rate_age", "rate_escalation", "rate_per_10k"],
    [50, "level", 560],
    [50, "rpi", 336],
    [50, "fixed3", 408.8],
    [51, "level", 571.52],
    [51, "rpi", 345.17],
    [51, "fixed3", 418.34],
    [52, "level", 583.27],
    [52, "rpi", 354.58],
    [52, "fixed3", 428.11],
    [53, "level", 595.26]
  ],
  "format": {
    "enhanced_base_rate": {
      "key": "enhanced_base_rate",
      "label": "Base rate at rated age",
      "exp": "collection.filter(rate_age=={{rated_age}}).filter(rate_escalation=={{escalation}}).map(rate_per_10k).first()",
      "type": "decimal",
      "def": 0
    },
    "standard_base_rate": {
      "key": "standard_base_rate",
      "label": "Base rate at actual age",
      "exp": "collection.filter(rate_age=={{main_age}}).filter(rate_escalation=={{escalation}}).map(rate_per_10k).first()",
      "type": "decimal",
      "def": 0
    }
  }
}

09Lookup table

Postcode area factor

Adjusts income by postcode area. Areas not listed take 1.00.

Showing the first 10 of 30 rows.

{
  "id": "postcode_factors",
  "key": "postcode_factors",
  "step": "collection",
  "name": "Postcode area factor",
  "retain": true,
  "collection": [
    ["pc_area", "pc_factor"],
    ["G", 1.05],
    ["ML", 1.04],
    ["PA", 1.04],
    ["DD", 1.03],
    ["L", 1.03],
    ["NE", 1.03],
    ["SR", 1.03],
    ["BD", 1.03],
    ["M", 1.02],
    ["S", 1.02]
  ],
  "format": {
    "postcode_factor": {
      "key": "postcode_factor",
      "label": "Postcode area factor",
      "exp": "collection.filter(pc_area=={{postcode_area}}).map(pc_factor).first()",
      "type": "decimal",
      "def": 1
    }
  }
}

10Lookup table

Guarantee factor

Reduces income for a five or ten year guarantee. The cost rises with age, so it is looked up at the rated age and at the actual age.

{
  "id": "guarantee_factors",
  "key": "guarantee_factors",
  "step": "collection",
  "name": "Guarantee factor",
  "retain": true,
  "collection": [
    ["gtee_years", "gtee_age_min", "gtee_age_max", "gtee_factor"],
    [0, 0, 120, 1],
    [5, 0, 69, 0.997],
    [5, 70, 79, 0.99],
    [5, 80, 120, 0.975],
    [10, 0, 69, 0.985],
    [10, 70, 79, 0.96],
    [10, 80, 120, 0.91]
  ],
  "format": {
    "enhanced_guarantee_factor": {
      "key": "enhanced_guarantee_factor",
      "label": "Guarantee factor at rated age",
      "exp": "collection.filter(gtee_years=={{guarantee_years}}).filter(gtee_age_min<={{rated_age}}).filter(gtee_age_max>={{rated_age}}).map(gtee_factor).first()",
      "type": "decimal",
      "def": 1
    },
    "standard_guarantee_factor": {
      "key": "standard_guarantee_factor",
      "label": "Guarantee factor at actual age",
      "exp": "collection.filter(gtee_years=={{guarantee_years}}).filter(gtee_age_min<={{main_age}}).filter(gtee_age_max>={{main_age}}).map(gtee_factor).first()",
      "type": "decimal",
      "def": 1
    }
  }
}

11Lookup table

Frequency and timing factor

Adjusts income for how often and when it is paid. Monthly in advance is 1.00.

{
  "id": "payment_factors",
  "key": "payment_factors",
  "step": "collection",
  "name": "Frequency and timing factor",
  "retain": true,
  "collection": [
    ["pay_frequency", "pay_timing", "pay_factor"],
    ["monthly", "advance", 1],
    ["monthly", "arrears", 1.004],
    ["quarterly", "advance", 0.995],
    ["quarterly", "arrears", 1.007],
    ["annual", "advance", 0.975],
    ["annual", "arrears", 1.02]
  ],
  "format": {
    "payment_factor": {
      "key": "payment_factor",
      "label": "Frequency and timing factor",
      "exp": "collection.filter(pay_frequency=={{frequency}}).filter(pay_timing=={{timing}}).map(pay_factor).first()",
      "type": "decimal",
      "def": 1
    }
  }
}

12Lookup table

Joint life factor

Reduces income to pay for the survivor's pension, by survivor percentage and the spouse's age less the applicant's. Single life takes 1.00.

Showing the first 10 of 13 rows.

{
  "id": "joint_factors",
  "key": "joint_factors",
  "step": "collection",
  "name": "Joint life factor",
  "retain": true,
  "collection": [
    ["jl_survivor", "jl_gap_min", "jl_gap_max", "jl_factor"],
    [0, -99, 99, 1],
    [50, -99, -5, 0.94],
    [50, -4, -1, 0.95],
    [50, 0, 4, 0.96],
    [50, 5, 99, 0.97],
    [66.67, -99, -5, 0.89],
    [66.67, -4, -1, 0.905],
    [66.67, 0, 4, 0.92],
    [66.67, 5, 99, 0.935],
    [100, -99, -5, 0.81]
  ],
  "format": {
    "joint_factor": {
      "key": "joint_factor",
      "label": "Joint life factor",
      "exp": "collection.filter(jl_survivor=={{survivor_key}}).filter(jl_gap_min<={{age_gap}}).filter(jl_gap_max>={{age_gap}}).map(jl_factor).first()",
      "type": "decimal",
      "def": 1
    }
  }
}

13Calculation

Enhanced annual income

Purchase price divided by 10,000, times the base rate at the rated age and every factor.

{
  "id": "enhanced_annual_income",
  "key": "enhanced_annual_income",
  "step": "calculation",
  "name": "Enhanced annual income",
  "def": 0,
  "formula": "round({{purchase_price}} / 10000 * {{enhanced_base_rate}} * {{postcode_factor}} * {{enhanced_guarantee_factor}} * {{payment_factor}} * {{joint_factor}}, 2)"
}

14Calculation

Standard annual income

The same calculation at the applicant's actual age, with no health rating.

{
  "id": "standard_annual_income",
  "key": "standard_annual_income",
  "step": "calculation",
  "name": "Standard annual income",
  "def": 0,
  "formula": "round({{purchase_price}} / 10000 * {{standard_base_rate}} * {{postcode_factor}} * {{standard_guarantee_factor}} * {{payment_factor}} * {{joint_factor}}, 2)"
}

15Calculation

Monthly income

Enhanced annual income divided by 12.

{
  "id": "monthly_income",
  "key": "monthly_income",
  "step": "calculation",
  "name": "Monthly income",
  "def": 0,
  "formula": "round({{enhanced_annual_income}} / 12, 2)"
}

16Calculation

Enhancement

Enhanced annual income less standard annual income.

{
  "id": "enhancement",
  "key": "enhancement",
  "step": "calculation",
  "name": "Enhancement",
  "def": 0,
  "formula": "round({{enhanced_annual_income}} - {{standard_annual_income}}, 2)"
}

Worked example

Demo case: Judith Halloran, joint life

This quote was priced by the Ptally rating engine. The trace below follows it through every step to the final result.

Quote input

{
  "quote_date": "2026-11-10",
  "main_dob": "1959-03-14",
  "spouse_dob": "1957-08-02",
  "basis": "joint",
  "survivor_pct": 66.67,
  "escalation": "level",
  "guarantee_years": 5,
  "frequency": "monthly",
  "timing": "advance",
  "purchase_price": 184912.5,
  "postcode": "TA19 0ZZ",
  "smoker_status": "former",
  "cigs_per_day": 20,
  "years_quit": 11,
  "bmi": 30.9,
  "diabetes_type2": true,
  "hypertension": true,
  "medicines_unmatched": true
}

Result14,876.14VALIDREFER

Calculation trace

Ages and postcode areaTransform
{{main_dob.age(YY, quote_date)}} → 67{{spouse_dob.age(YY, quote_date)}} → 69{{postcode.postcode(area)}} → "TA"
Health and lifestyle loadsTransform
true === true ? 2 : 0 → 2true === true ? 1 : 0 → 1"former" === 'current' ? 3 : "former" === 'former' && 11 < 10 ? 1 : 0 → 030.9 > 30 ? 1 : 0 → 1
Health ratingCalculation
2 + 1 + 0 + 1 = 4
Rated ageCalculation
min(67 + 4, 100) = 71
Joint life termsTransform
"joint" === 'joint' ? 66.67 : 0 → 66.67"joint" === 'joint' && 69 > 0 ? 69 - 67 : 0 → 2
Decline rulesDecline rules
Purchase price under 10,000: not firedApplicant age outside 55 to 85: not firedJoint life without spouse date of birth: not fired
Refer rulesRefer rules
Medicine with no declared condition: firedHealth rating over 6 years: not firedPurchase price over 1,000,000: not fired
Base annuity ratesLookup table
enhanced_base_rate = 874.54 · standard_base_rate = 794.8
Postcode area factorLookup table
postcode_factor = 1.01
Guarantee factorLookup table
enhanced_guarantee_factor = 0.99 · standard_guarantee_factor = 0.997
Frequency and timing factorLookup table
payment_factor = 1
Joint life factorLookup table
joint_factor = 0.92
Enhanced annual incomeCalculation
round(184,912.5 / 10000 * 874.54 * 1.01 * 0.99 * 1 * 0.92, 2) = 14,876.14
Standard annual incomeCalculation
round(184,912.5 / 10000 * 794.8 * 1.01 * 0.997 * 1 * 0.92, 2) = 13,615.34
Monthly incomeCalculation
round(14,876.14 / 12, 2) = 1,239.68
EnhancementCalculation
round(14,876.14 - 13,615.34, 2) = 1,260.8

From the documents

What the AI client read

The adviser uploaded 5 files. The AI client extracted 41 fields, each linked to the page it came from, then built the quote input above.

Field	Value	Source
`applicant_name`	Judith Halloran	Application form p1
`applicant_dob`	1959-03-14	Application form p1
`applicant_ni_number`	QQ 12 34 56 C	Application form p1
`applicant_postcode`	TA19 0ZZ	Application form p1
`applicant_phone`	07700 900418	Application form p1
`applicant_email`	judith.halloran@example.com	Application form p1
`spouse_name`	Peter Halloran	Application form p2
`spouse_dob`	1957-08-02	Application form p2
`spouse_ni_number`	QQ 65 43 21 A	Application form p2
`height_m`	1.63	Questionnaire p2
`weight_kg`	82	Questionnaire p2
`bmi`	30.9	Calculated from questionnaire p2
`smoker_status`	former	Questionnaire p2
`cigs_per_day`	20	Questionnaire p2
`years_smoked`	30	Questionnaire p2
`year_stopped`	2015	Questionnaire p2
`alcohol_units_per_week`	6	Questionnaire p2
`diabetes_type2`	true	Questionnaire p3
`diabetes_diagnosed`	2019	Questionnaire p3
`diabetes_medicine`	Metformin 500 mg twice daily	Questionnaire p3, prescription
`hypertension`	true	Questionnaire p3
`hypertension_medicine`	Ramipril 5 mg daily	Questionnaire p3, prescription
`other_conditions_declared`	none	Questionnaire p3
`prescription_item_1`	Metformin 500 mg	Prescription
`prescription_item_2`	Ramipril 5 mg	Prescription
`prescription_item_3`	Atorvastatin 20 mg (spouse)	Prescription
`prescription_date`	2026-10-21	Prescription
`medicines_unmatched`	true	Prescription against questionnaire p3
`pp_provider`	Demo Personal Pension	Pension statement PP p1
`pp_policy_number`	DPP-0048213	Pension statement PP p1
`pp_fund_value`	182400	Pension statement PP p1
`pp_statement_date`	2026-10-31	Pension statement PP p1
`pp_transfer`	full	Pension statement PP p1
`pp_protected_tax_free_cash`	false	Pension statement PP p2
`gpp_provider`	Demo Workplace Pension Trust	Workplace pension valuation, Summary sheet
`gpp_policy_number`	DWPT-771905	Workplace pension valuation, Summary sheet
`gpp_fund_value`	64150	Workplace pension valuation, Summary sheet
`gpp_statement_date`	2026-10-28	Workplace pension valuation, Summary sheet
`gpp_transfer`	full	Workplace pension valuation, Summary sheet
`gpp_protected_tax_free_cash`	false	Workplace pension valuation, Options sheet
`guaranteed_annuity_rate`	false	Pension statement PP p2, valuation Options sheet

Over MCP

The run_quote call

The AI client prices the case with one tool call and saves it. A referral doesn't stop the price; it flags the case for an underwriter.

Request

{
  "project_reference": "<your Individual Annuity project>",
  "save": true,
  "input": {
    "quote_date": "2026-11-10",
    "main_dob": "1959-03-14",
    "spouse_dob": "1957-08-02",
    "basis": "joint",
    "survivor_pct": 66.67,
    "escalation": "level",
    "guarantee_years": 5,
    "frequency": "monthly",
    "timing": "advance",
    "purchase_price": 184912.5,
    "postcode": "TA19 0ZZ",
    "smoker_status": "former",
    "cigs_per_day": 20,
    "years_quit": 11,
    "bmi": 30.9,
    "diabetes_type2": true,
    "hypertension": true,
    "medicines_unmatched": true
  }
}

Response (abridged)

{
  "dry_run": false,
  "quote_reference": "PTQ-DEMO-24117",
  "valid": true,
  "result": 14876.14,
  "output": {
    "annual_income": 14876.14,
    "monthly_income": 1239.68,
    "standard_annual_income": 13615.34,
    "enhancement": 1260.8,
    "rating_years": 4,
    "basis_version": "demo-basis-2026-11-03",
    "refer": true
  },
  "refers": ["Medicine with no declared condition"]
}

Case history

Data hash 32e276ab

Event	Time	Actor	Detail
Documents received	09:02	Adviser	5 files
Fields extracted	09:03	Claude · MCP	41 fields, each linked to a page
Checks run	09:03	Ptally	1 referral: spouse medicine
Quoted and saved	09:04	Claude · MCP	£14,876.14 a year · demo-basis-2026-11-03
Options compared	09:11	Adviser	RPI £10,939.97 · no guarantee £15,026.41
Referral cleared	09:20	Underwriter	High cholesterol confirmed, no change
Pack generated	09:26	Ptally	Data hash 32e276ab
Sent for signature	09:31	Adviser	Applicant, spouse, adviser

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